Original Research

Posttraumatic stress disorder (PTSD) is a common psychiatric condition in the veteran population and is associated with significant sleep disturbances and trauma-related nightmares.¹ PTSD can present with intrusive symptoms, such as recurrent memories or dreams, which are associated with traumatic events.² Clinical studies have described an increase in central nervous system (CNS) noradrenergic activity in PTSD; specifically, noradrenergic outflow and/or postsynaptic adrenoreceptor responsiveness is increased.^3,4 Targeting a reduction in noradrenergic activity via antagonism of noradrenergic receptors has been a therapeutic treatment strategy in PTSD.

Prazosin crosses the blood-brain barrier and works to antagonize α-1 adrenoreceptors to decrease noradrenergic outflow.⁵ It has been shown in multiple trials to effectively reduce nightmares and improve sleep quality in the veteran population.^6-12 However, a recent negative trial contributed to a downgraded recommendation for prazosin in the treatment of PTSD-related nightmares in the joint PTSD guideline from the US Department of Veterans Affairs (VA) and US Department of Defense (DoD).^13,14

The diagnosis of PTSD in veterans aged ≥ 65 years has been increasing due to improved recognition.¹⁵ As a result, prazosin may be considered more frequently as a treatment option for those patients who report PTSD-related nightmares. It is important to recognize that the normal physiologic process of aging is associated with increased noradrenergic outflow, which may change the pharmacodynamics of prazosin in geriatric patients.^12,16 This may necessitate increased doses to adequately antagonize the α-1 adenoreceptor.¹⁷ High doses of prazosin may increase the risk of hypotension in older patients.¹² This increased risk is especially concerning for patients who already receive multiple medications or have comorbid conditions that impact blood pressure (BP).

The existing literature has few studies that have reported on outcomes with prazosin use in older veterans.^11,12 The few existing reports provide clinically valuable descriptions of tolerability and efficacy with prazosin. For example, Peskind and colleagues showed prazosin to be an effective agent in the treatment of PTSD-related nightmares.¹² However, in older veterans prazosin dosing > 4 mg has not been described or reported in the literature.

There appears to be a lack of clinical guidance with regards to dosing of prazosin in older patients. The goal of the current study was to assess the outcomes of older veterans with PTSD under pharmacist management of prazosin at our outpatient Prazosin Titration Clinic (PTC) in order to contribute to the minimal, yet valuable, existing clinical literature.

Methods

This study was approved by the University of Iowa Institutional Review Board and Iowa City Veterans Affairs Health Care System (ICVAHCS) research and development committee. The study was a retrospective chart review of older patients with consultations referred to the ICVAHCS PTC. To be eligible for inclusion, veterans with a PTSD diagnosis must have been evaluated at an initial consult appointment with a mental health clinical pharmacy specialist (MH CPS) from February 1, 2016 to August 31, 2018, and had at least 1 follow-up appointment. Follow-up visits were conducted either by telephone or in a face-to-face clinic visit.

 

Prazosin Titration Clinics

VA health care systems use pharmacists to manage veterans prescribed prazosin through PTC consultations. PTCs provide a process for close follow-up and assessment of PTSD-related outcomes. Due to the frequency of follow-up, this service may be beneficial for older veterans with more complex comorbidities and medication regimens. Any veteran with PTSD-related nightmares may be referred to the PTC for a consultation by any health care provider. Once referred to the clinic, MH CPSs assume responsibility for the prazosin prescription, including dose adjustments. For example, if a veteran reported no issues with tolerability but continued to have frequent and distressing nightmares, the dose may be increased, typically by 1-mg to 2-mg increments. Once the veteran reaches a stable and tolerable dose of prazosin, they are discharged from the PTC, and the referring health care provider resumes responsibility for the prazosin prescription.

Clinically Measured Outcomes

Nightmare frequency and intensity were measured using the Recurrent Distressing Dreams item B2 of the Clinician Administered PTSD Scale (CAPS) (Table 1). The PTSD Checklist (PCL-5), Insomnia Severity Index (ISI), and total sleep hours were used to determine the effect of prazosin on symptom severity (Table 2). The PCL-5 is a 20-item self-report used to monitor and quantify symptom level and change over time. It evaluates the frequency over the past month that a patient was bothered by any of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) PTSD criterion.² Scores range from 0 (not at all) to 4 (extreme), with a maximum score of 80. The ISI is a 7-item self-report of sleep symptoms, with a total score of 28, where increasing scores indicate increasing severity of insomnia (Table 3).

Clinically measured outcome scales were performed and assessed by MH CPSs. CAPS frequency and intensity were measured at each clinic visit. PCL-5 and ISI scores were assessed at baseline and at the endpoint of study or discharge from clinic (Table 4). Patients who continued in the PTC after the end of the study date or who were lost to follow-up did not complete these measures at time of discharge.

Data Analysis

The primary outcome was change in CAPS nightmare frequency and intensity from time of initial clinic visit to time of discharge or end of study. The secondary outcomes included change in PCL-5, ISI, and sleep hours. Other secondary outcomes included measures of tolerability: BP changes, adverse effects (AEs) reported, and outcome of prazosin therapy when AEs were reported. Change in PTSD symptoms, PCL-5, and ISI were assessed using the Wilcoxon signed rank tests. Findings were considered to be statistically significant at P ≤ .05. Other variables were reported descriptively.

Results

Thirty-two veterans, aged ≥ 65 years, with clinical diagnosis of PTSD at the time of referral to the PTC were reviewed (Table 5). All patients were male and 93.8% were white. Thirty were Vietnam era veterans, 1 served in the Persian Gulf era, and 2 served in the post-Korean War era. Twenty-eight veterans had a combat history. Severe PTSD symptoms were reported as indicated by baseline PCL-5 scores, and moderate severity insomnia symptoms as indicated by baseline ISI scores.

 

All veterans had at least 1 comorbid medical condition, and the majority had multiple medical comorbidities. All were taking multiple medical and psychiatric medications. More than 80% of veterans were taking antihypertensive agents at baseline (Table 6). Twenty-two of the 32 veterans were prescribed a VA/DoD PTSD guideline-recommended antidepressant.

Primary Outcomes

The baseline, final, and changes in the primary outcomes are included in the Figure. Treatment with prazosin was associated with significant improvement in median scores from baseline to endpoint for CAPS nightmare frequency (-2, P = .0001), CAPS nightmare intensity (-2, P = .001), and total CAPS item score (-4, P < .001).

Secondary Outcomes

Of the 32 patients included in the study, PCL-5 was obtained from 20 veterans and ISI from 17 veterans at discharge from clinic. Thirty veterans reported final sleep hours, 2 veterans were unable to quantify average sleep hours per night at their final visit. PTSD symptom severity showed significant median change from baseline to endpoint of management in PTC for PCL-5 (-20.5, P = .0002) and ISI (-6.5, P = .002). Total sleep hours also showed significant improvement from baseline to endpoint (1.5, P = .003) (Table 7).

Prazosin Dosing

Maximum prazosin total daily doses were evaluated from the study baseline to the endpoint (Table 8). The mean (SD) maximum total daily dose of prazosin reached was 5.6 (5.1) mg (median, 3.5 mg; range, 1-17 mg). The mean (SD) total daily dose of prazosin at endpoint of study was 5.1 (5.3) mg (median, 2.5 mg; range, 0-17 mg). The average (SD) change of prazosin dose from baseline to endpoint was 3.5 (4.6) mg (median, 2 mg; range, -2 to 15 mg).

Tolerability

The average (SD) baseline systolic BP (SBP) was 135.8 (20.5) mm Hg and diastolic BP (DBP) was 77.2 (11.0) mm Hg. The average SBP and DBP at study endpoint were 131.8 (16.6) mm Hg and 75.9 (13.7) mm Hg, respectively. Endpoint BP values were missing for 6 patients.

Nine of 32 veterans reported AEs during PTC management of prazosin. Dizziness was the most common AE reported. Other AEs noted included orthostatic hypotension, headache, and falls. Of 12 reported AEs, 8 were related to dizziness, 5 of which were transient or tolerable. One veteran had a dose reduction of prazosin due to dizziness, and 3 veterans discontinued prazosin due to orthostasis. Several veterans had changes made to their antihypertensive medication regimen during prazosin titration, including dose reductions and/or decreased number of medications. If indicated, the MH CPS collaborated with the antihypertensive prescriber to make dosing adjustments. Two veterans reported a fall during prazosin titration; 1 veteran had other mobility-related factors thought to precipitate to their fall, and neither veterans were injured because of the falls.

Twenty-eight veterans (87.5%) treated in the PTC continued prazosin therapy after discharge. Six months postdischarge, 70% of veterans had maintained prazosin therapy. Two veterans required a dose increase postdischarge from PTC, and 1 veteran required a dose reduction. About one-third of veterans included in this study continued in the PTC beyond the end of the study period. Common reasons for clinic discharge were symptom resolution (37.5%), adverse reactions (12.5%), lost to follow-up (6.3%), or nonadherence (3.1%).

 

Discussion

The existing literature reports few outcomes for older veterans prescribed prazosin for PTSD. One report included a 75-year-old otherwise-healthy veteran, who received 2-mg prazosin at bedtime. At this dose, he reported good tolerability and response, as indicated by a reduction in his CAPS nightmare severity score.¹¹ An open-label trial assessed prazosin in 9 geriatric men with chronic PTSD and found low-dose prazosin (average [SD] maximum prazosin dose reported was 2.3 [0.7] mg, range 2-4 mg per day) greatly reduced nightmares and overall PTSD severity in 8 of 9 subjects.¹² Despite the veterans in that study having multiple medical comorbid conditions and taking concomitant medications, prazosin was reported to be well tolerated, and changes in BP were determined to be clinically insignificant.¹² A recent study of middle-aged veterans (average [SD] age 52 [14] years) reported prazosin did not significantly alleviate PTSD-related nightmares.¹³ However, we observed prazosin therapy significantly reduced nightmares and sleep disturbances, and significantly improved PTSD severity in our older veteran population.

To our knowledge, the current study is the largest retrospective study that evaluates prazosin therapy for the treatment of PTSD-related nightmares in older veterans. The findings of this study are similar to a previous study in older veterans as well as studies of prazosin in younger and middle-aged adult veterans, with the average age ranging from 30 to 56 years.^6-12 Like the previously reported studies, prazosin also was well tolerated in our sample of veterans with multiple comorbidities and concomitant medications. Changes in BP were not clinically significant.

Studies have demonstrated increased noradrenergic activity as a component of the normal aging process.^16,17 This may require utilizing caution during prazosin dose titration and frequent patient assessment, due to the concern for risk of hypotension in older patients and in particular those who may require increased doses to achieve efficacy. In our study, favorable outcomes were achieved at an average (SD) total daily dose of 5.1 (5.3) mg (median, 2.5 mg; range 0-17 mg). A previous report showed efficacy of prazosin around an average (SD) maximum dose of 2.3 (0.7) mg, which is lower than the doses reported in the current study.¹² In addition, 13 veterans (40.6%) from our sample reached doses of ≥ 5 mg per day, and 8 veterans (25.0%) reached doses of ≥ 10 mg per day.

The doses reached in this study were reflective of a management approach using assessment of patient-reported symptoms at weekly to biweekly follow-up visits. The individualized management approach applied in the PTC by MH CPSs aids in uncovering the most efficacious and tolerated dose of prazosin for each veteran. Evaluation of symptom change during treatment in PTC was facilitated use of objective rating scales, which helped measure nightmare frequency and intensity, sleep satisfaction, and global PTSD severity. Given the variability in dosing of prazosin reported in the literature, further studies may be warranted to provide more definitive clinical guidance as far as dosing prazosin in older patients.

The study by Peskind and colleaguesrationalized that lower doses of prazosin may be used in older patients given pharmacokinetic effects of aging, age-associated changes in PTSD pathophysiology, and effects and interactions of concomitant medications.¹² However, our study found that prazosin could be well tolerated at higher doses. The rate of discontinuation due to intolerable AEs was low. AEs reported were consistent with the established AE profile of prazosin, with dizziness, orthostasis, and headache most commonly reported. Similar to the Peskind and colleagues study, BP had a tendency to decrease in this current study; however, the change was not clinically significant.¹² That study also reported transient dizziness with prazosin titration, which was shown to be tolerable in the majority of our veterans reporting dizziness.¹² Other common AEs with prazosin, such as rash, priapism, sedation, syncope, other cardiac AEs, and sleep disturbance were not reported in our study population.

MH CPS-managed PTCs are one venue that may allow veterans to achieve favorable outcomes through frequent follow-up. As prazosin dosing is specific to each individual patient, frequent follow-up visits are helpful in determining optimal doses that maximize efficacy while minimizing intolerable AEs. The majority of veterans treated in our PTC continued use of prazosin 6 months postdischarge, while 3 veterans required a postdischarge dose change.

The 2017 VA/DoD PTSD guidelines recommend individual, trauma-focused psychotherapy over pharmacologic therapy for the primary treatment of PTSD.¹⁴ About half of the veterans in the current study participated in either group or individual psychotherapy during enrollment in the PTC. A systematic review of psychotherapy in older veterans reported mixed results, with 4 studies indicating positive effects of therapy, while the other 3 studies reported no benefit or mixed effects for PTSD symptoms. The review concluded that fewer older adults experience complete remission of symptoms with psychotherapy alone.¹⁸ A previous study of older veterans described improvement in PTSD-related symptoms with prazosin without concurrent psychotherapy.¹²

 

Limitations and Strengths

While this study is the largest study to evaluate outcomes of prazosin in older patients with PTSD, there are several important limitations. The study population was small and all were male. The results of this study may not be applicable to women. Another limitation was several missing values in our data set, as some secondary outcomes were not collected via telephone follow-up visits. This could potentially contribute a measurement bias in the reported secondary outcomes results, specifically for the PCL-5 and ISI. Additionally, some veterans in this study may have reported symptomatic improvement based on the additional supportive intervention that clinical pharmacists were able to offer, as well as concomitant participation in psychotherapy. This may be reflected in the study results. This study did not have a true placebo group, as we may find a reduction in symptoms with placebo.

Strengths of this study include multiple data points for assessment of prazosin tolerability and a pre- and poststudy design, which allowed for the veterans to serve as their own control. Another strength of this study is that data were complete for primary outcome measures, including the CAPS Recurrent and Distressing Dreams Item, where prazosin showed significant benefit in reduction of PTSD-related nightmares. While the results of this study are reassuring, further randomized, double-blind, placebo-controlled trials are likely needed in order to establish efficacy and tolerability of prazosin in older veterans for PTSD related nightmares.

Conclusion

These results demonstrate prazosin therapy in older veterans can significantly improve PTSD-related nightmares and PTSD severity. Prazosin was well tolerated in this population at doses higher than previously reported in other studies. This study shows that prazosin therapy can be effectively managed and tolerated in older veterans with complex medical and psychiatric comorbidities to provide favorable patient outcomes.

Acknowledgments

This material is the result of work supported with resources and the use of facilities at the Iowa City VA Health Care System and by the Health Services Research and Development Service, US Department of Veterans Affairs.

Posttraumatic stress disorder (PTSD) is a common psychiatric condition in the veteran population and is associated with significant sleep disturbances and trauma-related nightmares.¹ PTSD can present with intrusive symptoms, such as recurrent memories or dreams, which are associated with traumatic events.² Clinical studies have described an increase in central nervous system (CNS) noradrenergic activity in PTSD; specifically, noradrenergic outflow and/or postsynaptic adrenoreceptor responsiveness is increased.^3,4 Targeting a reduction in noradrenergic activity via antagonism of noradrenergic receptors has been a therapeutic treatment strategy in PTSD.

Prazosin crosses the blood-brain barrier and works to antagonize α-1 adrenoreceptors to decrease noradrenergic outflow.⁵ It has been shown in multiple trials to effectively reduce nightmares and improve sleep quality in the veteran population.^6-12 However, a recent negative trial contributed to a downgraded recommendation for prazosin in the treatment of PTSD-related nightmares in the joint PTSD guideline from the US Department of Veterans Affairs (VA) and US Department of Defense (DoD).^13,14

The diagnosis of PTSD in veterans aged ≥ 65 years has been increasing due to improved recognition.¹⁵ As a result, prazosin may be considered more frequently as a treatment option for those patients who report PTSD-related nightmares. It is important to recognize that the normal physiologic process of aging is associated with increased noradrenergic outflow, which may change the pharmacodynamics of prazosin in geriatric patients.^12,16 This may necessitate increased doses to adequately antagonize the α-1 adenoreceptor.¹⁷ High doses of prazosin may increase the risk of hypotension in older patients.¹² This increased risk is especially concerning for patients who already receive multiple medications or have comorbid conditions that impact blood pressure (BP).

The existing literature has few studies that have reported on outcomes with prazosin use in older veterans.^11,12 The few existing reports provide clinically valuable descriptions of tolerability and efficacy with prazosin. For example, Peskind and colleagues showed prazosin to be an effective agent in the treatment of PTSD-related nightmares.¹² However, in older veterans prazosin dosing > 4 mg has not been described or reported in the literature.

There appears to be a lack of clinical guidance with regards to dosing of prazosin in older patients. The goal of the current study was to assess the outcomes of older veterans with PTSD under pharmacist management of prazosin at our outpatient Prazosin Titration Clinic (PTC) in order to contribute to the minimal, yet valuable, existing clinical literature.

Methods

This study was approved by the University of Iowa Institutional Review Board and Iowa City Veterans Affairs Health Care System (ICVAHCS) research and development committee. The study was a retrospective chart review of older patients with consultations referred to the ICVAHCS PTC. To be eligible for inclusion, veterans with a PTSD diagnosis must have been evaluated at an initial consult appointment with a mental health clinical pharmacy specialist (MH CPS) from February 1, 2016 to August 31, 2018, and had at least 1 follow-up appointment. Follow-up visits were conducted either by telephone or in a face-to-face clinic visit.

 

Prazosin Titration Clinics

VA health care systems use pharmacists to manage veterans prescribed prazosin through PTC consultations. PTCs provide a process for close follow-up and assessment of PTSD-related outcomes. Due to the frequency of follow-up, this service may be beneficial for older veterans with more complex comorbidities and medication regimens. Any veteran with PTSD-related nightmares may be referred to the PTC for a consultation by any health care provider. Once referred to the clinic, MH CPSs assume responsibility for the prazosin prescription, including dose adjustments. For example, if a veteran reported no issues with tolerability but continued to have frequent and distressing nightmares, the dose may be increased, typically by 1-mg to 2-mg increments. Once the veteran reaches a stable and tolerable dose of prazosin, they are discharged from the PTC, and the referring health care provider resumes responsibility for the prazosin prescription.

Clinically Measured Outcomes

Nightmare frequency and intensity were measured using the Recurrent Distressing Dreams item B2 of the Clinician Administered PTSD Scale (CAPS) (Table 1). The PTSD Checklist (PCL-5), Insomnia Severity Index (ISI), and total sleep hours were used to determine the effect of prazosin on symptom severity (Table 2). The PCL-5 is a 20-item self-report used to monitor and quantify symptom level and change over time. It evaluates the frequency over the past month that a patient was bothered by any of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) PTSD criterion.² Scores range from 0 (not at all) to 4 (extreme), with a maximum score of 80. The ISI is a 7-item self-report of sleep symptoms, with a total score of 28, where increasing scores indicate increasing severity of insomnia (Table 3).

Clinically measured outcome scales were performed and assessed by MH CPSs. CAPS frequency and intensity were measured at each clinic visit. PCL-5 and ISI scores were assessed at baseline and at the endpoint of study or discharge from clinic (Table 4). Patients who continued in the PTC after the end of the study date or who were lost to follow-up did not complete these measures at time of discharge.

Data Analysis

The primary outcome was change in CAPS nightmare frequency and intensity from time of initial clinic visit to time of discharge or end of study. The secondary outcomes included change in PCL-5, ISI, and sleep hours. Other secondary outcomes included measures of tolerability: BP changes, adverse effects (AEs) reported, and outcome of prazosin therapy when AEs were reported. Change in PTSD symptoms, PCL-5, and ISI were assessed using the Wilcoxon signed rank tests. Findings were considered to be statistically significant at P ≤ .05. Other variables were reported descriptively.

Results

Thirty-two veterans, aged ≥ 65 years, with clinical diagnosis of PTSD at the time of referral to the PTC were reviewed (Table 5). All patients were male and 93.8% were white. Thirty were Vietnam era veterans, 1 served in the Persian Gulf era, and 2 served in the post-Korean War era. Twenty-eight veterans had a combat history. Severe PTSD symptoms were reported as indicated by baseline PCL-5 scores, and moderate severity insomnia symptoms as indicated by baseline ISI scores.

 

All veterans had at least 1 comorbid medical condition, and the majority had multiple medical comorbidities. All were taking multiple medical and psychiatric medications. More than 80% of veterans were taking antihypertensive agents at baseline (Table 6). Twenty-two of the 32 veterans were prescribed a VA/DoD PTSD guideline-recommended antidepressant.

Primary Outcomes

The baseline, final, and changes in the primary outcomes are included in the Figure. Treatment with prazosin was associated with significant improvement in median scores from baseline to endpoint for CAPS nightmare frequency (-2, P = .0001), CAPS nightmare intensity (-2, P = .001), and total CAPS item score (-4, P < .001).

Secondary Outcomes

Of the 32 patients included in the study, PCL-5 was obtained from 20 veterans and ISI from 17 veterans at discharge from clinic. Thirty veterans reported final sleep hours, 2 veterans were unable to quantify average sleep hours per night at their final visit. PTSD symptom severity showed significant median change from baseline to endpoint of management in PTC for PCL-5 (-20.5, P = .0002) and ISI (-6.5, P = .002). Total sleep hours also showed significant improvement from baseline to endpoint (1.5, P = .003) (Table 7).

Prazosin Dosing

Maximum prazosin total daily doses were evaluated from the study baseline to the endpoint (Table 8). The mean (SD) maximum total daily dose of prazosin reached was 5.6 (5.1) mg (median, 3.5 mg; range, 1-17 mg). The mean (SD) total daily dose of prazosin at endpoint of study was 5.1 (5.3) mg (median, 2.5 mg; range, 0-17 mg). The average (SD) change of prazosin dose from baseline to endpoint was 3.5 (4.6) mg (median, 2 mg; range, -2 to 15 mg).

Tolerability

The average (SD) baseline systolic BP (SBP) was 135.8 (20.5) mm Hg and diastolic BP (DBP) was 77.2 (11.0) mm Hg. The average SBP and DBP at study endpoint were 131.8 (16.6) mm Hg and 75.9 (13.7) mm Hg, respectively. Endpoint BP values were missing for 6 patients.

Nine of 32 veterans reported AEs during PTC management of prazosin. Dizziness was the most common AE reported. Other AEs noted included orthostatic hypotension, headache, and falls. Of 12 reported AEs, 8 were related to dizziness, 5 of which were transient or tolerable. One veteran had a dose reduction of prazosin due to dizziness, and 3 veterans discontinued prazosin due to orthostasis. Several veterans had changes made to their antihypertensive medication regimen during prazosin titration, including dose reductions and/or decreased number of medications. If indicated, the MH CPS collaborated with the antihypertensive prescriber to make dosing adjustments. Two veterans reported a fall during prazosin titration; 1 veteran had other mobility-related factors thought to precipitate to their fall, and neither veterans were injured because of the falls.

Twenty-eight veterans (87.5%) treated in the PTC continued prazosin therapy after discharge. Six months postdischarge, 70% of veterans had maintained prazosin therapy. Two veterans required a dose increase postdischarge from PTC, and 1 veteran required a dose reduction. About one-third of veterans included in this study continued in the PTC beyond the end of the study period. Common reasons for clinic discharge were symptom resolution (37.5%), adverse reactions (12.5%), lost to follow-up (6.3%), or nonadherence (3.1%).

 

Discussion

The existing literature reports few outcomes for older veterans prescribed prazosin for PTSD. One report included a 75-year-old otherwise-healthy veteran, who received 2-mg prazosin at bedtime. At this dose, he reported good tolerability and response, as indicated by a reduction in his CAPS nightmare severity score.¹¹ An open-label trial assessed prazosin in 9 geriatric men with chronic PTSD and found low-dose prazosin (average [SD] maximum prazosin dose reported was 2.3 [0.7] mg, range 2-4 mg per day) greatly reduced nightmares and overall PTSD severity in 8 of 9 subjects.¹² Despite the veterans in that study having multiple medical comorbid conditions and taking concomitant medications, prazosin was reported to be well tolerated, and changes in BP were determined to be clinically insignificant.¹² A recent study of middle-aged veterans (average [SD] age 52 [14] years) reported prazosin did not significantly alleviate PTSD-related nightmares.¹³ However, we observed prazosin therapy significantly reduced nightmares and sleep disturbances, and significantly improved PTSD severity in our older veteran population.

To our knowledge, the current study is the largest retrospective study that evaluates prazosin therapy for the treatment of PTSD-related nightmares in older veterans. The findings of this study are similar to a previous study in older veterans as well as studies of prazosin in younger and middle-aged adult veterans, with the average age ranging from 30 to 56 years.^6-12 Like the previously reported studies, prazosin also was well tolerated in our sample of veterans with multiple comorbidities and concomitant medications. Changes in BP were not clinically significant.

Studies have demonstrated increased noradrenergic activity as a component of the normal aging process.^16,17 This may require utilizing caution during prazosin dose titration and frequent patient assessment, due to the concern for risk of hypotension in older patients and in particular those who may require increased doses to achieve efficacy. In our study, favorable outcomes were achieved at an average (SD) total daily dose of 5.1 (5.3) mg (median, 2.5 mg; range 0-17 mg). A previous report showed efficacy of prazosin around an average (SD) maximum dose of 2.3 (0.7) mg, which is lower than the doses reported in the current study.¹² In addition, 13 veterans (40.6%) from our sample reached doses of ≥ 5 mg per day, and 8 veterans (25.0%) reached doses of ≥ 10 mg per day.

The doses reached in this study were reflective of a management approach using assessment of patient-reported symptoms at weekly to biweekly follow-up visits. The individualized management approach applied in the PTC by MH CPSs aids in uncovering the most efficacious and tolerated dose of prazosin for each veteran. Evaluation of symptom change during treatment in PTC was facilitated use of objective rating scales, which helped measure nightmare frequency and intensity, sleep satisfaction, and global PTSD severity. Given the variability in dosing of prazosin reported in the literature, further studies may be warranted to provide more definitive clinical guidance as far as dosing prazosin in older patients.

The study by Peskind and colleaguesrationalized that lower doses of prazosin may be used in older patients given pharmacokinetic effects of aging, age-associated changes in PTSD pathophysiology, and effects and interactions of concomitant medications.¹² However, our study found that prazosin could be well tolerated at higher doses. The rate of discontinuation due to intolerable AEs was low. AEs reported were consistent with the established AE profile of prazosin, with dizziness, orthostasis, and headache most commonly reported. Similar to the Peskind and colleagues study, BP had a tendency to decrease in this current study; however, the change was not clinically significant.¹² That study also reported transient dizziness with prazosin titration, which was shown to be tolerable in the majority of our veterans reporting dizziness.¹² Other common AEs with prazosin, such as rash, priapism, sedation, syncope, other cardiac AEs, and sleep disturbance were not reported in our study population.

MH CPS-managed PTCs are one venue that may allow veterans to achieve favorable outcomes through frequent follow-up. As prazosin dosing is specific to each individual patient, frequent follow-up visits are helpful in determining optimal doses that maximize efficacy while minimizing intolerable AEs. The majority of veterans treated in our PTC continued use of prazosin 6 months postdischarge, while 3 veterans required a postdischarge dose change.

The 2017 VA/DoD PTSD guidelines recommend individual, trauma-focused psychotherapy over pharmacologic therapy for the primary treatment of PTSD.¹⁴ About half of the veterans in the current study participated in either group or individual psychotherapy during enrollment in the PTC. A systematic review of psychotherapy in older veterans reported mixed results, with 4 studies indicating positive effects of therapy, while the other 3 studies reported no benefit or mixed effects for PTSD symptoms. The review concluded that fewer older adults experience complete remission of symptoms with psychotherapy alone.¹⁸ A previous study of older veterans described improvement in PTSD-related symptoms with prazosin without concurrent psychotherapy.¹²

 

Limitations and Strengths

While this study is the largest study to evaluate outcomes of prazosin in older patients with PTSD, there are several important limitations. The study population was small and all were male. The results of this study may not be applicable to women. Another limitation was several missing values in our data set, as some secondary outcomes were not collected via telephone follow-up visits. This could potentially contribute a measurement bias in the reported secondary outcomes results, specifically for the PCL-5 and ISI. Additionally, some veterans in this study may have reported symptomatic improvement based on the additional supportive intervention that clinical pharmacists were able to offer, as well as concomitant participation in psychotherapy. This may be reflected in the study results. This study did not have a true placebo group, as we may find a reduction in symptoms with placebo.

Strengths of this study include multiple data points for assessment of prazosin tolerability and a pre- and poststudy design, which allowed for the veterans to serve as their own control. Another strength of this study is that data were complete for primary outcome measures, including the CAPS Recurrent and Distressing Dreams Item, where prazosin showed significant benefit in reduction of PTSD-related nightmares. While the results of this study are reassuring, further randomized, double-blind, placebo-controlled trials are likely needed in order to establish efficacy and tolerability of prazosin in older veterans for PTSD related nightmares.

Conclusion

These results demonstrate prazosin therapy in older veterans can significantly improve PTSD-related nightmares and PTSD severity. Prazosin was well tolerated in this population at doses higher than previously reported in other studies. This study shows that prazosin therapy can be effectively managed and tolerated in older veterans with complex medical and psychiatric comorbidities to provide favorable patient outcomes.

Acknowledgments

This material is the result of work supported with resources and the use of facilities at the Iowa City VA Health Care System and by the Health Services Research and Development Service, US Department of Veterans Affairs.

Posttraumatic stress disorder (PTSD) is a common psychiatric condition in the veteran population and is associated with significant sleep disturbances and trauma-related nightmares.¹ PTSD can present with intrusive symptoms, such as recurrent memories or dreams, which are associated with traumatic events.² Clinical studies have described an increase in central nervous system (CNS) noradrenergic activity in PTSD; specifically, noradrenergic outflow and/or postsynaptic adrenoreceptor responsiveness is increased.^3,4 Targeting a reduction in noradrenergic activity via antagonism of noradrenergic receptors has been a therapeutic treatment strategy in PTSD.

Prazosin crosses the blood-brain barrier and works to antagonize α-1 adrenoreceptors to decrease noradrenergic outflow.⁵ It has been shown in multiple trials to effectively reduce nightmares and improve sleep quality in the veteran population.^6-12 However, a recent negative trial contributed to a downgraded recommendation for prazosin in the treatment of PTSD-related nightmares in the joint PTSD guideline from the US Department of Veterans Affairs (VA) and US Department of Defense (DoD).^13,14

The diagnosis of PTSD in veterans aged ≥ 65 years has been increasing due to improved recognition.¹⁵ As a result, prazosin may be considered more frequently as a treatment option for those patients who report PTSD-related nightmares. It is important to recognize that the normal physiologic process of aging is associated with increased noradrenergic outflow, which may change the pharmacodynamics of prazosin in geriatric patients.^12,16 This may necessitate increased doses to adequately antagonize the α-1 adenoreceptor.¹⁷ High doses of prazosin may increase the risk of hypotension in older patients.¹² This increased risk is especially concerning for patients who already receive multiple medications or have comorbid conditions that impact blood pressure (BP).

The existing literature has few studies that have reported on outcomes with prazosin use in older veterans.^11,12 The few existing reports provide clinically valuable descriptions of tolerability and efficacy with prazosin. For example, Peskind and colleagues showed prazosin to be an effective agent in the treatment of PTSD-related nightmares.¹² However, in older veterans prazosin dosing > 4 mg has not been described or reported in the literature.

There appears to be a lack of clinical guidance with regards to dosing of prazosin in older patients. The goal of the current study was to assess the outcomes of older veterans with PTSD under pharmacist management of prazosin at our outpatient Prazosin Titration Clinic (PTC) in order to contribute to the minimal, yet valuable, existing clinical literature.

Methods

This study was approved by the University of Iowa Institutional Review Board and Iowa City Veterans Affairs Health Care System (ICVAHCS) research and development committee. The study was a retrospective chart review of older patients with consultations referred to the ICVAHCS PTC. To be eligible for inclusion, veterans with a PTSD diagnosis must have been evaluated at an initial consult appointment with a mental health clinical pharmacy specialist (MH CPS) from February 1, 2016 to August 31, 2018, and had at least 1 follow-up appointment. Follow-up visits were conducted either by telephone or in a face-to-face clinic visit.

 

Prazosin Titration Clinics

VA health care systems use pharmacists to manage veterans prescribed prazosin through PTC consultations. PTCs provide a process for close follow-up and assessment of PTSD-related outcomes. Due to the frequency of follow-up, this service may be beneficial for older veterans with more complex comorbidities and medication regimens. Any veteran with PTSD-related nightmares may be referred to the PTC for a consultation by any health care provider. Once referred to the clinic, MH CPSs assume responsibility for the prazosin prescription, including dose adjustments. For example, if a veteran reported no issues with tolerability but continued to have frequent and distressing nightmares, the dose may be increased, typically by 1-mg to 2-mg increments. Once the veteran reaches a stable and tolerable dose of prazosin, they are discharged from the PTC, and the referring health care provider resumes responsibility for the prazosin prescription.

Clinically Measured Outcomes

Nightmare frequency and intensity were measured using the Recurrent Distressing Dreams item B2 of the Clinician Administered PTSD Scale (CAPS) (Table 1). The PTSD Checklist (PCL-5), Insomnia Severity Index (ISI), and total sleep hours were used to determine the effect of prazosin on symptom severity (Table 2). The PCL-5 is a 20-item self-report used to monitor and quantify symptom level and change over time. It evaluates the frequency over the past month that a patient was bothered by any of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) PTSD criterion.² Scores range from 0 (not at all) to 4 (extreme), with a maximum score of 80. The ISI is a 7-item self-report of sleep symptoms, with a total score of 28, where increasing scores indicate increasing severity of insomnia (Table 3).

Clinically measured outcome scales were performed and assessed by MH CPSs. CAPS frequency and intensity were measured at each clinic visit. PCL-5 and ISI scores were assessed at baseline and at the endpoint of study or discharge from clinic (Table 4). Patients who continued in the PTC after the end of the study date or who were lost to follow-up did not complete these measures at time of discharge.

Data Analysis

The primary outcome was change in CAPS nightmare frequency and intensity from time of initial clinic visit to time of discharge or end of study. The secondary outcomes included change in PCL-5, ISI, and sleep hours. Other secondary outcomes included measures of tolerability: BP changes, adverse effects (AEs) reported, and outcome of prazosin therapy when AEs were reported. Change in PTSD symptoms, PCL-5, and ISI were assessed using the Wilcoxon signed rank tests. Findings were considered to be statistically significant at P ≤ .05. Other variables were reported descriptively.

Results

Thirty-two veterans, aged ≥ 65 years, with clinical diagnosis of PTSD at the time of referral to the PTC were reviewed (Table 5). All patients were male and 93.8% were white. Thirty were Vietnam era veterans, 1 served in the Persian Gulf era, and 2 served in the post-Korean War era. Twenty-eight veterans had a combat history. Severe PTSD symptoms were reported as indicated by baseline PCL-5 scores, and moderate severity insomnia symptoms as indicated by baseline ISI scores.

 

All veterans had at least 1 comorbid medical condition, and the majority had multiple medical comorbidities. All were taking multiple medical and psychiatric medications. More than 80% of veterans were taking antihypertensive agents at baseline (Table 6). Twenty-two of the 32 veterans were prescribed a VA/DoD PTSD guideline-recommended antidepressant.

Primary Outcomes

The baseline, final, and changes in the primary outcomes are included in the Figure. Treatment with prazosin was associated with significant improvement in median scores from baseline to endpoint for CAPS nightmare frequency (-2, P = .0001), CAPS nightmare intensity (-2, P = .001), and total CAPS item score (-4, P < .001).

Secondary Outcomes

Of the 32 patients included in the study, PCL-5 was obtained from 20 veterans and ISI from 17 veterans at discharge from clinic. Thirty veterans reported final sleep hours, 2 veterans were unable to quantify average sleep hours per night at their final visit. PTSD symptom severity showed significant median change from baseline to endpoint of management in PTC for PCL-5 (-20.5, P = .0002) and ISI (-6.5, P = .002). Total sleep hours also showed significant improvement from baseline to endpoint (1.5, P = .003) (Table 7).

Prazosin Dosing

Maximum prazosin total daily doses were evaluated from the study baseline to the endpoint (Table 8). The mean (SD) maximum total daily dose of prazosin reached was 5.6 (5.1) mg (median, 3.5 mg; range, 1-17 mg). The mean (SD) total daily dose of prazosin at endpoint of study was 5.1 (5.3) mg (median, 2.5 mg; range, 0-17 mg). The average (SD) change of prazosin dose from baseline to endpoint was 3.5 (4.6) mg (median, 2 mg; range, -2 to 15 mg).

Tolerability

The average (SD) baseline systolic BP (SBP) was 135.8 (20.5) mm Hg and diastolic BP (DBP) was 77.2 (11.0) mm Hg. The average SBP and DBP at study endpoint were 131.8 (16.6) mm Hg and 75.9 (13.7) mm Hg, respectively. Endpoint BP values were missing for 6 patients.

Nine of 32 veterans reported AEs during PTC management of prazosin. Dizziness was the most common AE reported. Other AEs noted included orthostatic hypotension, headache, and falls. Of 12 reported AEs, 8 were related to dizziness, 5 of which were transient or tolerable. One veteran had a dose reduction of prazosin due to dizziness, and 3 veterans discontinued prazosin due to orthostasis. Several veterans had changes made to their antihypertensive medication regimen during prazosin titration, including dose reductions and/or decreased number of medications. If indicated, the MH CPS collaborated with the antihypertensive prescriber to make dosing adjustments. Two veterans reported a fall during prazosin titration; 1 veteran had other mobility-related factors thought to precipitate to their fall, and neither veterans were injured because of the falls.

Twenty-eight veterans (87.5%) treated in the PTC continued prazosin therapy after discharge. Six months postdischarge, 70% of veterans had maintained prazosin therapy. Two veterans required a dose increase postdischarge from PTC, and 1 veteran required a dose reduction. About one-third of veterans included in this study continued in the PTC beyond the end of the study period. Common reasons for clinic discharge were symptom resolution (37.5%), adverse reactions (12.5%), lost to follow-up (6.3%), or nonadherence (3.1%).

 

Discussion

The existing literature reports few outcomes for older veterans prescribed prazosin for PTSD. One report included a 75-year-old otherwise-healthy veteran, who received 2-mg prazosin at bedtime. At this dose, he reported good tolerability and response, as indicated by a reduction in his CAPS nightmare severity score.¹¹ An open-label trial assessed prazosin in 9 geriatric men with chronic PTSD and found low-dose prazosin (average [SD] maximum prazosin dose reported was 2.3 [0.7] mg, range 2-4 mg per day) greatly reduced nightmares and overall PTSD severity in 8 of 9 subjects.¹² Despite the veterans in that study having multiple medical comorbid conditions and taking concomitant medications, prazosin was reported to be well tolerated, and changes in BP were determined to be clinically insignificant.¹² A recent study of middle-aged veterans (average [SD] age 52 [14] years) reported prazosin did not significantly alleviate PTSD-related nightmares.¹³ However, we observed prazosin therapy significantly reduced nightmares and sleep disturbances, and significantly improved PTSD severity in our older veteran population.

To our knowledge, the current study is the largest retrospective study that evaluates prazosin therapy for the treatment of PTSD-related nightmares in older veterans. The findings of this study are similar to a previous study in older veterans as well as studies of prazosin in younger and middle-aged adult veterans, with the average age ranging from 30 to 56 years.^6-12 Like the previously reported studies, prazosin also was well tolerated in our sample of veterans with multiple comorbidities and concomitant medications. Changes in BP were not clinically significant.

Studies have demonstrated increased noradrenergic activity as a component of the normal aging process.^16,17 This may require utilizing caution during prazosin dose titration and frequent patient assessment, due to the concern for risk of hypotension in older patients and in particular those who may require increased doses to achieve efficacy. In our study, favorable outcomes were achieved at an average (SD) total daily dose of 5.1 (5.3) mg (median, 2.5 mg; range 0-17 mg). A previous report showed efficacy of prazosin around an average (SD) maximum dose of 2.3 (0.7) mg, which is lower than the doses reported in the current study.¹² In addition, 13 veterans (40.6%) from our sample reached doses of ≥ 5 mg per day, and 8 veterans (25.0%) reached doses of ≥ 10 mg per day.

The doses reached in this study were reflective of a management approach using assessment of patient-reported symptoms at weekly to biweekly follow-up visits. The individualized management approach applied in the PTC by MH CPSs aids in uncovering the most efficacious and tolerated dose of prazosin for each veteran. Evaluation of symptom change during treatment in PTC was facilitated use of objective rating scales, which helped measure nightmare frequency and intensity, sleep satisfaction, and global PTSD severity. Given the variability in dosing of prazosin reported in the literature, further studies may be warranted to provide more definitive clinical guidance as far as dosing prazosin in older patients.

The study by Peskind and colleaguesrationalized that lower doses of prazosin may be used in older patients given pharmacokinetic effects of aging, age-associated changes in PTSD pathophysiology, and effects and interactions of concomitant medications.¹² However, our study found that prazosin could be well tolerated at higher doses. The rate of discontinuation due to intolerable AEs was low. AEs reported were consistent with the established AE profile of prazosin, with dizziness, orthostasis, and headache most commonly reported. Similar to the Peskind and colleagues study, BP had a tendency to decrease in this current study; however, the change was not clinically significant.¹² That study also reported transient dizziness with prazosin titration, which was shown to be tolerable in the majority of our veterans reporting dizziness.¹² Other common AEs with prazosin, such as rash, priapism, sedation, syncope, other cardiac AEs, and sleep disturbance were not reported in our study population.

MH CPS-managed PTCs are one venue that may allow veterans to achieve favorable outcomes through frequent follow-up. As prazosin dosing is specific to each individual patient, frequent follow-up visits are helpful in determining optimal doses that maximize efficacy while minimizing intolerable AEs. The majority of veterans treated in our PTC continued use of prazosin 6 months postdischarge, while 3 veterans required a postdischarge dose change.

The 2017 VA/DoD PTSD guidelines recommend individual, trauma-focused psychotherapy over pharmacologic therapy for the primary treatment of PTSD.¹⁴ About half of the veterans in the current study participated in either group or individual psychotherapy during enrollment in the PTC. A systematic review of psychotherapy in older veterans reported mixed results, with 4 studies indicating positive effects of therapy, while the other 3 studies reported no benefit or mixed effects for PTSD symptoms. The review concluded that fewer older adults experience complete remission of symptoms with psychotherapy alone.¹⁸ A previous study of older veterans described improvement in PTSD-related symptoms with prazosin without concurrent psychotherapy.¹²

 

Limitations and Strengths

While this study is the largest study to evaluate outcomes of prazosin in older patients with PTSD, there are several important limitations. The study population was small and all were male. The results of this study may not be applicable to women. Another limitation was several missing values in our data set, as some secondary outcomes were not collected via telephone follow-up visits. This could potentially contribute a measurement bias in the reported secondary outcomes results, specifically for the PCL-5 and ISI. Additionally, some veterans in this study may have reported symptomatic improvement based on the additional supportive intervention that clinical pharmacists were able to offer, as well as concomitant participation in psychotherapy. This may be reflected in the study results. This study did not have a true placebo group, as we may find a reduction in symptoms with placebo.

Strengths of this study include multiple data points for assessment of prazosin tolerability and a pre- and poststudy design, which allowed for the veterans to serve as their own control. Another strength of this study is that data were complete for primary outcome measures, including the CAPS Recurrent and Distressing Dreams Item, where prazosin showed significant benefit in reduction of PTSD-related nightmares. While the results of this study are reassuring, further randomized, double-blind, placebo-controlled trials are likely needed in order to establish efficacy and tolerability of prazosin in older veterans for PTSD related nightmares.

Conclusion

These results demonstrate prazosin therapy in older veterans can significantly improve PTSD-related nightmares and PTSD severity. Prazosin was well tolerated in this population at doses higher than previously reported in other studies. This study shows that prazosin therapy can be effectively managed and tolerated in older veterans with complex medical and psychiatric comorbidities to provide favorable patient outcomes.

Acknowledgments

This material is the result of work supported with resources and the use of facilities at the Iowa City VA Health Care System and by the Health Services Research and Development Service, US Department of Veterans Affairs.

Sporadic porphyria cutanea tarda (PCT) is the most common cause of porphyria worldwide.^1,2 Unlike other forms of porphyria, PCT usually is an acquired disease precipitated by extrinsic risk factors that commonly include excessive alcohol consumption, smoking, and chronic hepatitis C virus (HCV) infection. Additional risk factors include myeloproliferative disorders, exposure to polyhalogenated compounds, estrogen therapy, diseases of iron overload like hereditary hemochromatosis (HH), and potentially, HIV infection.^1-3

In this case report, we present a patient with an iron overload (due in part to an HFE gene mutation) and concomitant PCT, HCV infection, and coronary artery disease (CAD). We will discuss the relationship that his iron overload may play in each of these disease states.

Case Presentation

Mr. M is a 59-year-old white male of Irish background with a medical history that includes coronary artery disease. He is status post ST-elevation myocardial infarction and percutaneous coronary intervention with placement of 2 drug-eluting stents. Additional medical issues include PCT and HCV infection with cirrhosis. He is an active smoker.

The patient has a long history of developing blisters with minor trauma, such as rubbing against his mattress/bed sheets or bumping into doors. These blisters primarily occur on his upper extremities, but also can occur on his face after shaving. Mr. M was diagnosed with HCV infection in 1979 while on active military duty. At that time, he had an acute HCV infection and jaundice that required a prolonged hospitalization. He reported no IV drug use and that many others on his military base had similar manifestations. He drinks 1 to 2 beers daily, but reports no binge drinking.

His laboratory studies were notable for ferritin, 2,069 ng/mL; serum iron, 317 mcg/dL; total iron binding capacity, 320 mcg/dL; transferrin, 239 mg/dl; liver function test alanine aminotransferase, 151 U/L; aspartate aminotransferase, 159 U/L; total bilirubin, 1.73 mg/dL; albumin, 3.6 g/dL; alkaline phosphatase, 119 U/L; INR, 1.1; and transferrin saturation, 99%. Mr. M’s HCV viral load was 28,700 IU/L with genotype 1b. Hemochromatosis genetic studies were notable for a heterozygous C282Y gene mutation and negative for H63D and S65C mutations. He repeatedly declined completing a 24-hour urine study of porphyrins. Ultrasonography was consistent with cirrhosis and splenomegaly. The patient was treatment naïve for HCV. He declined multiple offers for treatment of his HCV, citing financial considerations.

Porphyria Cutanea Tarda

The pathogenesis of PCT is related to the intrahepatic deficiency of uroporphyrinogen decarboxylase (UROD), an enzyme in the heme biosynthetic pathway (Figure 1). Decreased activity of UROD leads to accumulation of uroporphyrinogen and its derivatives, which most likely are oxidized in presence of cytochrome P450 1A2. Up to 80% of PCT cases are sporadic, in which the deficiency of UROD is acquired by exogenous risk factors as mentioned above. However, the remaining 20% of PCT cases are due to an autosomal dominant mutation of UROD that causes the partial deficiency (up to 50%) of UROD. In these cases, additional risk factors are needed to decrease UROD activity to < 75% for symptoms to occur.

 

Clinical Manifestation

Patients with PCT typically develop blisters, skin fragility, and peeling with sun exposure or minor trauma. They also may experience delayed wound healing in sun-exposed skin.³ The photosensitivity of PCT is believed to be related to the saturation of highly carboxylated uroporphyrins in the liver, which are then released into the circulation. Sun exposure then activates these products facilitating an immune reaction and subsequent skin damage.² In chronic cases, fibrotic reactions and scaring occur which can be mistaken for scleroderma. Other skin manifestations include hyperpigmentation, hypertrichosis, alopecia due to scaring and purplish heliotrope suffusion of periorbital areas.

Patients can develop cirrhosis due to accumulation of porphyria in the hepatocytes and subsequent parenchymal damage. Hepatocellular carcinoma surveillance is recommended for patients with PCT, although its incidence is rare in those patients.

Diagnosis and Treatment

PCT is mainly a clinical diagnosis. Physicians should consider PCT in patients with photosensitivity and blisters after minor trauma (Figure 2). The urine of a patient with PCT is often pink or red when exposed to air or light due to its high concentration of porphyrin products. Mild elevation of liver enzymes and fatty liver on ultrasound are also noted. Evidence of iron overload is seen in most cases. Screening for risk factors like HCV, HIV, hepatitis B virus, and HH is recommended. Confirmation of PCT typically requires measurement of the porphyria level in a 24-hour urine collection.

Avoiding sun exposure is fundamental in decreasing the development of skin lesions and scaring. Additionally, patients should be advised about the adverse effects of alcohol, smoking, and estrogen therapy on PCT. Treatment of PCT is frequently focused on iron overload and subsequent increased porphyrin oxidation.^1,2 Iron can increase reactive oxygen species (ROS), which, in turn, increases the rate of oxidation of uroporphyrinogens. Excess iron also decreases the activity of UROD and increases δ-aminolevulinic acid (ALA) production (the precursor of uroporphyrinogen). Phlebotomy to treat iron overload should be done to a target ferritin level of 20 ng/mL. Clinical manifestations, including skin lesions, typically will normalize before the laboratory findings. Therapeutic remission is expected after 6 to 7 phlebotomy attempts, while clinical improvement can occur after 2 to 3 phlebotomies.

In addition to phlebotomy, 4-aminoquinoline medications (chloroquine and hydroxychloroquine) can be used effectively to treat PCT. Hydroxychloroquine is generally preferred due to its better safety profile. Although the exact mechanism of action of 4-aminoquinolines is not clear, it has been suggested that they bind to porphyrins and form water-soluble products, which are then excreted in the urine. Again, clinical remission occurs much sooner than chemical remission, (3 months vs 12 months). A 4-aminoquinoline should not be used in patients with severe liver disease, renal insufficiency, pregnancy, or G6PD deficiency. When used, they should be used in lower than typical doses due to the rapid removal of accumulated porphyrin from the hepatocytes potentially causing necrosis and acute hepatitis.

Iron chelation also is effective, but it is slower in achieving remission and more expensive than phlebotomy. Treatment of PCT should be individualized. For example, 4-aminoquinolines are contraindicated for patients with end-stage renal disease (ESRD), while phlebotomy could present a problem for patients with preexisting anemia. In this instance, removing 50 cc of blood every 2 weeks may be safe and effective. Furthermore, 4-aminoquinolines in patients with severe iron overload and phlebotomy have been used together. Plasmapheresis is still another option in patients with ESRD.

The use of direct antiviral agents (DAA) in the treatment of HCV has shown promising results in maintaining undetectable viral loads and concurrent remission of PCT. Several studies have shown that treatment of HCV with a DAA obviates the need for treatment PCT.^3-5 Treatment of HCV with interferon (IFN) and ribavirin have shown mixed results in controlling PCT, possibly due to their ineffectiveness in maintaining a suppressed viral load. Some studies even showed worsening of PCT with IFN/ribavirin.⁶

 

Hemochromatosis

Human cells need iron for aerobic respiration. The intestinal mucosa controls iron uptake and its transfer to the blood stream. Aside from variations in intestinal absorption with fecal excretion, humans do not have another pathway to excrete excess iron. HH is the most common genetic disorder in whites.⁷ It is an autosomal recessive disorder that increases the intestinal absorption of iron. The most common mutation in the hemochromatosis (HFE) gene results in a substitution of tyrosine for cysteine at amino acid number 282 and is referred to as the C282Y mutation. A second mutation changes histidine at position 63 to aspartic acid and is referred to as a H63D mutation. H63D is present in a minority of the patients with phenotypically expressed HH and its clinical impact is unknown.

Homozygosity of the C282Y mutation is the most common genotype associated with clinical hemochromatosis. While carriers of the C282Y gene heterozygote mutation typically do not develop enough iron overload to cause clinical hemochromatosis, they can if other risk factors, such as PCT, excess alcohol use, liver disease, or HCV, are present.⁸ Additionally, an associated genetic defect, like a compound heterozygotes C282Y/H63D mutation, a private HFE mutation in trans, or other iron-related genes, can cause manifestations of iron overload. Lastly, about 20% of patients that are heterozygous for both mutations can express the HH phenotype.⁸

Clinical Manifestation

Patients with HH absorb only a few extra milligrams of iron daily. The clinical manifestation begins to occur when the total body iron store reaches 15-40 g (normal, 4 g). While the genetic mutation is present from birth, iron stores start to rise slowly to around 10 g > age 15 years, at which point serum iron levels are elevated. After age 20 years, the speed with which the iron is stored increases, and by 30 years, liver damage and tissue injury will occur. Cirrhosis is possible by 40 years.⁷ Age, sex, dietary iron intake, blood loss (menstruation), pregnancy, and other unknown factors greatly influence the disease progression. Homozygote C282Y mutation is as common in women as it is in men, but women are less likely to express the HH phenotype, presumably due, in part, to menstruation. When diagnosed early, most of the clinical manifestations of HH are preventable. Additional manifestations of HH include hyperpigmentation, cardiomyopathy, diabetes mellitus, hypogonadism, hypothyroidism, and arthropathy due to pseudogout.

Iron overload due to HH should be distinguished from other causes of iron overload including exogenous iron overload, anemia (thalassemia, sideroblastic), and chronic liver diseases like PCT, viral hepatitis, nonalcoholic steatohepatitis, and alcoholic liver disease.

Diagnosis

HH should be suspected in patients with a high serum transferrin saturation and elevated serum ferritin concentrations. Typically, transferrin saturation is > 50% and ferritin levels are > 300 ng/mL in men and > 200 ng/mL in women. In early stages of the disease, transferrin saturation can be normal. Additionally, in patients with chronic inflammation, ferritin may be high due to acute-phase reactants and the iron panel should be interpreted with caution. When the secondary causes of abnormalities in a patient’s iron studies are excluded, genetic testing for HFE gene is recommended.

 

The majority of patients (60-93%) with clinically evident hemochromatosis are homozygous for C282Y mutation. In a heterozygous C282Y mutation with a high transferrin saturation and HH phenotype, additional genetic testing for a heterozygous compound mutation C282Y/H63D is recommended.⁸ Additional studies could include evaluation for a private HFE mutation in trans or other iron-related genes. Liver biopsy is the gold standard for assessing the degree of hepatic fibrosis. Determining the degree of fibrosis by some means is needed due to the increased risk of hepatocellular carcinoma (HCC) in HH patients with advanced fibrosis and cirrhosis.⁹

Treatment

Iron depletion with phlebotomy is the cornerstone of treatment in HH. Phlebotomy initially is done weekly with goal of achieving a transferrin saturation < 50%, a serum ferritin level < 50 ng/mL, and a hemoglobin of 12 to 13 ng/mL. When these goals are achieved, patients typically need 4 to 8 phlebotomies per year to maintain a transferrin saturation < 50% (Figure 3).

Hemochromatosis and PCT

Many studies have investigated the relevance of C282Y and/or H63D mutations in patients with PCT.^9,10 It appears that ≥ 1 mutation of the HFE gene in PCT may be an important susceptibility factor in the development of clinical PCT. Various studies have shown an incidence of C282Y mutations of 44 to 47% in patients with PCT, compared with 9 to 12% in control populations.^9,10 The incidence of the H63D mutation in PCT has been more variable, with some studies showing no difference between patients with PCT and a control group, while other studies showed 31% incidence of H63D mutation in patients with PCT.^9,10 A higher incidence of C282Y and H63D mutations in PCT may be a sign that the HFE mutation could be an important factor in developing PCT.

Hemochromatosis and Hepatitis C

Transferrin saturation is frequently elevated in patients with HCV. It is yet unclear whether the pathology of liver disease in patients with HCV is influenced by iron overload or limited to the direct cell damage from replication of the virus and subsequent inflammation. It is believed that the pathology of iron overload in the patients with HCV is different from HH. Like other secondary causes of iron overload, the excess iron is stored in the Kupffer cells of patients with HCV. In HH, excess iron is stored in hepatocytes.

The prevalence of the HFE mutation is the same in the patients with chronic HCV and healthy individuals.^10,11 However, HFE mutations are more prevalent in 30 to 60% of the patients with chronic HCV who have elevated transferrin saturations. Alone, C282Y heterozygosity, H63D heterozygosity, or C282Y/H63D compound heterozygosity could not lead to clinically significant iron overload in otherwise healthy individuals; however, these could be a significant cause of iron overload in patients with chronic HCV. Theoretically, the combination of iron overload and HFE gene mutations could increase the rate of advanced fibrosis/cirrhosis in chronic HCV. An increase serum ferritin level of 200 ng/dL in women and 250 ng/dL in men has been observed in 32% of patients with chronic HCV. In this subset of patients, phlebotomy reduced the progression of their liver disease and reduction in their liver enzymes.

 

Iron Overload and Cardiovascular Risk

In 1987, a Framingham cohort of > 2,800 patients showed a higher incident of CAD in postmenopausal women when compared with premenopausal women.¹² In the 1980s, Sullivan hypothesized that the reason for higher incidence of CAD in men when compared with premenopausal women was due to their higher body iron storage.^13-16 A study of 1,930 Finnish men reported that the men with ferritin level ≥ 200 ng/dL had a risk 2.2 times higher of acute myocardial infarction when compared to men with lower serum ferritin level.¹⁷

A prospective study published in 1997 by Klechl showed the role of iron stores in early atherogenesis via promotion of lipid oxidation.¹⁸ Other epidemiological studies have shown a decreased risk of myocardial infarction in blood donors, and while arguments have been made that the blood donors tend to be healthier individuals, 2 studies were published in 1997 matching healthy blood donors to healthy nonblood donors, and both showed a lower risk of CVD in the donors when compared with nondonors.^19,20 Furthermore, in an animal model of atherosclerosis, an iron depleted diet showed a reduction of atherosclerosis progression.²¹ Multiple studies have shown that the heterozygosity for HFE is significantly linked to the risk of cardiovascular events, including the fact that heterozygosity for C282Y has been shown to be a risk factor for myocardial infarction in men and cerebrovascular death in women.^22-25

Conclusion

Multiple studies have shown an association between the elevated iron levels associated with the HFE genotype and the disease states of our patient. These include an increased risk of CAD, the increased risk of cirrhosis in HCV and the development of PCT. Indeed, in this case, our patient likely acquired PCT from the combined risks of HCV and his heterozygous HFE genetic mutation.

With regard to Mr. M’s treatment, the use of an antiviral agent in the treatment of his HCV is fundamental, along with avoidance of alcohol and smoking. If he were to accept HCV treatment, we would anticipate resolution of the PCT, but the ongoing progression of his liver and cardiovascular conditions, due perhaps in part, to relative iron overload from his heterozygous HFE mutation. In this situation, we expect that an ongoing course of therapeutic phlebotomy could help to delay the progression of his chronic liver and cardiovascular diseases.

Sporadic porphyria cutanea tarda (PCT) is the most common cause of porphyria worldwide.^1,2 Unlike other forms of porphyria, PCT usually is an acquired disease precipitated by extrinsic risk factors that commonly include excessive alcohol consumption, smoking, and chronic hepatitis C virus (HCV) infection. Additional risk factors include myeloproliferative disorders, exposure to polyhalogenated compounds, estrogen therapy, diseases of iron overload like hereditary hemochromatosis (HH), and potentially, HIV infection.^1-3

In this case report, we present a patient with an iron overload (due in part to an HFE gene mutation) and concomitant PCT, HCV infection, and coronary artery disease (CAD). We will discuss the relationship that his iron overload may play in each of these disease states.

Case Presentation

Mr. M is a 59-year-old white male of Irish background with a medical history that includes coronary artery disease. He is status post ST-elevation myocardial infarction and percutaneous coronary intervention with placement of 2 drug-eluting stents. Additional medical issues include PCT and HCV infection with cirrhosis. He is an active smoker.

The patient has a long history of developing blisters with minor trauma, such as rubbing against his mattress/bed sheets or bumping into doors. These blisters primarily occur on his upper extremities, but also can occur on his face after shaving. Mr. M was diagnosed with HCV infection in 1979 while on active military duty. At that time, he had an acute HCV infection and jaundice that required a prolonged hospitalization. He reported no IV drug use and that many others on his military base had similar manifestations. He drinks 1 to 2 beers daily, but reports no binge drinking.

His laboratory studies were notable for ferritin, 2,069 ng/mL; serum iron, 317 mcg/dL; total iron binding capacity, 320 mcg/dL; transferrin, 239 mg/dl; liver function test alanine aminotransferase, 151 U/L; aspartate aminotransferase, 159 U/L; total bilirubin, 1.73 mg/dL; albumin, 3.6 g/dL; alkaline phosphatase, 119 U/L; INR, 1.1; and transferrin saturation, 99%. Mr. M’s HCV viral load was 28,700 IU/L with genotype 1b. Hemochromatosis genetic studies were notable for a heterozygous C282Y gene mutation and negative for H63D and S65C mutations. He repeatedly declined completing a 24-hour urine study of porphyrins. Ultrasonography was consistent with cirrhosis and splenomegaly. The patient was treatment naïve for HCV. He declined multiple offers for treatment of his HCV, citing financial considerations.

Porphyria Cutanea Tarda

The pathogenesis of PCT is related to the intrahepatic deficiency of uroporphyrinogen decarboxylase (UROD), an enzyme in the heme biosynthetic pathway (Figure 1). Decreased activity of UROD leads to accumulation of uroporphyrinogen and its derivatives, which most likely are oxidized in presence of cytochrome P450 1A2. Up to 80% of PCT cases are sporadic, in which the deficiency of UROD is acquired by exogenous risk factors as mentioned above. However, the remaining 20% of PCT cases are due to an autosomal dominant mutation of UROD that causes the partial deficiency (up to 50%) of UROD. In these cases, additional risk factors are needed to decrease UROD activity to < 75% for symptoms to occur.

 

Clinical Manifestation

Patients with PCT typically develop blisters, skin fragility, and peeling with sun exposure or minor trauma. They also may experience delayed wound healing in sun-exposed skin.³ The photosensitivity of PCT is believed to be related to the saturation of highly carboxylated uroporphyrins in the liver, which are then released into the circulation. Sun exposure then activates these products facilitating an immune reaction and subsequent skin damage.² In chronic cases, fibrotic reactions and scaring occur which can be mistaken for scleroderma. Other skin manifestations include hyperpigmentation, hypertrichosis, alopecia due to scaring and purplish heliotrope suffusion of periorbital areas.

Patients can develop cirrhosis due to accumulation of porphyria in the hepatocytes and subsequent parenchymal damage. Hepatocellular carcinoma surveillance is recommended for patients with PCT, although its incidence is rare in those patients.

Diagnosis and Treatment

PCT is mainly a clinical diagnosis. Physicians should consider PCT in patients with photosensitivity and blisters after minor trauma (Figure 2). The urine of a patient with PCT is often pink or red when exposed to air or light due to its high concentration of porphyrin products. Mild elevation of liver enzymes and fatty liver on ultrasound are also noted. Evidence of iron overload is seen in most cases. Screening for risk factors like HCV, HIV, hepatitis B virus, and HH is recommended. Confirmation of PCT typically requires measurement of the porphyria level in a 24-hour urine collection.

Avoiding sun exposure is fundamental in decreasing the development of skin lesions and scaring. Additionally, patients should be advised about the adverse effects of alcohol, smoking, and estrogen therapy on PCT. Treatment of PCT is frequently focused on iron overload and subsequent increased porphyrin oxidation.^1,2 Iron can increase reactive oxygen species (ROS), which, in turn, increases the rate of oxidation of uroporphyrinogens. Excess iron also decreases the activity of UROD and increases δ-aminolevulinic acid (ALA) production (the precursor of uroporphyrinogen). Phlebotomy to treat iron overload should be done to a target ferritin level of 20 ng/mL. Clinical manifestations, including skin lesions, typically will normalize before the laboratory findings. Therapeutic remission is expected after 6 to 7 phlebotomy attempts, while clinical improvement can occur after 2 to 3 phlebotomies.

In addition to phlebotomy, 4-aminoquinoline medications (chloroquine and hydroxychloroquine) can be used effectively to treat PCT. Hydroxychloroquine is generally preferred due to its better safety profile. Although the exact mechanism of action of 4-aminoquinolines is not clear, it has been suggested that they bind to porphyrins and form water-soluble products, which are then excreted in the urine. Again, clinical remission occurs much sooner than chemical remission, (3 months vs 12 months). A 4-aminoquinoline should not be used in patients with severe liver disease, renal insufficiency, pregnancy, or G6PD deficiency. When used, they should be used in lower than typical doses due to the rapid removal of accumulated porphyrin from the hepatocytes potentially causing necrosis and acute hepatitis.

Iron chelation also is effective, but it is slower in achieving remission and more expensive than phlebotomy. Treatment of PCT should be individualized. For example, 4-aminoquinolines are contraindicated for patients with end-stage renal disease (ESRD), while phlebotomy could present a problem for patients with preexisting anemia. In this instance, removing 50 cc of blood every 2 weeks may be safe and effective. Furthermore, 4-aminoquinolines in patients with severe iron overload and phlebotomy have been used together. Plasmapheresis is still another option in patients with ESRD.

The use of direct antiviral agents (DAA) in the treatment of HCV has shown promising results in maintaining undetectable viral loads and concurrent remission of PCT. Several studies have shown that treatment of HCV with a DAA obviates the need for treatment PCT.^3-5 Treatment of HCV with interferon (IFN) and ribavirin have shown mixed results in controlling PCT, possibly due to their ineffectiveness in maintaining a suppressed viral load. Some studies even showed worsening of PCT with IFN/ribavirin.⁶

 

Hemochromatosis

Human cells need iron for aerobic respiration. The intestinal mucosa controls iron uptake and its transfer to the blood stream. Aside from variations in intestinal absorption with fecal excretion, humans do not have another pathway to excrete excess iron. HH is the most common genetic disorder in whites.⁷ It is an autosomal recessive disorder that increases the intestinal absorption of iron. The most common mutation in the hemochromatosis (HFE) gene results in a substitution of tyrosine for cysteine at amino acid number 282 and is referred to as the C282Y mutation. A second mutation changes histidine at position 63 to aspartic acid and is referred to as a H63D mutation. H63D is present in a minority of the patients with phenotypically expressed HH and its clinical impact is unknown.

Homozygosity of the C282Y mutation is the most common genotype associated with clinical hemochromatosis. While carriers of the C282Y gene heterozygote mutation typically do not develop enough iron overload to cause clinical hemochromatosis, they can if other risk factors, such as PCT, excess alcohol use, liver disease, or HCV, are present.⁸ Additionally, an associated genetic defect, like a compound heterozygotes C282Y/H63D mutation, a private HFE mutation in trans, or other iron-related genes, can cause manifestations of iron overload. Lastly, about 20% of patients that are heterozygous for both mutations can express the HH phenotype.⁸

Clinical Manifestation

Patients with HH absorb only a few extra milligrams of iron daily. The clinical manifestation begins to occur when the total body iron store reaches 15-40 g (normal, 4 g). While the genetic mutation is present from birth, iron stores start to rise slowly to around 10 g > age 15 years, at which point serum iron levels are elevated. After age 20 years, the speed with which the iron is stored increases, and by 30 years, liver damage and tissue injury will occur. Cirrhosis is possible by 40 years.⁷ Age, sex, dietary iron intake, blood loss (menstruation), pregnancy, and other unknown factors greatly influence the disease progression. Homozygote C282Y mutation is as common in women as it is in men, but women are less likely to express the HH phenotype, presumably due, in part, to menstruation. When diagnosed early, most of the clinical manifestations of HH are preventable. Additional manifestations of HH include hyperpigmentation, cardiomyopathy, diabetes mellitus, hypogonadism, hypothyroidism, and arthropathy due to pseudogout.

Iron overload due to HH should be distinguished from other causes of iron overload including exogenous iron overload, anemia (thalassemia, sideroblastic), and chronic liver diseases like PCT, viral hepatitis, nonalcoholic steatohepatitis, and alcoholic liver disease.

Diagnosis

HH should be suspected in patients with a high serum transferrin saturation and elevated serum ferritin concentrations. Typically, transferrin saturation is > 50% and ferritin levels are > 300 ng/mL in men and > 200 ng/mL in women. In early stages of the disease, transferrin saturation can be normal. Additionally, in patients with chronic inflammation, ferritin may be high due to acute-phase reactants and the iron panel should be interpreted with caution. When the secondary causes of abnormalities in a patient’s iron studies are excluded, genetic testing for HFE gene is recommended.

 

The majority of patients (60-93%) with clinically evident hemochromatosis are homozygous for C282Y mutation. In a heterozygous C282Y mutation with a high transferrin saturation and HH phenotype, additional genetic testing for a heterozygous compound mutation C282Y/H63D is recommended.⁸ Additional studies could include evaluation for a private HFE mutation in trans or other iron-related genes. Liver biopsy is the gold standard for assessing the degree of hepatic fibrosis. Determining the degree of fibrosis by some means is needed due to the increased risk of hepatocellular carcinoma (HCC) in HH patients with advanced fibrosis and cirrhosis.⁹

Treatment

Iron depletion with phlebotomy is the cornerstone of treatment in HH. Phlebotomy initially is done weekly with goal of achieving a transferrin saturation < 50%, a serum ferritin level < 50 ng/mL, and a hemoglobin of 12 to 13 ng/mL. When these goals are achieved, patients typically need 4 to 8 phlebotomies per year to maintain a transferrin saturation < 50% (Figure 3).

Hemochromatosis and PCT

Many studies have investigated the relevance of C282Y and/or H63D mutations in patients with PCT.^9,10 It appears that ≥ 1 mutation of the HFE gene in PCT may be an important susceptibility factor in the development of clinical PCT. Various studies have shown an incidence of C282Y mutations of 44 to 47% in patients with PCT, compared with 9 to 12% in control populations.^9,10 The incidence of the H63D mutation in PCT has been more variable, with some studies showing no difference between patients with PCT and a control group, while other studies showed 31% incidence of H63D mutation in patients with PCT.^9,10 A higher incidence of C282Y and H63D mutations in PCT may be a sign that the HFE mutation could be an important factor in developing PCT.

Hemochromatosis and Hepatitis C

Transferrin saturation is frequently elevated in patients with HCV. It is yet unclear whether the pathology of liver disease in patients with HCV is influenced by iron overload or limited to the direct cell damage from replication of the virus and subsequent inflammation. It is believed that the pathology of iron overload in the patients with HCV is different from HH. Like other secondary causes of iron overload, the excess iron is stored in the Kupffer cells of patients with HCV. In HH, excess iron is stored in hepatocytes.

The prevalence of the HFE mutation is the same in the patients with chronic HCV and healthy individuals.^10,11 However, HFE mutations are more prevalent in 30 to 60% of the patients with chronic HCV who have elevated transferrin saturations. Alone, C282Y heterozygosity, H63D heterozygosity, or C282Y/H63D compound heterozygosity could not lead to clinically significant iron overload in otherwise healthy individuals; however, these could be a significant cause of iron overload in patients with chronic HCV. Theoretically, the combination of iron overload and HFE gene mutations could increase the rate of advanced fibrosis/cirrhosis in chronic HCV. An increase serum ferritin level of 200 ng/dL in women and 250 ng/dL in men has been observed in 32% of patients with chronic HCV. In this subset of patients, phlebotomy reduced the progression of their liver disease and reduction in their liver enzymes.

 

Iron Overload and Cardiovascular Risk

In 1987, a Framingham cohort of > 2,800 patients showed a higher incident of CAD in postmenopausal women when compared with premenopausal women.¹² In the 1980s, Sullivan hypothesized that the reason for higher incidence of CAD in men when compared with premenopausal women was due to their higher body iron storage.^13-16 A study of 1,930 Finnish men reported that the men with ferritin level ≥ 200 ng/dL had a risk 2.2 times higher of acute myocardial infarction when compared to men with lower serum ferritin level.¹⁷

A prospective study published in 1997 by Klechl showed the role of iron stores in early atherogenesis via promotion of lipid oxidation.¹⁸ Other epidemiological studies have shown a decreased risk of myocardial infarction in blood donors, and while arguments have been made that the blood donors tend to be healthier individuals, 2 studies were published in 1997 matching healthy blood donors to healthy nonblood donors, and both showed a lower risk of CVD in the donors when compared with nondonors.^19,20 Furthermore, in an animal model of atherosclerosis, an iron depleted diet showed a reduction of atherosclerosis progression.²¹ Multiple studies have shown that the heterozygosity for HFE is significantly linked to the risk of cardiovascular events, including the fact that heterozygosity for C282Y has been shown to be a risk factor for myocardial infarction in men and cerebrovascular death in women.^22-25

Conclusion

Multiple studies have shown an association between the elevated iron levels associated with the HFE genotype and the disease states of our patient. These include an increased risk of CAD, the increased risk of cirrhosis in HCV and the development of PCT. Indeed, in this case, our patient likely acquired PCT from the combined risks of HCV and his heterozygous HFE genetic mutation.

With regard to Mr. M’s treatment, the use of an antiviral agent in the treatment of his HCV is fundamental, along with avoidance of alcohol and smoking. If he were to accept HCV treatment, we would anticipate resolution of the PCT, but the ongoing progression of his liver and cardiovascular conditions, due perhaps in part, to relative iron overload from his heterozygous HFE mutation. In this situation, we expect that an ongoing course of therapeutic phlebotomy could help to delay the progression of his chronic liver and cardiovascular diseases.

Sporadic porphyria cutanea tarda (PCT) is the most common cause of porphyria worldwide.^1,2 Unlike other forms of porphyria, PCT usually is an acquired disease precipitated by extrinsic risk factors that commonly include excessive alcohol consumption, smoking, and chronic hepatitis C virus (HCV) infection. Additional risk factors include myeloproliferative disorders, exposure to polyhalogenated compounds, estrogen therapy, diseases of iron overload like hereditary hemochromatosis (HH), and potentially, HIV infection.^1-3

In this case report, we present a patient with an iron overload (due in part to an HFE gene mutation) and concomitant PCT, HCV infection, and coronary artery disease (CAD). We will discuss the relationship that his iron overload may play in each of these disease states.

Case Presentation

Mr. M is a 59-year-old white male of Irish background with a medical history that includes coronary artery disease. He is status post ST-elevation myocardial infarction and percutaneous coronary intervention with placement of 2 drug-eluting stents. Additional medical issues include PCT and HCV infection with cirrhosis. He is an active smoker.

The patient has a long history of developing blisters with minor trauma, such as rubbing against his mattress/bed sheets or bumping into doors. These blisters primarily occur on his upper extremities, but also can occur on his face after shaving. Mr. M was diagnosed with HCV infection in 1979 while on active military duty. At that time, he had an acute HCV infection and jaundice that required a prolonged hospitalization. He reported no IV drug use and that many others on his military base had similar manifestations. He drinks 1 to 2 beers daily, but reports no binge drinking.

His laboratory studies were notable for ferritin, 2,069 ng/mL; serum iron, 317 mcg/dL; total iron binding capacity, 320 mcg/dL; transferrin, 239 mg/dl; liver function test alanine aminotransferase, 151 U/L; aspartate aminotransferase, 159 U/L; total bilirubin, 1.73 mg/dL; albumin, 3.6 g/dL; alkaline phosphatase, 119 U/L; INR, 1.1; and transferrin saturation, 99%. Mr. M’s HCV viral load was 28,700 IU/L with genotype 1b. Hemochromatosis genetic studies were notable for a heterozygous C282Y gene mutation and negative for H63D and S65C mutations. He repeatedly declined completing a 24-hour urine study of porphyrins. Ultrasonography was consistent with cirrhosis and splenomegaly. The patient was treatment naïve for HCV. He declined multiple offers for treatment of his HCV, citing financial considerations.

Porphyria Cutanea Tarda

The pathogenesis of PCT is related to the intrahepatic deficiency of uroporphyrinogen decarboxylase (UROD), an enzyme in the heme biosynthetic pathway (Figure 1). Decreased activity of UROD leads to accumulation of uroporphyrinogen and its derivatives, which most likely are oxidized in presence of cytochrome P450 1A2. Up to 80% of PCT cases are sporadic, in which the deficiency of UROD is acquired by exogenous risk factors as mentioned above. However, the remaining 20% of PCT cases are due to an autosomal dominant mutation of UROD that causes the partial deficiency (up to 50%) of UROD. In these cases, additional risk factors are needed to decrease UROD activity to < 75% for symptoms to occur.

 

Clinical Manifestation

Patients with PCT typically develop blisters, skin fragility, and peeling with sun exposure or minor trauma. They also may experience delayed wound healing in sun-exposed skin.³ The photosensitivity of PCT is believed to be related to the saturation of highly carboxylated uroporphyrins in the liver, which are then released into the circulation. Sun exposure then activates these products facilitating an immune reaction and subsequent skin damage.² In chronic cases, fibrotic reactions and scaring occur which can be mistaken for scleroderma. Other skin manifestations include hyperpigmentation, hypertrichosis, alopecia due to scaring and purplish heliotrope suffusion of periorbital areas.

Patients can develop cirrhosis due to accumulation of porphyria in the hepatocytes and subsequent parenchymal damage. Hepatocellular carcinoma surveillance is recommended for patients with PCT, although its incidence is rare in those patients.

Diagnosis and Treatment

PCT is mainly a clinical diagnosis. Physicians should consider PCT in patients with photosensitivity and blisters after minor trauma (Figure 2). The urine of a patient with PCT is often pink or red when exposed to air or light due to its high concentration of porphyrin products. Mild elevation of liver enzymes and fatty liver on ultrasound are also noted. Evidence of iron overload is seen in most cases. Screening for risk factors like HCV, HIV, hepatitis B virus, and HH is recommended. Confirmation of PCT typically requires measurement of the porphyria level in a 24-hour urine collection.

Avoiding sun exposure is fundamental in decreasing the development of skin lesions and scaring. Additionally, patients should be advised about the adverse effects of alcohol, smoking, and estrogen therapy on PCT. Treatment of PCT is frequently focused on iron overload and subsequent increased porphyrin oxidation.^1,2 Iron can increase reactive oxygen species (ROS), which, in turn, increases the rate of oxidation of uroporphyrinogens. Excess iron also decreases the activity of UROD and increases δ-aminolevulinic acid (ALA) production (the precursor of uroporphyrinogen). Phlebotomy to treat iron overload should be done to a target ferritin level of 20 ng/mL. Clinical manifestations, including skin lesions, typically will normalize before the laboratory findings. Therapeutic remission is expected after 6 to 7 phlebotomy attempts, while clinical improvement can occur after 2 to 3 phlebotomies.

In addition to phlebotomy, 4-aminoquinoline medications (chloroquine and hydroxychloroquine) can be used effectively to treat PCT. Hydroxychloroquine is generally preferred due to its better safety profile. Although the exact mechanism of action of 4-aminoquinolines is not clear, it has been suggested that they bind to porphyrins and form water-soluble products, which are then excreted in the urine. Again, clinical remission occurs much sooner than chemical remission, (3 months vs 12 months). A 4-aminoquinoline should not be used in patients with severe liver disease, renal insufficiency, pregnancy, or G6PD deficiency. When used, they should be used in lower than typical doses due to the rapid removal of accumulated porphyrin from the hepatocytes potentially causing necrosis and acute hepatitis.

Iron chelation also is effective, but it is slower in achieving remission and more expensive than phlebotomy. Treatment of PCT should be individualized. For example, 4-aminoquinolines are contraindicated for patients with end-stage renal disease (ESRD), while phlebotomy could present a problem for patients with preexisting anemia. In this instance, removing 50 cc of blood every 2 weeks may be safe and effective. Furthermore, 4-aminoquinolines in patients with severe iron overload and phlebotomy have been used together. Plasmapheresis is still another option in patients with ESRD.

The use of direct antiviral agents (DAA) in the treatment of HCV has shown promising results in maintaining undetectable viral loads and concurrent remission of PCT. Several studies have shown that treatment of HCV with a DAA obviates the need for treatment PCT.^3-5 Treatment of HCV with interferon (IFN) and ribavirin have shown mixed results in controlling PCT, possibly due to their ineffectiveness in maintaining a suppressed viral load. Some studies even showed worsening of PCT with IFN/ribavirin.⁶

 

Hemochromatosis

Human cells need iron for aerobic respiration. The intestinal mucosa controls iron uptake and its transfer to the blood stream. Aside from variations in intestinal absorption with fecal excretion, humans do not have another pathway to excrete excess iron. HH is the most common genetic disorder in whites.⁷ It is an autosomal recessive disorder that increases the intestinal absorption of iron. The most common mutation in the hemochromatosis (HFE) gene results in a substitution of tyrosine for cysteine at amino acid number 282 and is referred to as the C282Y mutation. A second mutation changes histidine at position 63 to aspartic acid and is referred to as a H63D mutation. H63D is present in a minority of the patients with phenotypically expressed HH and its clinical impact is unknown.

Homozygosity of the C282Y mutation is the most common genotype associated with clinical hemochromatosis. While carriers of the C282Y gene heterozygote mutation typically do not develop enough iron overload to cause clinical hemochromatosis, they can if other risk factors, such as PCT, excess alcohol use, liver disease, or HCV, are present.⁸ Additionally, an associated genetic defect, like a compound heterozygotes C282Y/H63D mutation, a private HFE mutation in trans, or other iron-related genes, can cause manifestations of iron overload. Lastly, about 20% of patients that are heterozygous for both mutations can express the HH phenotype.⁸

Clinical Manifestation

Patients with HH absorb only a few extra milligrams of iron daily. The clinical manifestation begins to occur when the total body iron store reaches 15-40 g (normal, 4 g). While the genetic mutation is present from birth, iron stores start to rise slowly to around 10 g > age 15 years, at which point serum iron levels are elevated. After age 20 years, the speed with which the iron is stored increases, and by 30 years, liver damage and tissue injury will occur. Cirrhosis is possible by 40 years.⁷ Age, sex, dietary iron intake, blood loss (menstruation), pregnancy, and other unknown factors greatly influence the disease progression. Homozygote C282Y mutation is as common in women as it is in men, but women are less likely to express the HH phenotype, presumably due, in part, to menstruation. When diagnosed early, most of the clinical manifestations of HH are preventable. Additional manifestations of HH include hyperpigmentation, cardiomyopathy, diabetes mellitus, hypogonadism, hypothyroidism, and arthropathy due to pseudogout.

Iron overload due to HH should be distinguished from other causes of iron overload including exogenous iron overload, anemia (thalassemia, sideroblastic), and chronic liver diseases like PCT, viral hepatitis, nonalcoholic steatohepatitis, and alcoholic liver disease.

Diagnosis

HH should be suspected in patients with a high serum transferrin saturation and elevated serum ferritin concentrations. Typically, transferrin saturation is > 50% and ferritin levels are > 300 ng/mL in men and > 200 ng/mL in women. In early stages of the disease, transferrin saturation can be normal. Additionally, in patients with chronic inflammation, ferritin may be high due to acute-phase reactants and the iron panel should be interpreted with caution. When the secondary causes of abnormalities in a patient’s iron studies are excluded, genetic testing for HFE gene is recommended.

 

The majority of patients (60-93%) with clinically evident hemochromatosis are homozygous for C282Y mutation. In a heterozygous C282Y mutation with a high transferrin saturation and HH phenotype, additional genetic testing for a heterozygous compound mutation C282Y/H63D is recommended.⁸ Additional studies could include evaluation for a private HFE mutation in trans or other iron-related genes. Liver biopsy is the gold standard for assessing the degree of hepatic fibrosis. Determining the degree of fibrosis by some means is needed due to the increased risk of hepatocellular carcinoma (HCC) in HH patients with advanced fibrosis and cirrhosis.⁹

Treatment

Iron depletion with phlebotomy is the cornerstone of treatment in HH. Phlebotomy initially is done weekly with goal of achieving a transferrin saturation < 50%, a serum ferritin level < 50 ng/mL, and a hemoglobin of 12 to 13 ng/mL. When these goals are achieved, patients typically need 4 to 8 phlebotomies per year to maintain a transferrin saturation < 50% (Figure 3).

Hemochromatosis and PCT

Many studies have investigated the relevance of C282Y and/or H63D mutations in patients with PCT.^9,10 It appears that ≥ 1 mutation of the HFE gene in PCT may be an important susceptibility factor in the development of clinical PCT. Various studies have shown an incidence of C282Y mutations of 44 to 47% in patients with PCT, compared with 9 to 12% in control populations.^9,10 The incidence of the H63D mutation in PCT has been more variable, with some studies showing no difference between patients with PCT and a control group, while other studies showed 31% incidence of H63D mutation in patients with PCT.^9,10 A higher incidence of C282Y and H63D mutations in PCT may be a sign that the HFE mutation could be an important factor in developing PCT.

Hemochromatosis and Hepatitis C

Transferrin saturation is frequently elevated in patients with HCV. It is yet unclear whether the pathology of liver disease in patients with HCV is influenced by iron overload or limited to the direct cell damage from replication of the virus and subsequent inflammation. It is believed that the pathology of iron overload in the patients with HCV is different from HH. Like other secondary causes of iron overload, the excess iron is stored in the Kupffer cells of patients with HCV. In HH, excess iron is stored in hepatocytes.

The prevalence of the HFE mutation is the same in the patients with chronic HCV and healthy individuals.^10,11 However, HFE mutations are more prevalent in 30 to 60% of the patients with chronic HCV who have elevated transferrin saturations. Alone, C282Y heterozygosity, H63D heterozygosity, or C282Y/H63D compound heterozygosity could not lead to clinically significant iron overload in otherwise healthy individuals; however, these could be a significant cause of iron overload in patients with chronic HCV. Theoretically, the combination of iron overload and HFE gene mutations could increase the rate of advanced fibrosis/cirrhosis in chronic HCV. An increase serum ferritin level of 200 ng/dL in women and 250 ng/dL in men has been observed in 32% of patients with chronic HCV. In this subset of patients, phlebotomy reduced the progression of their liver disease and reduction in their liver enzymes.

 

Iron Overload and Cardiovascular Risk

In 1987, a Framingham cohort of > 2,800 patients showed a higher incident of CAD in postmenopausal women when compared with premenopausal women.¹² In the 1980s, Sullivan hypothesized that the reason for higher incidence of CAD in men when compared with premenopausal women was due to their higher body iron storage.^13-16 A study of 1,930 Finnish men reported that the men with ferritin level ≥ 200 ng/dL had a risk 2.2 times higher of acute myocardial infarction when compared to men with lower serum ferritin level.¹⁷

A prospective study published in 1997 by Klechl showed the role of iron stores in early atherogenesis via promotion of lipid oxidation.¹⁸ Other epidemiological studies have shown a decreased risk of myocardial infarction in blood donors, and while arguments have been made that the blood donors tend to be healthier individuals, 2 studies were published in 1997 matching healthy blood donors to healthy nonblood donors, and both showed a lower risk of CVD in the donors when compared with nondonors.^19,20 Furthermore, in an animal model of atherosclerosis, an iron depleted diet showed a reduction of atherosclerosis progression.²¹ Multiple studies have shown that the heterozygosity for HFE is significantly linked to the risk of cardiovascular events, including the fact that heterozygosity for C282Y has been shown to be a risk factor for myocardial infarction in men and cerebrovascular death in women.^22-25

Conclusion

Multiple studies have shown an association between the elevated iron levels associated with the HFE genotype and the disease states of our patient. These include an increased risk of CAD, the increased risk of cirrhosis in HCV and the development of PCT. Indeed, in this case, our patient likely acquired PCT from the combined risks of HCV and his heterozygous HFE genetic mutation.

With regard to Mr. M’s treatment, the use of an antiviral agent in the treatment of his HCV is fundamental, along with avoidance of alcohol and smoking. If he were to accept HCV treatment, we would anticipate resolution of the PCT, but the ongoing progression of his liver and cardiovascular conditions, due perhaps in part, to relative iron overload from his heterozygous HFE mutation. In this situation, we expect that an ongoing course of therapeutic phlebotomy could help to delay the progression of his chronic liver and cardiovascular diseases.

The ideal method of resident education is a subject of great interest within the medical community, and many dermatology residency programs utilize a traditional classroom model for didactic training consisting of required textbook reading completed at home and classroom lectures that often include presentations featuring text, dermatology images, and questions throughout the lecture. A second teaching model is known as the flipped, or inverted, classroom. This model moves the didactic material that typically is covered in the classroom into the realm of home study or homework and focuses on application and clarification of the new material in the classroom. ¹ There is an emphasis on completing and understanding course material prior to the classroom session. Students are expected to be prepared for the lesson, and the classroom session can include question review and deeper exploration of the topic with a focus on subject mastery. ²

In recent years, the flipped classroom model has been used in elementary education, due in part to the influence of teachers Bergmann and Sams,³ as described in their book Flip Your Classroom: Reach Every Student in Every Class Every Day. More recently, Prober and Khan⁴ argued for its use in medical education, and this model has been utilized in medical school curricula to teach specialty subjects, including medical dermatology.⁵

Given the increasing popularity and use of the flipped classroom, the primary objective of this study was to determine if a difference in knowledge acquisition and resident perception exists between the traditional and flipped classrooms. If differences do exist, the secondary aim was to quantify them. We hypothesized that the flipped classroom actively engages residents and would improve both knowledge acquisition and resident sentiment toward the residency program curriculum compared to the traditional model.

Methods

The Duke Health (Durham, North Carolina) institutional review board granted approval for this study. All of the dermatology residents from Duke University Medical Center for the 2014-2015 academic year participated in this study. Twelve individual lectures chosen by the dermatology residency program director were included: 6 traditional lectures and 6 flipped lectures. The lectures were paired for similar content.

Survey Administration
Each resident was assigned a unique 4-digit numeric code that was unknown to the investigators and recorded at the beginning of each survey. The residents expected flipped lectures for each session and were blinded as to when a traditional lecture and quiz would occur, with the exception of the resident providing the lecture. Classroom presentations were immediately followed by a voluntary survey administered through Qualtrics.⁶ Consent was given at the beginning of each survey, followed by 10 factual questions and 10 perception questions. The factual questions varied based on the lecture topic and were multiple-choice questions written by the program director, associate program director, and faculty. Each factual question was worth 10 points, and the scaled score for each quiz had a maximum value of 100. The perception questions were developed by the authors (J.H. and A.R.A.) in consultation with a survey methodology expert at the Duke Social Science Research Institute. These questions remained constant across each survey and were descriptive based on standard response scales. The data were extracted from Qualtrics for statistical analysis.

Statistical Analysis
The mean score with the standard deviation for each factual question quiz was calculated and plotted. A generalized linear mixed model was created to study the difference in quiz scores between the 2 classroom models after adjusting for other covariates, including resident, the interaction between resident and class type, quiz time, and the interaction between class type and quiz time. The variable resident was specified as a random variable, and a variance components covariance structure was used. For the perception questions, the frequency and percentage of each answer for a question was counted. Generalized linear mixed models with a Poisson distribution were created to study the difference in answers for each survey question between the 2 curriculum types after adjusting for other covariates, including scores for factual questions, quiz time, and the interaction between class type and quiz time. The variable resident was again specified as a random variable, and a diagonal covariance structure was used. All statistical analyses were carried out using SAS software package version 9.4 (SAS Institute) by the Duke University Department of Biostatistics and Bioinformatics. P<.05 was considered statistically significant.

Results

All 9 of the department’s residents were included and participated in this study. Mean score with standard deviation for each factual quiz is plotted in the Figure. Across all residents, the mean factual quiz score was slightly higher but not statistically significant in the flipped vs traditional classrooms (67.5% vs 65.4%; P=.448)(data not shown). When comparing traditional and flipped factual quiz scores by individual resident, there was not a significant difference in quiz performance (P=.166)(data not shown). However, there was a significant difference in the factual quiz scores among residents for all quizzes (P=.005) as well as a significant difference in performance between each individual quiz over time (P<.001)(data not shown). In the traditional classroom, residents demonstrated a trend in variable performance with each factual quiz. In the flipped classroom, residents also had variable performance, with wide-ranging scores (P=.008)(data not shown).

 

Each resident also answered 10 perception questions (Table 1). When comparing the responses by quiz type (Table 2), there was a significant difference for several questions in favor of the flipped classroom: how actively residents thought their co-residents participated in the lecture (P<.001), how much each resident enjoyed the session (P=.038), and how much each resident believed their co-residents enjoyed the session (P=.026). Additionally, residents thought that the flipped classroom sessions were more efficient (P=.033), better prepared them for boards (P=.050), and better prepared them for clinical practice (P=.034). There was not a significant difference in the amount of reading and preparation residents did for class (P=.697), how actively the residents thought they participated in the lecture (P=.303), the effectiveness of the day’s curriculum structure (P=.178), or whether residents thought the lesson increased their knowledge on the topic (P=.084).

Comment

The traditional model in medical education has undergone changes in recent years, and researchers have been looking for new ways to convey more information in shorter periods of time, especially as the field of medicine continues to expand. Despite the growing popularity and adoption of the flipped classroom, studies in dermatology have been limited. In this study, we compared a traditional classroom model with the flipped model, assessing both knowledge acquisition and resident perception of the experience.

There was not a significant difference in mean objective quiz scores when comparing the 2 curricula. The flipped model was not better or worse than the traditional teaching model at relaying information and promoting learning. Rather, there was a significant difference in quiz scores based on the individual resident and on the individual quiz. Individual performance was not affected by the teaching model but rather by the individual resident and lecture topic.

These findings differ from a study of internal medicine residents, which revealed that trainees in a quality-improvement flipped classroom had greater increases in knowledge than a traditional cohort.⁷ It is difficult to make direct comparisons to this group, given the difference in specialty and subject content. In comparison, an emergency medicine program completed a cross-sectional cohort study of in-service examination scores in the setting of a traditional curriculum (2011-2012) vs a flipped curriculum (2015-2016) and found that there was no statistical difference in average in-service examination scores.⁸ The type of examination content in this study may be more similar to the quizzes that our residents experienced (ie, fact-based material based on traditional medical knowledge).

The dermatology residents favored the flipped curriculum for 6 of 10 perception questions, which included areas of co-resident participation, personal and co-resident enjoyment, efficiency, boards preparation, and preparation for clinical practice. They did not favor the flipped classroom for prelecture preparation, personal participation, lecture effectiveness, or knowledge acquisition. They perceived their peers as being more engaged and found the flipped classroom to be a more positive experience. The residents thought that the flipped lectures were more time efficient, which could have contributed to overall learner satisfaction. Additionally, they thought that the flipped model better prepared them for both the boards and clinical practice, which are markers of future performance.

These findings are consistent with other studies that revealed improved postcourse perception scores for a quality improvement emergency medicine–flipped classroom. Most of this group preferred the flipped classroom over the traditional after completion of the flipped curriculum.⁹ A neurosurgery residency program also reported increased resident engagement and resident preference for a newly designed flipped curriculum.¹⁰

Overall, our data indicate that there was no objective change in knowledge acquisition at the time of the quiz, but learner satisfaction was significantly greater in the flipped classroom model.

Limitations
This study was comprised of a small number of residents from a single institution and was based on a limited number of lectures given throughout the year. All lectures during the study year were flipped with the exception of the 6 traditional study lectures. Therefore, each resident who presented a traditional lecture was not blinded for her individual assigned lecture. In addition, because traditional lectures only occurred on study days, once the lectures started, all trainees could predict that a content quiz would occur at the end of the session, which could potentially introduce bias toward better quiz performance for the traditional lectures.

Conclusion

When comparing traditional and flipped classroom models, we found no difference in knowledge acquisition. Rather, the difference in quiz scores was among individual residents. There was a significant positive difference in how residents perceived these teaching models, including enjoyment and feeling prepared for the boards. The flipped classroom model provides another opportunity to better engage residents during teaching and should be considered as part of dermatology residency education.



Acknowledgments
Duke Social Sciences Institute postdoctoral fellow Scott Clifford, PhD, and Duke Dermatology residents Daniel Chang, MD; Sinae Kane, MD; Rebecca Bialas, MD; Jolene Jewell, MD; Elizabeth Ju, MD; Michael Raisch, MD; Reed Garza, MD; Joanna Hooten, MD; and E. Schell Bressler, MD (all Durham, North Carolina).

The ideal method of resident education is a subject of great interest within the medical community, and many dermatology residency programs utilize a traditional classroom model for didactic training consisting of required textbook reading completed at home and classroom lectures that often include presentations featuring text, dermatology images, and questions throughout the lecture. A second teaching model is known as the flipped, or inverted, classroom. This model moves the didactic material that typically is covered in the classroom into the realm of home study or homework and focuses on application and clarification of the new material in the classroom. ¹ There is an emphasis on completing and understanding course material prior to the classroom session. Students are expected to be prepared for the lesson, and the classroom session can include question review and deeper exploration of the topic with a focus on subject mastery. ²

In recent years, the flipped classroom model has been used in elementary education, due in part to the influence of teachers Bergmann and Sams,³ as described in their book Flip Your Classroom: Reach Every Student in Every Class Every Day. More recently, Prober and Khan⁴ argued for its use in medical education, and this model has been utilized in medical school curricula to teach specialty subjects, including medical dermatology.⁵

Given the increasing popularity and use of the flipped classroom, the primary objective of this study was to determine if a difference in knowledge acquisition and resident perception exists between the traditional and flipped classrooms. If differences do exist, the secondary aim was to quantify them. We hypothesized that the flipped classroom actively engages residents and would improve both knowledge acquisition and resident sentiment toward the residency program curriculum compared to the traditional model.

Methods

The Duke Health (Durham, North Carolina) institutional review board granted approval for this study. All of the dermatology residents from Duke University Medical Center for the 2014-2015 academic year participated in this study. Twelve individual lectures chosen by the dermatology residency program director were included: 6 traditional lectures and 6 flipped lectures. The lectures were paired for similar content.

Survey Administration
Each resident was assigned a unique 4-digit numeric code that was unknown to the investigators and recorded at the beginning of each survey. The residents expected flipped lectures for each session and were blinded as to when a traditional lecture and quiz would occur, with the exception of the resident providing the lecture. Classroom presentations were immediately followed by a voluntary survey administered through Qualtrics.⁶ Consent was given at the beginning of each survey, followed by 10 factual questions and 10 perception questions. The factual questions varied based on the lecture topic and were multiple-choice questions written by the program director, associate program director, and faculty. Each factual question was worth 10 points, and the scaled score for each quiz had a maximum value of 100. The perception questions were developed by the authors (J.H. and A.R.A.) in consultation with a survey methodology expert at the Duke Social Science Research Institute. These questions remained constant across each survey and were descriptive based on standard response scales. The data were extracted from Qualtrics for statistical analysis.

Statistical Analysis
The mean score with the standard deviation for each factual question quiz was calculated and plotted. A generalized linear mixed model was created to study the difference in quiz scores between the 2 classroom models after adjusting for other covariates, including resident, the interaction between resident and class type, quiz time, and the interaction between class type and quiz time. The variable resident was specified as a random variable, and a variance components covariance structure was used. For the perception questions, the frequency and percentage of each answer for a question was counted. Generalized linear mixed models with a Poisson distribution were created to study the difference in answers for each survey question between the 2 curriculum types after adjusting for other covariates, including scores for factual questions, quiz time, and the interaction between class type and quiz time. The variable resident was again specified as a random variable, and a diagonal covariance structure was used. All statistical analyses were carried out using SAS software package version 9.4 (SAS Institute) by the Duke University Department of Biostatistics and Bioinformatics. P<.05 was considered statistically significant.

Results

All 9 of the department’s residents were included and participated in this study. Mean score with standard deviation for each factual quiz is plotted in the Figure. Across all residents, the mean factual quiz score was slightly higher but not statistically significant in the flipped vs traditional classrooms (67.5% vs 65.4%; P=.448)(data not shown). When comparing traditional and flipped factual quiz scores by individual resident, there was not a significant difference in quiz performance (P=.166)(data not shown). However, there was a significant difference in the factual quiz scores among residents for all quizzes (P=.005) as well as a significant difference in performance between each individual quiz over time (P<.001)(data not shown). In the traditional classroom, residents demonstrated a trend in variable performance with each factual quiz. In the flipped classroom, residents also had variable performance, with wide-ranging scores (P=.008)(data not shown).

 

Each resident also answered 10 perception questions (Table 1). When comparing the responses by quiz type (Table 2), there was a significant difference for several questions in favor of the flipped classroom: how actively residents thought their co-residents participated in the lecture (P<.001), how much each resident enjoyed the session (P=.038), and how much each resident believed their co-residents enjoyed the session (P=.026). Additionally, residents thought that the flipped classroom sessions were more efficient (P=.033), better prepared them for boards (P=.050), and better prepared them for clinical practice (P=.034). There was not a significant difference in the amount of reading and preparation residents did for class (P=.697), how actively the residents thought they participated in the lecture (P=.303), the effectiveness of the day’s curriculum structure (P=.178), or whether residents thought the lesson increased their knowledge on the topic (P=.084).

Comment

The traditional model in medical education has undergone changes in recent years, and researchers have been looking for new ways to convey more information in shorter periods of time, especially as the field of medicine continues to expand. Despite the growing popularity and adoption of the flipped classroom, studies in dermatology have been limited. In this study, we compared a traditional classroom model with the flipped model, assessing both knowledge acquisition and resident perception of the experience.

There was not a significant difference in mean objective quiz scores when comparing the 2 curricula. The flipped model was not better or worse than the traditional teaching model at relaying information and promoting learning. Rather, there was a significant difference in quiz scores based on the individual resident and on the individual quiz. Individual performance was not affected by the teaching model but rather by the individual resident and lecture topic.

These findings differ from a study of internal medicine residents, which revealed that trainees in a quality-improvement flipped classroom had greater increases in knowledge than a traditional cohort.⁷ It is difficult to make direct comparisons to this group, given the difference in specialty and subject content. In comparison, an emergency medicine program completed a cross-sectional cohort study of in-service examination scores in the setting of a traditional curriculum (2011-2012) vs a flipped curriculum (2015-2016) and found that there was no statistical difference in average in-service examination scores.⁸ The type of examination content in this study may be more similar to the quizzes that our residents experienced (ie, fact-based material based on traditional medical knowledge).

The dermatology residents favored the flipped curriculum for 6 of 10 perception questions, which included areas of co-resident participation, personal and co-resident enjoyment, efficiency, boards preparation, and preparation for clinical practice. They did not favor the flipped classroom for prelecture preparation, personal participation, lecture effectiveness, or knowledge acquisition. They perceived their peers as being more engaged and found the flipped classroom to be a more positive experience. The residents thought that the flipped lectures were more time efficient, which could have contributed to overall learner satisfaction. Additionally, they thought that the flipped model better prepared them for both the boards and clinical practice, which are markers of future performance.

These findings are consistent with other studies that revealed improved postcourse perception scores for a quality improvement emergency medicine–flipped classroom. Most of this group preferred the flipped classroom over the traditional after completion of the flipped curriculum.⁹ A neurosurgery residency program also reported increased resident engagement and resident preference for a newly designed flipped curriculum.¹⁰

Overall, our data indicate that there was no objective change in knowledge acquisition at the time of the quiz, but learner satisfaction was significantly greater in the flipped classroom model.

Limitations
This study was comprised of a small number of residents from a single institution and was based on a limited number of lectures given throughout the year. All lectures during the study year were flipped with the exception of the 6 traditional study lectures. Therefore, each resident who presented a traditional lecture was not blinded for her individual assigned lecture. In addition, because traditional lectures only occurred on study days, once the lectures started, all trainees could predict that a content quiz would occur at the end of the session, which could potentially introduce bias toward better quiz performance for the traditional lectures.

Conclusion

When comparing traditional and flipped classroom models, we found no difference in knowledge acquisition. Rather, the difference in quiz scores was among individual residents. There was a significant positive difference in how residents perceived these teaching models, including enjoyment and feeling prepared for the boards. The flipped classroom model provides another opportunity to better engage residents during teaching and should be considered as part of dermatology residency education.



Acknowledgments
Duke Social Sciences Institute postdoctoral fellow Scott Clifford, PhD, and Duke Dermatology residents Daniel Chang, MD; Sinae Kane, MD; Rebecca Bialas, MD; Jolene Jewell, MD; Elizabeth Ju, MD; Michael Raisch, MD; Reed Garza, MD; Joanna Hooten, MD; and E. Schell Bressler, MD (all Durham, North Carolina).

The ideal method of resident education is a subject of great interest within the medical community, and many dermatology residency programs utilize a traditional classroom model for didactic training consisting of required textbook reading completed at home and classroom lectures that often include presentations featuring text, dermatology images, and questions throughout the lecture. A second teaching model is known as the flipped, or inverted, classroom. This model moves the didactic material that typically is covered in the classroom into the realm of home study or homework and focuses on application and clarification of the new material in the classroom. ¹ There is an emphasis on completing and understanding course material prior to the classroom session. Students are expected to be prepared for the lesson, and the classroom session can include question review and deeper exploration of the topic with a focus on subject mastery. ²

In recent years, the flipped classroom model has been used in elementary education, due in part to the influence of teachers Bergmann and Sams,³ as described in their book Flip Your Classroom: Reach Every Student in Every Class Every Day. More recently, Prober and Khan⁴ argued for its use in medical education, and this model has been utilized in medical school curricula to teach specialty subjects, including medical dermatology.⁵

Given the increasing popularity and use of the flipped classroom, the primary objective of this study was to determine if a difference in knowledge acquisition and resident perception exists between the traditional and flipped classrooms. If differences do exist, the secondary aim was to quantify them. We hypothesized that the flipped classroom actively engages residents and would improve both knowledge acquisition and resident sentiment toward the residency program curriculum compared to the traditional model.

Methods

The Duke Health (Durham, North Carolina) institutional review board granted approval for this study. All of the dermatology residents from Duke University Medical Center for the 2014-2015 academic year participated in this study. Twelve individual lectures chosen by the dermatology residency program director were included: 6 traditional lectures and 6 flipped lectures. The lectures were paired for similar content.

Survey Administration
Each resident was assigned a unique 4-digit numeric code that was unknown to the investigators and recorded at the beginning of each survey. The residents expected flipped lectures for each session and were blinded as to when a traditional lecture and quiz would occur, with the exception of the resident providing the lecture. Classroom presentations were immediately followed by a voluntary survey administered through Qualtrics.⁶ Consent was given at the beginning of each survey, followed by 10 factual questions and 10 perception questions. The factual questions varied based on the lecture topic and were multiple-choice questions written by the program director, associate program director, and faculty. Each factual question was worth 10 points, and the scaled score for each quiz had a maximum value of 100. The perception questions were developed by the authors (J.H. and A.R.A.) in consultation with a survey methodology expert at the Duke Social Science Research Institute. These questions remained constant across each survey and were descriptive based on standard response scales. The data were extracted from Qualtrics for statistical analysis.

Statistical Analysis
The mean score with the standard deviation for each factual question quiz was calculated and plotted. A generalized linear mixed model was created to study the difference in quiz scores between the 2 classroom models after adjusting for other covariates, including resident, the interaction between resident and class type, quiz time, and the interaction between class type and quiz time. The variable resident was specified as a random variable, and a variance components covariance structure was used. For the perception questions, the frequency and percentage of each answer for a question was counted. Generalized linear mixed models with a Poisson distribution were created to study the difference in answers for each survey question between the 2 curriculum types after adjusting for other covariates, including scores for factual questions, quiz time, and the interaction between class type and quiz time. The variable resident was again specified as a random variable, and a diagonal covariance structure was used. All statistical analyses were carried out using SAS software package version 9.4 (SAS Institute) by the Duke University Department of Biostatistics and Bioinformatics. P<.05 was considered statistically significant.

Results

All 9 of the department’s residents were included and participated in this study. Mean score with standard deviation for each factual quiz is plotted in the Figure. Across all residents, the mean factual quiz score was slightly higher but not statistically significant in the flipped vs traditional classrooms (67.5% vs 65.4%; P=.448)(data not shown). When comparing traditional and flipped factual quiz scores by individual resident, there was not a significant difference in quiz performance (P=.166)(data not shown). However, there was a significant difference in the factual quiz scores among residents for all quizzes (P=.005) as well as a significant difference in performance between each individual quiz over time (P<.001)(data not shown). In the traditional classroom, residents demonstrated a trend in variable performance with each factual quiz. In the flipped classroom, residents also had variable performance, with wide-ranging scores (P=.008)(data not shown).

 

Each resident also answered 10 perception questions (Table 1). When comparing the responses by quiz type (Table 2), there was a significant difference for several questions in favor of the flipped classroom: how actively residents thought their co-residents participated in the lecture (P<.001), how much each resident enjoyed the session (P=.038), and how much each resident believed their co-residents enjoyed the session (P=.026). Additionally, residents thought that the flipped classroom sessions were more efficient (P=.033), better prepared them for boards (P=.050), and better prepared them for clinical practice (P=.034). There was not a significant difference in the amount of reading and preparation residents did for class (P=.697), how actively the residents thought they participated in the lecture (P=.303), the effectiveness of the day’s curriculum structure (P=.178), or whether residents thought the lesson increased their knowledge on the topic (P=.084).

Comment

The traditional model in medical education has undergone changes in recent years, and researchers have been looking for new ways to convey more information in shorter periods of time, especially as the field of medicine continues to expand. Despite the growing popularity and adoption of the flipped classroom, studies in dermatology have been limited. In this study, we compared a traditional classroom model with the flipped model, assessing both knowledge acquisition and resident perception of the experience.

There was not a significant difference in mean objective quiz scores when comparing the 2 curricula. The flipped model was not better or worse than the traditional teaching model at relaying information and promoting learning. Rather, there was a significant difference in quiz scores based on the individual resident and on the individual quiz. Individual performance was not affected by the teaching model but rather by the individual resident and lecture topic.

These findings differ from a study of internal medicine residents, which revealed that trainees in a quality-improvement flipped classroom had greater increases in knowledge than a traditional cohort.⁷ It is difficult to make direct comparisons to this group, given the difference in specialty and subject content. In comparison, an emergency medicine program completed a cross-sectional cohort study of in-service examination scores in the setting of a traditional curriculum (2011-2012) vs a flipped curriculum (2015-2016) and found that there was no statistical difference in average in-service examination scores.⁸ The type of examination content in this study may be more similar to the quizzes that our residents experienced (ie, fact-based material based on traditional medical knowledge).

The dermatology residents favored the flipped curriculum for 6 of 10 perception questions, which included areas of co-resident participation, personal and co-resident enjoyment, efficiency, boards preparation, and preparation for clinical practice. They did not favor the flipped classroom for prelecture preparation, personal participation, lecture effectiveness, or knowledge acquisition. They perceived their peers as being more engaged and found the flipped classroom to be a more positive experience. The residents thought that the flipped lectures were more time efficient, which could have contributed to overall learner satisfaction. Additionally, they thought that the flipped model better prepared them for both the boards and clinical practice, which are markers of future performance.

These findings are consistent with other studies that revealed improved postcourse perception scores for a quality improvement emergency medicine–flipped classroom. Most of this group preferred the flipped classroom over the traditional after completion of the flipped curriculum.⁹ A neurosurgery residency program also reported increased resident engagement and resident preference for a newly designed flipped curriculum.¹⁰

Overall, our data indicate that there was no objective change in knowledge acquisition at the time of the quiz, but learner satisfaction was significantly greater in the flipped classroom model.

Limitations
This study was comprised of a small number of residents from a single institution and was based on a limited number of lectures given throughout the year. All lectures during the study year were flipped with the exception of the 6 traditional study lectures. Therefore, each resident who presented a traditional lecture was not blinded for her individual assigned lecture. In addition, because traditional lectures only occurred on study days, once the lectures started, all trainees could predict that a content quiz would occur at the end of the session, which could potentially introduce bias toward better quiz performance for the traditional lectures.

Conclusion

When comparing traditional and flipped classroom models, we found no difference in knowledge acquisition. Rather, the difference in quiz scores was among individual residents. There was a significant positive difference in how residents perceived these teaching models, including enjoyment and feeling prepared for the boards. The flipped classroom model provides another opportunity to better engage residents during teaching and should be considered as part of dermatology residency education.



Acknowledgments
Duke Social Sciences Institute postdoctoral fellow Scott Clifford, PhD, and Duke Dermatology residents Daniel Chang, MD; Sinae Kane, MD; Rebecca Bialas, MD; Jolene Jewell, MD; Elizabeth Ju, MD; Michael Raisch, MD; Reed Garza, MD; Joanna Hooten, MD; and E. Schell Bressler, MD (all Durham, North Carolina).

Providing high-quality, patient-centered health care is a top priority for the US Department of Veterans Affairs (VA) Veteran Health Administration (VHA), whose core mission is to improve the health and well-being of US veterans. Thus, news of long wait times for medical appointments in the VHA sparked intense national attention and debate and led to changes in senior management and legislative action. ¹ On August 8, 2014, President Bara c k Obama signed the Veterans Access, Choice, and Accountability Act of 2014, also known as the Choice Act, which provided an additional $16 billion in emergency spending over 3 years to improve veterans’ access to timely health care. ² The Choice Act sought to develop an integrated health care network that allowed qualified VHA patients to receive specific health care services in their communities delivered by non-VHA health care providers (HCPs) but paid for by the VHA. The Choice Act also laid out explicit criteria for how to prioritize who would be eligible for VHA-purchased civilian care: (1) veterans who could not get timely appointments at a VHA medical facility within 30 days of referral; or (2) veterans who lived > 40 miles from the closest VHA medical facility.

VHA decision makers seeking to improve care delivery also need to weigh trade-offs between alternative approaches to providing rapid access. For instance, increasing access to non-VHA HCPs may not always decrease wait times and could result in loss of continuity, limited care coordination, limited ability to ensure and enforce high-quality standards at the VHA, and other challenges.^3-6 Although the concerns and views of elected representatives, advocacy groups, and health system leaders are important, it is unknown whether these views and preferences align with those of veterans. Arguably, the range of views and concerns of informed veterans whose health is at stake should be particularly prominent in such policy decision making.

To identify the considerations that were most important to veterans regarding VHA policy around decreasing wait times, a study was designed to engage a group of veterans who were eligible for civilian care under the Choice Act. The study took place 1 year after the Choice Act was passed. Veterans were asked to focus on 2 related questions: First, how should funding be used for building VHA capacity (build) vs purchasing civilian care (buy)? Second, under what circumstances should civilian care be prioritized?

The aim of this paper is to describe democratic deliberation (DD), a specific method that engaged veteran patients in complex policy decisions around access to care. DD methods have been used increasingly in health care for developing policy guidance, setting priorities, providing advice on ethical dilemmas, weighing risk-benefit trade-offs, and determining decision-making authority.^7-12 For example, DD helped guide national policy for mammography screening for breast cancer in New Zealand.¹³ The Agency for Healthcare Research and Quality has completed a systematic review and a large, randomized experiment on best practices for carrying out public deliberation.^8,13,14 However, despite the potential value of this approach, there has been little use of deliberative methods within the VHA for the explicit purpose of informing veteran health care delivery.

This paper describes the experience engaging veterans by using DD methodology and informing VHA leadership about the results of those deliberations. The specific aims were to understand whether DD is an acceptable approach to use to engage patients in the medical services policy-making process within VHA and whether veterans are able to come to an informed consensus.

 

Methods

Engaging patients and incorporating their needs and concerns within the policy-making process may improve health system policies and make those policies more patient centered. Such engagement also could be a way to generate creative solutions. However, because health-system decisions often involve making difficult trade-offs, effectively obtaining patient population input on complex care delivery issues can be challenging.

Although surveys can provide intuitive, top-of-mind input from respondents, these opinions are generally not sufficient for resolving complex problems.¹⁵ Focus groups and interviews may produce results that are more in-depth than surveys, but these methods tend to elicit settled private preferences rather than opinions about what the community should do.¹⁶ DD, on the other hand, is designed to elicit deeply informed public opinions on complex, value-laden topics to develop recommendations and policies for a larger community.¹⁷ The goal is to find collective solutions to challenging social problems. DD achieves this by giving participants an opportunity to explore a topic in-depth, question experts, and engage peers in reason-based discussions.^18,19 This method has its roots in political science and has been used over several decades to successfully inform policy making on a broad array of topics nationally and internationally—from health research ethics in the US to nuclear and energy policy in Japan.^7,16,20,21 DD has been found to promote ownership of public programs and lend legitimacy to policy decisions, political institutions, and democracy itself.¹⁸

A single day (8 hours) DD session was convened, following a Citizens Jury model of deliberation, which brings veteran patients together to learn about a topic, ask questions of experts, deliberate with peers, and generate a “citizen’s report” that contains a set of recommendations (Table 1). An overview of the different models of DD and rationale for each can be found elsewhere.^8,15

Recruitment Considerations

A purposively selected sample of civilian care-eligible veterans from a midwestern VHA health care system (1 medical center and 3 community-based outpatient clinics [CBOCs]) were invited to the DD session. The targeted number of participants was 30. Female veterans, who comprise only 7% of the local veteran population, were oversampled to account for their potentially different health care needs and to create balance between males and females in the session. Oversampling for other characteristics was not possible due to the relatively small sample size. Based on prior experience,⁷ it was assumed that 70% of willing participants would attend the session; therefore 34 veterans were invited and 24 attended. Each participant received a $200 incentive in appreciation for their substantial time commitment and to offset transportation costs.

Background Materials

A packet with educational materials (Flesch-Kincaid Grade Level of 10.5) was mailed to participants about 2 weeks before the DD session. Participants were asked to review prior to attending the session. These materials described the session (eg, purpose, organizers, importance) and provided factual information about the Choice Act (eg, eligibility, out-of-pocket costs, travel pay, prescription drug policies).

Session Overview

The session was structured to accomplish the following goals: (1) Elicit participants’ opinions about access to health care and reasons for those opinions; (2) Provide in-depth education about the Choice Act through presentations and discussions with topical experts; and (3) Elicit reasoning and recommendations on both the criteria by which participants prioritize candidates for civilian care and how participants would allocate additional funding to improve access (ie, by building VHA capacity to deliver more timely health care vs purchasing health care from civilian HCPs).

 

Participants were asked to fill out a survey on arrival in the morning and were assigned to 1 of 3 tables or small groups. Each table had a facilitator who had extensive experience in qualitative data collection methods and guided the dialogue using a scripted protocol that they helped develop and refine. The facilitation materials drew from and used previously published studies.^22,23 Each facilitator audio recorded the sessions and took notes. Three experts presented during plenary education sessions. Presentations were designed to provide balanced factual information and included a veteran’s perspective. One presenter was a clinician on the project team, another was a local clinical leader responsible for making decisions about what services to provide via civilian care (buy) vs enhancing the local VHA health system’s ability to provide those services (build), and the third presenter was a veteran who was on the project team.

Education Session 1

The first plenary education session with expert presentations was conducted after each table completed an icebreaker exercise. The project team physician provided a brief history and description of the Choice Act to reinforce educational materials sent to participants prior to the session. The health system clinical leader described his decision process and principles and highlighted constraints placed on him by the Choice Act that were in place at the time of the DD session. He also described existing local and national programs to provide civilian care (eg, local fee-basis non-VHA care programs) and how these programs sought to achieve goals similar to the Choice Act. The veteran presenter focused on the importance of session participants providing candid insight and observations and emphasized that this session was a significant opportunity to “have their voices heard.”

Deliberation 1: What criteria should be used to prioritize patients for receiving civilian care paid for by the VHA? To elicit preferences on the central question of this deliberation, participants were presented with 8 real-world cases that were based on interviews conducted with Choice Act-eligible veterans (Table 2 and eAppendices A

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 , and D 

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 ). Participants were first instructed to read through and discuss the cases as a group, then come to agreement on prioritizing how the patients in the case scenarios should receive civilian care. Agreement was defined as having complete consensus or consensus by the majority, in which case, the facilitator noted the number who agreed and disagreed within each group. The facilitators documented the criteria each group considered as they prioritized the cases, along with the group’s reasoning behind their choices.

Education Session 2

In the second plenary session, the project team physician provided information about health care access issues, both inside and outside of the VHA, particularly between urban and rural areas. He also discussed factors related to the insufficient capacity to meet growing demand that contributed to the VHA wait-time crisis. The veteran presenter shared reflections on health care access from a veteran’s perspective.

Deliberation 2: How should additional funding be divided between increasing the ability of the VHA to (1) provide care by VHA HCPs; and (2) pay for care from non-VHA civilian HCPs? Participants were presented the patient examples and Choice Act funding scenarios (the buy policy option) and contrasted that with a build policy option. Participants were explicitly encouraged to shift their perspectives from thinking about individual cases to considering policy-level decisions and the broader social good (Table 2).

 

Ensuring Robust Deliberations

If participants do not adequately grasp the complexities of the topic, a deliberation can fail. To facilitate nuanced reasoning, real-world concrete examples were developed as the starting point of each deliberation based on interviews with actual patients (deliberation 1) and actual policy proposals relevant to the funding allocation decisions within the Choice Act (deliberation 2).

A deliberation also can fail with self-silencing, where participants withhold opinions that differ from those articulated first or by more vocal members of the group.²⁴ To combat self-silencing, highly experienced facilitators were used to ensure sharing from all participants and to support an open-minded, courteous, and reason-based environment for discourse. It was specified that the best solutions are achieved through reason-based and cordial disagreement and that success can be undermined when participants simply agree because it is easier or more comfortable.

A third way a deliberation can fail is if individuals do not adopt a group or system-level perspective. To counter this, facilitators reinforced at multiple points the importance of taking a broader social perspective rather than sharing only one’s personal preferences.

Finally, it is important to assess the quality of the deliberative process itself, to ensure that results are trustworthy.²⁵ To assess the quality of the deliberative process, participants knowledge about key issues pre- and postdeliberation were assessed. Participants also were asked to rate the quality of the facilitators and how well they felt their voice was heard and respected, and facilitators made qualitative assessments about the extent to which participants were engaged in reason-based and collaborative discussion.

Data

Quantitative data were collected via pre- and postsession surveys. The surveys contained items related to knowledge about the Choice Act, expectations for the DD session, beliefs and opinions about the provision of health care for veterans, recommended funding allocations between build vs buy policy options, and general demographics. Qualitative data were collected through detailed notes taken by the 3 facilitators. Each table’s deliberations were audio recorded so that gaps in the notes could be filled.

The 3 facilitators, who were all experienced qualitative researchers, typed their written notes into a template immediately after the session. Two of the 3 facilitators led the analysis of the session notes. Findings within and across the 3 deliberation tables were developed using content and matrix analysis methods.²⁶ Descriptive statistics were generated from survey responses and compared survey items pre- and postsession using paired t tests or χ² tests for categorical responses.

Results

Thirty-three percent of individuals invited (n = 127) agreed to participate. Those who declined cited conflicts related to distance, transportation, work/school, medical appointments, family commitments, or were not interested. In all, 24 (69%) of the 35 veterans who accepted the invitation attended the deliberation session. Of the 11 who accepted but did not attend, 5 cancelled ahead of time because of conflicts (Figure). Most participants were male (70%), 48% were aged 61 to 75 years, 65% were white, 43% had some college education, 43% reported an annual income of between $25,000 and $40,000, and only 35% reported very good health (eAppendix D).

 

Deliberation 1

During the deliberation on the prioritization criteria, the concept of “condition severity” emerged as an important criterion for veterans. This criterion captured simultaneous consideration of both clinical necessity and burden on the veteran to obtain care. For example, participants felt that patients with a life-threatening illness should be prioritized for civilian care over patients who need preventative or primary care (clinical necessity) and that elderly patients with substantial difficulty traveling to VHA appointments should be prioritized over patients who can travel more easily (burden). The Choice Act regulations at the time of the DD session did not reflect this nuanced perspective, stipulating only that veterans must live > 40 miles from the nearest VHA medical facility.

One of the 3 groups did not prioritize the patient cases because some members felt that no veteran should be constrained from receiving civilian care if they desired it. Nonetheless, this group did agree with prioritizing the first 2 cases in Table 3. The other groups prioritized all 8 cases in generally similar ways.

Deliberation 2

No clear consensus emerged on the buy vs build question. A representative from each table presented their group’s positions, rationale, and recommendations after deliberations were completed. After hearing the range of positions, the groups then had another opportunity to deliberate based on what they heard from the other tables; no new recommendations or consensus emerged.

Participants who were in favor of allocating more funds toward the build policy offered a range of rationales, saying that it would (1) increase access for rural veterans by building CBOCs and deploying more mobile units that could bring outlets for health care closer to their home communities; (2) provide critical and unique medical expertise to address veteran-specific issues such as prosthetics, traumatic brain injury, posttraumatic stress disorder, spinal cord injury, and shrapnel wounds that are typically not available through civilian providers; (3) give VHA more oversight over the quality and cost of care, which is more challenging to do with civilian providers; and (4) Improve VHA infrastructure by, for example, upgrading technology and attracting the best clinicians and staff to support “our VHA.”

Participants who were in favor of allocating more funds toward the buy policy also offered a range of rationales, saying that it would (1) decrease patient burden by increasing access through community providers, decreasing wait time, and lessening personal cost and travel time; (2) allow more patients to receive civilian care, which was generally seen as beneficial by a few participants because of perceptions that the VHA provides lower quality care due to a shortage of VHA providers, run-down/older facilities, lack of technology, and poorer-quality VHA providers; and (3) provide an opportunity to divest of costly facilities and invest in other innovative approaches. Regarding this last reason, a few participants felt that the VHA is “gouged” when building medical centers that overrun budgets. They also were concerned that investing in facilities tied VHA to specific locations when current locations of veterans may change “25 years from now.”

 

Survey Results

Twenty-three of the 24 participants completed both pre- and postsession surveys. The majority of participants in the session felt people in the group respected their opinion (96%); felt that the facilitator did not try to influence the group with her own opinions (96%); indicated they understood the information enough to participate as much as they wanted (100%); and were hopeful that their reasoning and recommendations would help inform VHA policy makers (82%).

The surveys also provided an opportunity to examine the extent to which knowledge, attitudes, and opinions changed from before to after the deliberation. Even with the small sample, responses revealed a trend toward improved knowledge about key elements of the Choice Act and its goals. Further, there was a shift in some participants’ opinions about how patients should be prioritized to receive civilian care. For example, before the deliberation participants generally felt that all veterans should be able to receive civilian care, whereas postdeliberation this was not the case. Postdeliberation, most participants felt that primary care should not be a high priority for civilian care but continued to endorse prioritizing civilian care for specialty services like orthopedic or cardiology-related care. Finally, participants moved from more diverse recommendations regarding additional funds allocations, toward consensus after the deliberation around allocating funds to the build policy. Eight participants supported a build policy beforehand, whereas 16 supported this policy afterward.

Discussion

This study explored DD as a method for deeply engaging veterans in complex policy making to guide funding allocation and prioritization decisions related to the Choice Act, decisions that are still very relevant today within the context of the Mission Act and have substantial implications for how health care is delivered in the VHA. The Mission Act passed on June 6, 2018, with the goal of improving access to and the reliability of civilian or community care for eligible veterans.²⁷ Decisions related to appropriating scarce funding to improve access to care is an emotional and value-laden topic that elicited strong and divergent opinions among the participants. Veterans were eager to have their voices heard and had strong expectations that VHA leadership would be briefed about their recommendations. The majority of participants were satisfied with the deliberation process, felt they understood the issues, and felt their opinions were respected. They expressed feelings of comradery and community throughout the process.

In this single deliberation session, the groups did not achieve a single, final consensus regarding how VHA funding should ultimately be allocated between buy and build policy options. Nonetheless, participants provided a rich array of recommendations and rationale for them. Session moderators observed rich, sophisticated, fair, and reason-based discussions on this complex topic. Participants left with a deeper knowledge and appreciation for the complex trade-offs and expressed strong rationales for both sides of the policy debate on build vs buy. In addition, the project yielded results of high interest to VHA policy makers.

This work was presented in multiple venues between 2015 to 2016, and to both local and national VHA leadership, including the local Executive Quality Leadership Boards, the VHA Central Office Committee on the Future State of VA Community Care, the VA Office of Patient Centered Care, and the National Veteran Experience Committee. Through these discussions and others, we saw great interest within the VHA system and high-level leaders to explore ways to include veterans’ voices in the policy-making process. This work was invaluable to our research team (eAppendix E 

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 ), has influenced the methodology of multiple research grants within the VA that seek to engage veterans in the research process, and played a pivotal role in the development of the Veteran Experience Office.

Many health system decisions regarding what care should be delivered (and how) involve making difficult, value-laden choices in the context of limited resources. DD methods can be used to target and obtain specific viewpoints from diverse populations, such as the informed perspectives of minority and underrepresented populations within the VHA.¹⁹ For example, female veterans were oversampled to ensure that the informed preferences of this population was obtained. Thus, DD methods could provide a valuable tool for health systems to elicit in-depth diverse patient input on high-profile policies that will have a substantial impact on the system’s patient population.

 

Limitations

One potential downside of DD is that, because of the resource-intensive nature of deliberation sessions, they are often conducted with relatively small groups.⁹ Viewpoints of those within these small samples who are willing to spend an entire day discussing a complex topic may not be representative of the larger patient community. However, the core goal of DD is diversity of opinions rather than representativeness.

A stratified random sampling strategy that oversampled for underrepresented and minority populations was used to help select a diverse group that represents the population on key characteristics and partially addresses concern about representativeness. Efforts to optimize participation rates, including providing monetary incentives, also are helpful and have led to high participation rates in past deliberations.⁷

Health system communication strategies that promote the importance of becoming involved in DD sessions also may be helpful in improving rates of recruitment. On particularly important topics where health system leaders feel a larger resource investment is justified, conducting larger scale deliberations with many small groups may obtain more generalizable evidence about what individual patients and groups of patients recommend.⁷ However, due to the inherent limitations of surveys and focus group approaches for obtaining informed views on complex topics, there are no clear systematic alternatives to the DD approach.

Conclusion

DD is an effective method to meaningfully engage patients in deep deliberations to guide complex policy making. Although design of deliberative sessions is resource-intensive, patient engagement efforts, such as those described in this paper, could be an important aspect of a well-functioning learning health system. Further research into alternative, streamlined methods that can also engage veterans more deeply is needed. DD also can be combined with other approaches to broaden and confirm findings, including focus groups, town hall meetings, or surveys.

Although this study did not provide consensus on how the VHA should allocate funds with respect to the Choice Act, it did provide insight into the importance and feasibility of engaging veterans in the policy-making process. As more policies aimed at improving veterans’ access to civilian care are created, such as the most recent Mission Act, policy makers should strongly consider using the DD method of obtaining informed veteran input into future policy decisions.

Acknowledgments
Funding was provided by the US Department of Veterans Affairs Office of Analytics and Business Intelligence (OABI) and the VA Quality Enhancement Research Initiative (QUERI). Dr. Caverly was supported in part by a VA Career Development Award (CDA 16-151). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). The authors thank the veterans who participated in this work. They also thank Caitlin Reardon and Natalya Wawrin for their assistance in organizing the deliberation session.

Providing high-quality, patient-centered health care is a top priority for the US Department of Veterans Affairs (VA) Veteran Health Administration (VHA), whose core mission is to improve the health and well-being of US veterans. Thus, news of long wait times for medical appointments in the VHA sparked intense national attention and debate and led to changes in senior management and legislative action. ¹ On August 8, 2014, President Bara c k Obama signed the Veterans Access, Choice, and Accountability Act of 2014, also known as the Choice Act, which provided an additional $16 billion in emergency spending over 3 years to improve veterans’ access to timely health care. ² The Choice Act sought to develop an integrated health care network that allowed qualified VHA patients to receive specific health care services in their communities delivered by non-VHA health care providers (HCPs) but paid for by the VHA. The Choice Act also laid out explicit criteria for how to prioritize who would be eligible for VHA-purchased civilian care: (1) veterans who could not get timely appointments at a VHA medical facility within 30 days of referral; or (2) veterans who lived > 40 miles from the closest VHA medical facility.

VHA decision makers seeking to improve care delivery also need to weigh trade-offs between alternative approaches to providing rapid access. For instance, increasing access to non-VHA HCPs may not always decrease wait times and could result in loss of continuity, limited care coordination, limited ability to ensure and enforce high-quality standards at the VHA, and other challenges.^3-6 Although the concerns and views of elected representatives, advocacy groups, and health system leaders are important, it is unknown whether these views and preferences align with those of veterans. Arguably, the range of views and concerns of informed veterans whose health is at stake should be particularly prominent in such policy decision making.

To identify the considerations that were most important to veterans regarding VHA policy around decreasing wait times, a study was designed to engage a group of veterans who were eligible for civilian care under the Choice Act. The study took place 1 year after the Choice Act was passed. Veterans were asked to focus on 2 related questions: First, how should funding be used for building VHA capacity (build) vs purchasing civilian care (buy)? Second, under what circumstances should civilian care be prioritized?

The aim of this paper is to describe democratic deliberation (DD), a specific method that engaged veteran patients in complex policy decisions around access to care. DD methods have been used increasingly in health care for developing policy guidance, setting priorities, providing advice on ethical dilemmas, weighing risk-benefit trade-offs, and determining decision-making authority.^7-12 For example, DD helped guide national policy for mammography screening for breast cancer in New Zealand.¹³ The Agency for Healthcare Research and Quality has completed a systematic review and a large, randomized experiment on best practices for carrying out public deliberation.^8,13,14 However, despite the potential value of this approach, there has been little use of deliberative methods within the VHA for the explicit purpose of informing veteran health care delivery.

This paper describes the experience engaging veterans by using DD methodology and informing VHA leadership about the results of those deliberations. The specific aims were to understand whether DD is an acceptable approach to use to engage patients in the medical services policy-making process within VHA and whether veterans are able to come to an informed consensus.

 

Methods

Engaging patients and incorporating their needs and concerns within the policy-making process may improve health system policies and make those policies more patient centered. Such engagement also could be a way to generate creative solutions. However, because health-system decisions often involve making difficult trade-offs, effectively obtaining patient population input on complex care delivery issues can be challenging.

Although surveys can provide intuitive, top-of-mind input from respondents, these opinions are generally not sufficient for resolving complex problems.¹⁵ Focus groups and interviews may produce results that are more in-depth than surveys, but these methods tend to elicit settled private preferences rather than opinions about what the community should do.¹⁶ DD, on the other hand, is designed to elicit deeply informed public opinions on complex, value-laden topics to develop recommendations and policies for a larger community.¹⁷ The goal is to find collective solutions to challenging social problems. DD achieves this by giving participants an opportunity to explore a topic in-depth, question experts, and engage peers in reason-based discussions.^18,19 This method has its roots in political science and has been used over several decades to successfully inform policy making on a broad array of topics nationally and internationally—from health research ethics in the US to nuclear and energy policy in Japan.^7,16,20,21 DD has been found to promote ownership of public programs and lend legitimacy to policy decisions, political institutions, and democracy itself.¹⁸

A single day (8 hours) DD session was convened, following a Citizens Jury model of deliberation, which brings veteran patients together to learn about a topic, ask questions of experts, deliberate with peers, and generate a “citizen’s report” that contains a set of recommendations (Table 1). An overview of the different models of DD and rationale for each can be found elsewhere.^8,15

Recruitment Considerations

A purposively selected sample of civilian care-eligible veterans from a midwestern VHA health care system (1 medical center and 3 community-based outpatient clinics [CBOCs]) were invited to the DD session. The targeted number of participants was 30. Female veterans, who comprise only 7% of the local veteran population, were oversampled to account for their potentially different health care needs and to create balance between males and females in the session. Oversampling for other characteristics was not possible due to the relatively small sample size. Based on prior experience,⁷ it was assumed that 70% of willing participants would attend the session; therefore 34 veterans were invited and 24 attended. Each participant received a $200 incentive in appreciation for their substantial time commitment and to offset transportation costs.

Background Materials

A packet with educational materials (Flesch-Kincaid Grade Level of 10.5) was mailed to participants about 2 weeks before the DD session. Participants were asked to review prior to attending the session. These materials described the session (eg, purpose, organizers, importance) and provided factual information about the Choice Act (eg, eligibility, out-of-pocket costs, travel pay, prescription drug policies).

Session Overview

The session was structured to accomplish the following goals: (1) Elicit participants’ opinions about access to health care and reasons for those opinions; (2) Provide in-depth education about the Choice Act through presentations and discussions with topical experts; and (3) Elicit reasoning and recommendations on both the criteria by which participants prioritize candidates for civilian care and how participants would allocate additional funding to improve access (ie, by building VHA capacity to deliver more timely health care vs purchasing health care from civilian HCPs).

 

Participants were asked to fill out a survey on arrival in the morning and were assigned to 1 of 3 tables or small groups. Each table had a facilitator who had extensive experience in qualitative data collection methods and guided the dialogue using a scripted protocol that they helped develop and refine. The facilitation materials drew from and used previously published studies.^22,23 Each facilitator audio recorded the sessions and took notes. Three experts presented during plenary education sessions. Presentations were designed to provide balanced factual information and included a veteran’s perspective. One presenter was a clinician on the project team, another was a local clinical leader responsible for making decisions about what services to provide via civilian care (buy) vs enhancing the local VHA health system’s ability to provide those services (build), and the third presenter was a veteran who was on the project team.

Education Session 1

The first plenary education session with expert presentations was conducted after each table completed an icebreaker exercise. The project team physician provided a brief history and description of the Choice Act to reinforce educational materials sent to participants prior to the session. The health system clinical leader described his decision process and principles and highlighted constraints placed on him by the Choice Act that were in place at the time of the DD session. He also described existing local and national programs to provide civilian care (eg, local fee-basis non-VHA care programs) and how these programs sought to achieve goals similar to the Choice Act. The veteran presenter focused on the importance of session participants providing candid insight and observations and emphasized that this session was a significant opportunity to “have their voices heard.”

Deliberation 1: What criteria should be used to prioritize patients for receiving civilian care paid for by the VHA? To elicit preferences on the central question of this deliberation, participants were presented with 8 real-world cases that were based on interviews conducted with Choice Act-eligible veterans (Table 2 and eAppendices A

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, B 

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,  C 

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 , and D 

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 ). Participants were first instructed to read through and discuss the cases as a group, then come to agreement on prioritizing how the patients in the case scenarios should receive civilian care. Agreement was defined as having complete consensus or consensus by the majority, in which case, the facilitator noted the number who agreed and disagreed within each group. The facilitators documented the criteria each group considered as they prioritized the cases, along with the group’s reasoning behind their choices.

Education Session 2

In the second plenary session, the project team physician provided information about health care access issues, both inside and outside of the VHA, particularly between urban and rural areas. He also discussed factors related to the insufficient capacity to meet growing demand that contributed to the VHA wait-time crisis. The veteran presenter shared reflections on health care access from a veteran’s perspective.

Deliberation 2: How should additional funding be divided between increasing the ability of the VHA to (1) provide care by VHA HCPs; and (2) pay for care from non-VHA civilian HCPs? Participants were presented the patient examples and Choice Act funding scenarios (the buy policy option) and contrasted that with a build policy option. Participants were explicitly encouraged to shift their perspectives from thinking about individual cases to considering policy-level decisions and the broader social good (Table 2).

 

Ensuring Robust Deliberations

If participants do not adequately grasp the complexities of the topic, a deliberation can fail. To facilitate nuanced reasoning, real-world concrete examples were developed as the starting point of each deliberation based on interviews with actual patients (deliberation 1) and actual policy proposals relevant to the funding allocation decisions within the Choice Act (deliberation 2).

A deliberation also can fail with self-silencing, where participants withhold opinions that differ from those articulated first or by more vocal members of the group.²⁴ To combat self-silencing, highly experienced facilitators were used to ensure sharing from all participants and to support an open-minded, courteous, and reason-based environment for discourse. It was specified that the best solutions are achieved through reason-based and cordial disagreement and that success can be undermined when participants simply agree because it is easier or more comfortable.

A third way a deliberation can fail is if individuals do not adopt a group or system-level perspective. To counter this, facilitators reinforced at multiple points the importance of taking a broader social perspective rather than sharing only one’s personal preferences.

Finally, it is important to assess the quality of the deliberative process itself, to ensure that results are trustworthy.²⁵ To assess the quality of the deliberative process, participants knowledge about key issues pre- and postdeliberation were assessed. Participants also were asked to rate the quality of the facilitators and how well they felt their voice was heard and respected, and facilitators made qualitative assessments about the extent to which participants were engaged in reason-based and collaborative discussion.

Data

Quantitative data were collected via pre- and postsession surveys. The surveys contained items related to knowledge about the Choice Act, expectations for the DD session, beliefs and opinions about the provision of health care for veterans, recommended funding allocations between build vs buy policy options, and general demographics. Qualitative data were collected through detailed notes taken by the 3 facilitators. Each table’s deliberations were audio recorded so that gaps in the notes could be filled.

The 3 facilitators, who were all experienced qualitative researchers, typed their written notes into a template immediately after the session. Two of the 3 facilitators led the analysis of the session notes. Findings within and across the 3 deliberation tables were developed using content and matrix analysis methods.²⁶ Descriptive statistics were generated from survey responses and compared survey items pre- and postsession using paired t tests or χ² tests for categorical responses.

Results

Thirty-three percent of individuals invited (n = 127) agreed to participate. Those who declined cited conflicts related to distance, transportation, work/school, medical appointments, family commitments, or were not interested. In all, 24 (69%) of the 35 veterans who accepted the invitation attended the deliberation session. Of the 11 who accepted but did not attend, 5 cancelled ahead of time because of conflicts (Figure). Most participants were male (70%), 48% were aged 61 to 75 years, 65% were white, 43% had some college education, 43% reported an annual income of between $25,000 and $40,000, and only 35% reported very good health (eAppendix D).

 

Deliberation 1

During the deliberation on the prioritization criteria, the concept of “condition severity” emerged as an important criterion for veterans. This criterion captured simultaneous consideration of both clinical necessity and burden on the veteran to obtain care. For example, participants felt that patients with a life-threatening illness should be prioritized for civilian care over patients who need preventative or primary care (clinical necessity) and that elderly patients with substantial difficulty traveling to VHA appointments should be prioritized over patients who can travel more easily (burden). The Choice Act regulations at the time of the DD session did not reflect this nuanced perspective, stipulating only that veterans must live > 40 miles from the nearest VHA medical facility.

One of the 3 groups did not prioritize the patient cases because some members felt that no veteran should be constrained from receiving civilian care if they desired it. Nonetheless, this group did agree with prioritizing the first 2 cases in Table 3. The other groups prioritized all 8 cases in generally similar ways.

Deliberation 2

No clear consensus emerged on the buy vs build question. A representative from each table presented their group’s positions, rationale, and recommendations after deliberations were completed. After hearing the range of positions, the groups then had another opportunity to deliberate based on what they heard from the other tables; no new recommendations or consensus emerged.

Participants who were in favor of allocating more funds toward the build policy offered a range of rationales, saying that it would (1) increase access for rural veterans by building CBOCs and deploying more mobile units that could bring outlets for health care closer to their home communities; (2) provide critical and unique medical expertise to address veteran-specific issues such as prosthetics, traumatic brain injury, posttraumatic stress disorder, spinal cord injury, and shrapnel wounds that are typically not available through civilian providers; (3) give VHA more oversight over the quality and cost of care, which is more challenging to do with civilian providers; and (4) Improve VHA infrastructure by, for example, upgrading technology and attracting the best clinicians and staff to support “our VHA.”

Participants who were in favor of allocating more funds toward the buy policy also offered a range of rationales, saying that it would (1) decrease patient burden by increasing access through community providers, decreasing wait time, and lessening personal cost and travel time; (2) allow more patients to receive civilian care, which was generally seen as beneficial by a few participants because of perceptions that the VHA provides lower quality care due to a shortage of VHA providers, run-down/older facilities, lack of technology, and poorer-quality VHA providers; and (3) provide an opportunity to divest of costly facilities and invest in other innovative approaches. Regarding this last reason, a few participants felt that the VHA is “gouged” when building medical centers that overrun budgets. They also were concerned that investing in facilities tied VHA to specific locations when current locations of veterans may change “25 years from now.”

 

Survey Results

Twenty-three of the 24 participants completed both pre- and postsession surveys. The majority of participants in the session felt people in the group respected their opinion (96%); felt that the facilitator did not try to influence the group with her own opinions (96%); indicated they understood the information enough to participate as much as they wanted (100%); and were hopeful that their reasoning and recommendations would help inform VHA policy makers (82%).

The surveys also provided an opportunity to examine the extent to which knowledge, attitudes, and opinions changed from before to after the deliberation. Even with the small sample, responses revealed a trend toward improved knowledge about key elements of the Choice Act and its goals. Further, there was a shift in some participants’ opinions about how patients should be prioritized to receive civilian care. For example, before the deliberation participants generally felt that all veterans should be able to receive civilian care, whereas postdeliberation this was not the case. Postdeliberation, most participants felt that primary care should not be a high priority for civilian care but continued to endorse prioritizing civilian care for specialty services like orthopedic or cardiology-related care. Finally, participants moved from more diverse recommendations regarding additional funds allocations, toward consensus after the deliberation around allocating funds to the build policy. Eight participants supported a build policy beforehand, whereas 16 supported this policy afterward.

Discussion

This study explored DD as a method for deeply engaging veterans in complex policy making to guide funding allocation and prioritization decisions related to the Choice Act, decisions that are still very relevant today within the context of the Mission Act and have substantial implications for how health care is delivered in the VHA. The Mission Act passed on June 6, 2018, with the goal of improving access to and the reliability of civilian or community care for eligible veterans.²⁷ Decisions related to appropriating scarce funding to improve access to care is an emotional and value-laden topic that elicited strong and divergent opinions among the participants. Veterans were eager to have their voices heard and had strong expectations that VHA leadership would be briefed about their recommendations. The majority of participants were satisfied with the deliberation process, felt they understood the issues, and felt their opinions were respected. They expressed feelings of comradery and community throughout the process.

In this single deliberation session, the groups did not achieve a single, final consensus regarding how VHA funding should ultimately be allocated between buy and build policy options. Nonetheless, participants provided a rich array of recommendations and rationale for them. Session moderators observed rich, sophisticated, fair, and reason-based discussions on this complex topic. Participants left with a deeper knowledge and appreciation for the complex trade-offs and expressed strong rationales for both sides of the policy debate on build vs buy. In addition, the project yielded results of high interest to VHA policy makers.

This work was presented in multiple venues between 2015 to 2016, and to both local and national VHA leadership, including the local Executive Quality Leadership Boards, the VHA Central Office Committee on the Future State of VA Community Care, the VA Office of Patient Centered Care, and the National Veteran Experience Committee. Through these discussions and others, we saw great interest within the VHA system and high-level leaders to explore ways to include veterans’ voices in the policy-making process. This work was invaluable to our research team (eAppendix E 

Document

fp-37-01-24_eappendix_e.pdf

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 ), has influenced the methodology of multiple research grants within the VA that seek to engage veterans in the research process, and played a pivotal role in the development of the Veteran Experience Office.

Many health system decisions regarding what care should be delivered (and how) involve making difficult, value-laden choices in the context of limited resources. DD methods can be used to target and obtain specific viewpoints from diverse populations, such as the informed perspectives of minority and underrepresented populations within the VHA.¹⁹ For example, female veterans were oversampled to ensure that the informed preferences of this population was obtained. Thus, DD methods could provide a valuable tool for health systems to elicit in-depth diverse patient input on high-profile policies that will have a substantial impact on the system’s patient population.

 

Limitations

One potential downside of DD is that, because of the resource-intensive nature of deliberation sessions, they are often conducted with relatively small groups.⁹ Viewpoints of those within these small samples who are willing to spend an entire day discussing a complex topic may not be representative of the larger patient community. However, the core goal of DD is diversity of opinions rather than representativeness.

A stratified random sampling strategy that oversampled for underrepresented and minority populations was used to help select a diverse group that represents the population on key characteristics and partially addresses concern about representativeness. Efforts to optimize participation rates, including providing monetary incentives, also are helpful and have led to high participation rates in past deliberations.⁷

Health system communication strategies that promote the importance of becoming involved in DD sessions also may be helpful in improving rates of recruitment. On particularly important topics where health system leaders feel a larger resource investment is justified, conducting larger scale deliberations with many small groups may obtain more generalizable evidence about what individual patients and groups of patients recommend.⁷ However, due to the inherent limitations of surveys and focus group approaches for obtaining informed views on complex topics, there are no clear systematic alternatives to the DD approach.

Conclusion

DD is an effective method to meaningfully engage patients in deep deliberations to guide complex policy making. Although design of deliberative sessions is resource-intensive, patient engagement efforts, such as those described in this paper, could be an important aspect of a well-functioning learning health system. Further research into alternative, streamlined methods that can also engage veterans more deeply is needed. DD also can be combined with other approaches to broaden and confirm findings, including focus groups, town hall meetings, or surveys.

Although this study did not provide consensus on how the VHA should allocate funds with respect to the Choice Act, it did provide insight into the importance and feasibility of engaging veterans in the policy-making process. As more policies aimed at improving veterans’ access to civilian care are created, such as the most recent Mission Act, policy makers should strongly consider using the DD method of obtaining informed veteran input into future policy decisions.

Acknowledgments
Funding was provided by the US Department of Veterans Affairs Office of Analytics and Business Intelligence (OABI) and the VA Quality Enhancement Research Initiative (QUERI). Dr. Caverly was supported in part by a VA Career Development Award (CDA 16-151). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). The authors thank the veterans who participated in this work. They also thank Caitlin Reardon and Natalya Wawrin for their assistance in organizing the deliberation session.

Providing high-quality, patient-centered health care is a top priority for the US Department of Veterans Affairs (VA) Veteran Health Administration (VHA), whose core mission is to improve the health and well-being of US veterans. Thus, news of long wait times for medical appointments in the VHA sparked intense national attention and debate and led to changes in senior management and legislative action. ¹ On August 8, 2014, President Bara c k Obama signed the Veterans Access, Choice, and Accountability Act of 2014, also known as the Choice Act, which provided an additional $16 billion in emergency spending over 3 years to improve veterans’ access to timely health care. ² The Choice Act sought to develop an integrated health care network that allowed qualified VHA patients to receive specific health care services in their communities delivered by non-VHA health care providers (HCPs) but paid for by the VHA. The Choice Act also laid out explicit criteria for how to prioritize who would be eligible for VHA-purchased civilian care: (1) veterans who could not get timely appointments at a VHA medical facility within 30 days of referral; or (2) veterans who lived > 40 miles from the closest VHA medical facility.

VHA decision makers seeking to improve care delivery also need to weigh trade-offs between alternative approaches to providing rapid access. For instance, increasing access to non-VHA HCPs may not always decrease wait times and could result in loss of continuity, limited care coordination, limited ability to ensure and enforce high-quality standards at the VHA, and other challenges.^3-6 Although the concerns and views of elected representatives, advocacy groups, and health system leaders are important, it is unknown whether these views and preferences align with those of veterans. Arguably, the range of views and concerns of informed veterans whose health is at stake should be particularly prominent in such policy decision making.

To identify the considerations that were most important to veterans regarding VHA policy around decreasing wait times, a study was designed to engage a group of veterans who were eligible for civilian care under the Choice Act. The study took place 1 year after the Choice Act was passed. Veterans were asked to focus on 2 related questions: First, how should funding be used for building VHA capacity (build) vs purchasing civilian care (buy)? Second, under what circumstances should civilian care be prioritized?

The aim of this paper is to describe democratic deliberation (DD), a specific method that engaged veteran patients in complex policy decisions around access to care. DD methods have been used increasingly in health care for developing policy guidance, setting priorities, providing advice on ethical dilemmas, weighing risk-benefit trade-offs, and determining decision-making authority.^7-12 For example, DD helped guide national policy for mammography screening for breast cancer in New Zealand.¹³ The Agency for Healthcare Research and Quality has completed a systematic review and a large, randomized experiment on best practices for carrying out public deliberation.^8,13,14 However, despite the potential value of this approach, there has been little use of deliberative methods within the VHA for the explicit purpose of informing veteran health care delivery.

This paper describes the experience engaging veterans by using DD methodology and informing VHA leadership about the results of those deliberations. The specific aims were to understand whether DD is an acceptable approach to use to engage patients in the medical services policy-making process within VHA and whether veterans are able to come to an informed consensus.

 

Methods

Engaging patients and incorporating their needs and concerns within the policy-making process may improve health system policies and make those policies more patient centered. Such engagement also could be a way to generate creative solutions. However, because health-system decisions often involve making difficult trade-offs, effectively obtaining patient population input on complex care delivery issues can be challenging.

Although surveys can provide intuitive, top-of-mind input from respondents, these opinions are generally not sufficient for resolving complex problems.¹⁵ Focus groups and interviews may produce results that are more in-depth than surveys, but these methods tend to elicit settled private preferences rather than opinions about what the community should do.¹⁶ DD, on the other hand, is designed to elicit deeply informed public opinions on complex, value-laden topics to develop recommendations and policies for a larger community.¹⁷ The goal is to find collective solutions to challenging social problems. DD achieves this by giving participants an opportunity to explore a topic in-depth, question experts, and engage peers in reason-based discussions.^18,19 This method has its roots in political science and has been used over several decades to successfully inform policy making on a broad array of topics nationally and internationally—from health research ethics in the US to nuclear and energy policy in Japan.^7,16,20,21 DD has been found to promote ownership of public programs and lend legitimacy to policy decisions, political institutions, and democracy itself.¹⁸

A single day (8 hours) DD session was convened, following a Citizens Jury model of deliberation, which brings veteran patients together to learn about a topic, ask questions of experts, deliberate with peers, and generate a “citizen’s report” that contains a set of recommendations (Table 1). An overview of the different models of DD and rationale for each can be found elsewhere.^8,15

Recruitment Considerations

A purposively selected sample of civilian care-eligible veterans from a midwestern VHA health care system (1 medical center and 3 community-based outpatient clinics [CBOCs]) were invited to the DD session. The targeted number of participants was 30. Female veterans, who comprise only 7% of the local veteran population, were oversampled to account for their potentially different health care needs and to create balance between males and females in the session. Oversampling for other characteristics was not possible due to the relatively small sample size. Based on prior experience,⁷ it was assumed that 70% of willing participants would attend the session; therefore 34 veterans were invited and 24 attended. Each participant received a $200 incentive in appreciation for their substantial time commitment and to offset transportation costs.

Background Materials

A packet with educational materials (Flesch-Kincaid Grade Level of 10.5) was mailed to participants about 2 weeks before the DD session. Participants were asked to review prior to attending the session. These materials described the session (eg, purpose, organizers, importance) and provided factual information about the Choice Act (eg, eligibility, out-of-pocket costs, travel pay, prescription drug policies).

Session Overview

The session was structured to accomplish the following goals: (1) Elicit participants’ opinions about access to health care and reasons for those opinions; (2) Provide in-depth education about the Choice Act through presentations and discussions with topical experts; and (3) Elicit reasoning and recommendations on both the criteria by which participants prioritize candidates for civilian care and how participants would allocate additional funding to improve access (ie, by building VHA capacity to deliver more timely health care vs purchasing health care from civilian HCPs).

 

Participants were asked to fill out a survey on arrival in the morning and were assigned to 1 of 3 tables or small groups. Each table had a facilitator who had extensive experience in qualitative data collection methods and guided the dialogue using a scripted protocol that they helped develop and refine. The facilitation materials drew from and used previously published studies.^22,23 Each facilitator audio recorded the sessions and took notes. Three experts presented during plenary education sessions. Presentations were designed to provide balanced factual information and included a veteran’s perspective. One presenter was a clinician on the project team, another was a local clinical leader responsible for making decisions about what services to provide via civilian care (buy) vs enhancing the local VHA health system’s ability to provide those services (build), and the third presenter was a veteran who was on the project team.

Education Session 1

The first plenary education session with expert presentations was conducted after each table completed an icebreaker exercise. The project team physician provided a brief history and description of the Choice Act to reinforce educational materials sent to participants prior to the session. The health system clinical leader described his decision process and principles and highlighted constraints placed on him by the Choice Act that were in place at the time of the DD session. He also described existing local and national programs to provide civilian care (eg, local fee-basis non-VHA care programs) and how these programs sought to achieve goals similar to the Choice Act. The veteran presenter focused on the importance of session participants providing candid insight and observations and emphasized that this session was a significant opportunity to “have their voices heard.”

Deliberation 1: What criteria should be used to prioritize patients for receiving civilian care paid for by the VHA? To elicit preferences on the central question of this deliberation, participants were presented with 8 real-world cases that were based on interviews conducted with Choice Act-eligible veterans (Table 2 and eAppendices A

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, B 

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,  C 

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 , and D 

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 ). Participants were first instructed to read through and discuss the cases as a group, then come to agreement on prioritizing how the patients in the case scenarios should receive civilian care. Agreement was defined as having complete consensus or consensus by the majority, in which case, the facilitator noted the number who agreed and disagreed within each group. The facilitators documented the criteria each group considered as they prioritized the cases, along with the group’s reasoning behind their choices.

Education Session 2

In the second plenary session, the project team physician provided information about health care access issues, both inside and outside of the VHA, particularly between urban and rural areas. He also discussed factors related to the insufficient capacity to meet growing demand that contributed to the VHA wait-time crisis. The veteran presenter shared reflections on health care access from a veteran’s perspective.

Deliberation 2: How should additional funding be divided between increasing the ability of the VHA to (1) provide care by VHA HCPs; and (2) pay for care from non-VHA civilian HCPs? Participants were presented the patient examples and Choice Act funding scenarios (the buy policy option) and contrasted that with a build policy option. Participants were explicitly encouraged to shift their perspectives from thinking about individual cases to considering policy-level decisions and the broader social good (Table 2).

 

Ensuring Robust Deliberations

If participants do not adequately grasp the complexities of the topic, a deliberation can fail. To facilitate nuanced reasoning, real-world concrete examples were developed as the starting point of each deliberation based on interviews with actual patients (deliberation 1) and actual policy proposals relevant to the funding allocation decisions within the Choice Act (deliberation 2).

A deliberation also can fail with self-silencing, where participants withhold opinions that differ from those articulated first or by more vocal members of the group.²⁴ To combat self-silencing, highly experienced facilitators were used to ensure sharing from all participants and to support an open-minded, courteous, and reason-based environment for discourse. It was specified that the best solutions are achieved through reason-based and cordial disagreement and that success can be undermined when participants simply agree because it is easier or more comfortable.

A third way a deliberation can fail is if individuals do not adopt a group or system-level perspective. To counter this, facilitators reinforced at multiple points the importance of taking a broader social perspective rather than sharing only one’s personal preferences.

Finally, it is important to assess the quality of the deliberative process itself, to ensure that results are trustworthy.²⁵ To assess the quality of the deliberative process, participants knowledge about key issues pre- and postdeliberation were assessed. Participants also were asked to rate the quality of the facilitators and how well they felt their voice was heard and respected, and facilitators made qualitative assessments about the extent to which participants were engaged in reason-based and collaborative discussion.

Data

Quantitative data were collected via pre- and postsession surveys. The surveys contained items related to knowledge about the Choice Act, expectations for the DD session, beliefs and opinions about the provision of health care for veterans, recommended funding allocations between build vs buy policy options, and general demographics. Qualitative data were collected through detailed notes taken by the 3 facilitators. Each table’s deliberations were audio recorded so that gaps in the notes could be filled.

The 3 facilitators, who were all experienced qualitative researchers, typed their written notes into a template immediately after the session. Two of the 3 facilitators led the analysis of the session notes. Findings within and across the 3 deliberation tables were developed using content and matrix analysis methods.²⁶ Descriptive statistics were generated from survey responses and compared survey items pre- and postsession using paired t tests or χ² tests for categorical responses.

Results

Thirty-three percent of individuals invited (n = 127) agreed to participate. Those who declined cited conflicts related to distance, transportation, work/school, medical appointments, family commitments, or were not interested. In all, 24 (69%) of the 35 veterans who accepted the invitation attended the deliberation session. Of the 11 who accepted but did not attend, 5 cancelled ahead of time because of conflicts (Figure). Most participants were male (70%), 48% were aged 61 to 75 years, 65% were white, 43% had some college education, 43% reported an annual income of between $25,000 and $40,000, and only 35% reported very good health (eAppendix D).

 

Deliberation 1

During the deliberation on the prioritization criteria, the concept of “condition severity” emerged as an important criterion for veterans. This criterion captured simultaneous consideration of both clinical necessity and burden on the veteran to obtain care. For example, participants felt that patients with a life-threatening illness should be prioritized for civilian care over patients who need preventative or primary care (clinical necessity) and that elderly patients with substantial difficulty traveling to VHA appointments should be prioritized over patients who can travel more easily (burden). The Choice Act regulations at the time of the DD session did not reflect this nuanced perspective, stipulating only that veterans must live > 40 miles from the nearest VHA medical facility.

One of the 3 groups did not prioritize the patient cases because some members felt that no veteran should be constrained from receiving civilian care if they desired it. Nonetheless, this group did agree with prioritizing the first 2 cases in Table 3. The other groups prioritized all 8 cases in generally similar ways.

Deliberation 2

No clear consensus emerged on the buy vs build question. A representative from each table presented their group’s positions, rationale, and recommendations after deliberations were completed. After hearing the range of positions, the groups then had another opportunity to deliberate based on what they heard from the other tables; no new recommendations or consensus emerged.

Participants who were in favor of allocating more funds toward the build policy offered a range of rationales, saying that it would (1) increase access for rural veterans by building CBOCs and deploying more mobile units that could bring outlets for health care closer to their home communities; (2) provide critical and unique medical expertise to address veteran-specific issues such as prosthetics, traumatic brain injury, posttraumatic stress disorder, spinal cord injury, and shrapnel wounds that are typically not available through civilian providers; (3) give VHA more oversight over the quality and cost of care, which is more challenging to do with civilian providers; and (4) Improve VHA infrastructure by, for example, upgrading technology and attracting the best clinicians and staff to support “our VHA.”

Participants who were in favor of allocating more funds toward the buy policy also offered a range of rationales, saying that it would (1) decrease patient burden by increasing access through community providers, decreasing wait time, and lessening personal cost and travel time; (2) allow more patients to receive civilian care, which was generally seen as beneficial by a few participants because of perceptions that the VHA provides lower quality care due to a shortage of VHA providers, run-down/older facilities, lack of technology, and poorer-quality VHA providers; and (3) provide an opportunity to divest of costly facilities and invest in other innovative approaches. Regarding this last reason, a few participants felt that the VHA is “gouged” when building medical centers that overrun budgets. They also were concerned that investing in facilities tied VHA to specific locations when current locations of veterans may change “25 years from now.”

 

Survey Results

Twenty-three of the 24 participants completed both pre- and postsession surveys. The majority of participants in the session felt people in the group respected their opinion (96%); felt that the facilitator did not try to influence the group with her own opinions (96%); indicated they understood the information enough to participate as much as they wanted (100%); and were hopeful that their reasoning and recommendations would help inform VHA policy makers (82%).

The surveys also provided an opportunity to examine the extent to which knowledge, attitudes, and opinions changed from before to after the deliberation. Even with the small sample, responses revealed a trend toward improved knowledge about key elements of the Choice Act and its goals. Further, there was a shift in some participants’ opinions about how patients should be prioritized to receive civilian care. For example, before the deliberation participants generally felt that all veterans should be able to receive civilian care, whereas postdeliberation this was not the case. Postdeliberation, most participants felt that primary care should not be a high priority for civilian care but continued to endorse prioritizing civilian care for specialty services like orthopedic or cardiology-related care. Finally, participants moved from more diverse recommendations regarding additional funds allocations, toward consensus after the deliberation around allocating funds to the build policy. Eight participants supported a build policy beforehand, whereas 16 supported this policy afterward.

Discussion

This study explored DD as a method for deeply engaging veterans in complex policy making to guide funding allocation and prioritization decisions related to the Choice Act, decisions that are still very relevant today within the context of the Mission Act and have substantial implications for how health care is delivered in the VHA. The Mission Act passed on June 6, 2018, with the goal of improving access to and the reliability of civilian or community care for eligible veterans.²⁷ Decisions related to appropriating scarce funding to improve access to care is an emotional and value-laden topic that elicited strong and divergent opinions among the participants. Veterans were eager to have their voices heard and had strong expectations that VHA leadership would be briefed about their recommendations. The majority of participants were satisfied with the deliberation process, felt they understood the issues, and felt their opinions were respected. They expressed feelings of comradery and community throughout the process.

In this single deliberation session, the groups did not achieve a single, final consensus regarding how VHA funding should ultimately be allocated between buy and build policy options. Nonetheless, participants provided a rich array of recommendations and rationale for them. Session moderators observed rich, sophisticated, fair, and reason-based discussions on this complex topic. Participants left with a deeper knowledge and appreciation for the complex trade-offs and expressed strong rationales for both sides of the policy debate on build vs buy. In addition, the project yielded results of high interest to VHA policy makers.

This work was presented in multiple venues between 2015 to 2016, and to both local and national VHA leadership, including the local Executive Quality Leadership Boards, the VHA Central Office Committee on the Future State of VA Community Care, the VA Office of Patient Centered Care, and the National Veteran Experience Committee. Through these discussions and others, we saw great interest within the VHA system and high-level leaders to explore ways to include veterans’ voices in the policy-making process. This work was invaluable to our research team (eAppendix E 

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 ), has influenced the methodology of multiple research grants within the VA that seek to engage veterans in the research process, and played a pivotal role in the development of the Veteran Experience Office.

Many health system decisions regarding what care should be delivered (and how) involve making difficult, value-laden choices in the context of limited resources. DD methods can be used to target and obtain specific viewpoints from diverse populations, such as the informed perspectives of minority and underrepresented populations within the VHA.¹⁹ For example, female veterans were oversampled to ensure that the informed preferences of this population was obtained. Thus, DD methods could provide a valuable tool for health systems to elicit in-depth diverse patient input on high-profile policies that will have a substantial impact on the system’s patient population.

 

Limitations

One potential downside of DD is that, because of the resource-intensive nature of deliberation sessions, they are often conducted with relatively small groups.⁹ Viewpoints of those within these small samples who are willing to spend an entire day discussing a complex topic may not be representative of the larger patient community. However, the core goal of DD is diversity of opinions rather than representativeness.

A stratified random sampling strategy that oversampled for underrepresented and minority populations was used to help select a diverse group that represents the population on key characteristics and partially addresses concern about representativeness. Efforts to optimize participation rates, including providing monetary incentives, also are helpful and have led to high participation rates in past deliberations.⁷

Health system communication strategies that promote the importance of becoming involved in DD sessions also may be helpful in improving rates of recruitment. On particularly important topics where health system leaders feel a larger resource investment is justified, conducting larger scale deliberations with many small groups may obtain more generalizable evidence about what individual patients and groups of patients recommend.⁷ However, due to the inherent limitations of surveys and focus group approaches for obtaining informed views on complex topics, there are no clear systematic alternatives to the DD approach.

Conclusion

DD is an effective method to meaningfully engage patients in deep deliberations to guide complex policy making. Although design of deliberative sessions is resource-intensive, patient engagement efforts, such as those described in this paper, could be an important aspect of a well-functioning learning health system. Further research into alternative, streamlined methods that can also engage veterans more deeply is needed. DD also can be combined with other approaches to broaden and confirm findings, including focus groups, town hall meetings, or surveys.

Although this study did not provide consensus on how the VHA should allocate funds with respect to the Choice Act, it did provide insight into the importance and feasibility of engaging veterans in the policy-making process. As more policies aimed at improving veterans’ access to civilian care are created, such as the most recent Mission Act, policy makers should strongly consider using the DD method of obtaining informed veteran input into future policy decisions.

Acknowledgments
Funding was provided by the US Department of Veterans Affairs Office of Analytics and Business Intelligence (OABI) and the VA Quality Enhancement Research Initiative (QUERI). Dr. Caverly was supported in part by a VA Career Development Award (CDA 16-151). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). The authors thank the veterans who participated in this work. They also thank Caitlin Reardon and Natalya Wawrin for their assistance in organizing the deliberation session.

Nearly 1 in 8 households—and 1 in 6 households with children—experienced food insecurity in 2017, defined as limited or uncertain availability of nutritionally adequate and safe foods.¹ Food insecurity is often even more pronounced among households with individuals with acute or chronic medical conditions.^2-6 Moreover, food insecurity is independently associated with a range of adverse health outcomes, including poorer control of diabetes mellitus, hypertension, depression and other major psychiatric disorders, HIV, and chronic lung and kidney disease, as well as poorer overall health status.^7-14 Food insecurity also has been associated with increased health care costs and acute care utilization as well as increased probability of delayed or missed care.^15-19

The relationship between food insecurity and poor health outcomes is a complex and often cyclic phenomenon (Figure 1). Poor nutritional status is fueled by limited access to healthful foods as well as increased reliance on calorie-dense and nutrient-poor “junk” foods, which are less expensive and often more readily available in low-income neighborhoods.^5,20-24 These compensatory dietary patterns place individuals at higher risk for developing cardiometabolic conditions and for poor control of these conditions.^{5,8,9,12,25,26} Additionally, the physiological and psychological stressors of food insecurity may precipitate depression and anxiety or worsen existing mental health conditions, resulting in feelings of overwhelm and decreased self-management capacity.^5,8,27-31 Food insecurity has further been associated with poor sleep, declines in cognitive function, and increased falls, particularly among the frail and elderly.^32-34

Individuals experiencing food insecurity often report having to make trade-offs between food and other necessities, such as paying rent or utilities. Additional strategies to stretch limited resources include cost-related underuse of medication and delays in needed medical care.^4,17,31,35 In a nationally representative survey among adults with at least 1 chronic medical condition, 1 in 3 reported having to choose between food and medicine; 11% were unable to afford either.³ Furthermore, the inability to reliably adhere to medication regimens that need to be taken with food can result in potentially life-threatening hypoglycemia (as can lack of food regardless of medication use).^5,26,36 In addition to the more obvious risks of glucose-lowering medications, such as insulin and long-acting sulfonylureas in patients experiencing food insecurity, many drugs commonly used among nondiabetic adults such as ACE-inhibitors, β blockers, quinolones, and salicylates can also precipitate hypoglycemia, and food insecurity has been associated with experiences of hypoglycemia even among individuals without diabetes mellitus.^32,37 In one study the risk for hospital admissions for hypoglycemia among low-income populations increased by 27% at the end of the month when food budgets were more likely to be exhausted.³⁸ Worsening health status and increased emergency department visits and hospitalizations may then result in lost wages and mounting medical bills, contributing to further financial strain and worsening food insecurity.

Prevalence and Importance of Food Insecurity Among US Veterans

Nearly 1.5 million veterans in the US are living below the federal poverty level (FPL).³⁹ An additional 2.4 million veterans are living paycheck to paycheck at < 200% of the FPL.⁴⁰ Veterans living in poverty are at even higher risk than nonveterans for food insecurity, homelessness, and other material hardship.⁴¹

 

Estimates of food insecurity among veterans vary widely, ranging from 6% to 24%—nearly twice that of the general US population.^8,42-45 Higher rates of food insecurity have been reported among certain high-risk subgroups, including veterans who served in Iraq and Afghanistan (27%), female veterans (28%), homeless and formerly homeless veterans (49%), and veterans with serious mental illness (35%).^6,32,43,46 Additional risk factors for food insecurity specific to veteran populations include younger age, having recently left active-duty military service, and lower final military paygrade.^42,45-47 As in the general population, veteran food insecurity is associated with a range of adverse health outcomes, including poorer overall health status as well as increased probability of delayed or missed care.^{6,8,32,42-44,46}

Even among veterans enrolled in federal food assistance programs, many still struggle to afford nutritionally adequate foods. As one example, in a study of mostly male homeless and formerly homeless veterans, O’Toole and colleagues found that nearly half of those reporting food insecurity were already receiving federal food assistance benefits, and 22% relied on emergency food resources.³² Of households served by Feeding America food pantries and meal programs, 20% have a member who has served in the US military.⁴⁸

Federal Programs To Address Food Insecurity

There are several important federal food assistance programs designed to help alleviate food insecurity. The Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp program) is the largest federal food assistance program and provides low-income Americans with cash benefits to purchase food. SNAP has been shown to substantially reduce food insecurity.^7,49 The program also is associated with significant decreases in cost-related medication nonadherence as well as reductions in health care costs and both acute care and nursing home utilization.^16,50-54 Although nearly 1.4 million veterans live in SNAP-enrolled households, 59% of eligible veterans are not enrolled.^43,55 Closing this SNAP eligibility-enrollment gap, has been a focus of recent efforts to improve long-term food security among veterans. There also are several federal food assistance programs for households with children, including the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and school meals programs. Among federal nutrition programs for seniors, the Older American’s Act contains designated funding to support nutrition services for older adults, including congregate meal programs in community settings like senior centers, places of worship, and housing communities, and home-delivered meals through programs like Meals on Wheels.⁵⁶

VHA Response to Food Insecurity

The Veterans Health Administration (VHA) is the country’s largest integrated, federally funded health care system.⁵⁷ In November 2015, congressional briefings on veteran food insecurity organized by the national non-profit organization MAZON: A Jewish Response to Hunger and hosted with bipartisan support were provided to the US House and Senate. As a result of these briefings, VHA chartered the national Ensuring Veteran Food Security Workgroup with a mandate to partner with governmental and nonprofit agencies to “focus on the issue of food insecurity, the identification of veterans at risk, the needed training of VHA staff and the coordination of resources and initiatives to support the veterans for whom we care.” Building off a pilot in US Department of Veterans Affairs (VA) Homeless Patient Aligned Care Teams (H-PACTs),³² VHA subsequently integrated a single-item food insecurity screening tool into the VA electronic health record (EHR) clinical reminder system (Figure 2). The clinical reminder, which was rolled out across VA medical centers nationally in October 2017, provides an alert to screen all noninstitutionalized veterans for food insecurity. To date, nearly 5 million veterans have been screened. When a veteran endorses food insecurity based on the initial screening question, a prompt appears to offer the veteran a referral to a social worker and/or dietitian. Positive screening results also should be communicated to the patient’s primary care provider. Depending on site-specific clinical flow, the reminders are typically completed in the outpatient setting either by nurses or medical assistants during intake or by providers as part of the clinical visit. However, any member of the health care team can complete the clinical reminder at any time. As of September 2019, approximately 74,000 veterans have been identified as food insecure.⁵⁸

 

Addressing Food Insecurity

VHA has been a recognized leader in addressing homelessness and other social determinants of health through its integrated care and PACT delivery models.^59-61 The food insecurity clinical reminder was designed to facilitate a tailored, interdisciplinary approach to identify and address food insecurity. Interdisciplinary care team members—including medical assistants, clinicians, social workers, registered dietitians, nurse care managers, occupational or physical therapists, and pharmacists—are uniquely positioned to identify veterans impacted by food insecurity, assess for associated clinical and/or social risk factors, and offer appropriate medical and nutrition interventions and resource referrals.

This interdisciplinary team-based model is essential given the range of potential drivers underlying veteran experiences of food insecurity and subsequent health outcomes. It is critically important for clinicians to review the medication list with veterans screening positive for food insecurity to assess for risk of hypoglycemia and/or cost-related nonadherence, make any necessary adjustments to therapeutic regimens, and assess for additional risk factors associated with food insecurity. Examples of tailored nutrition counseling that clinical dietitians may provide include meal preparation strategies for veterans who only have access to a microwave or hotplate, or recommendations for how veterans on medically restricted diets can best navigate food selection at soup kitchens or food pantries. Resource referrals provided by social workers or other care team members may include both emergency food resources to address immediate shortages (eg, food pantries, soup kitchens, or vouchers for free lunch) as well as resources focused on improving longer term food security (eg, federal food assistance programs or home delivered meal programs). Importantly, although providing a list of food resources may be helpful for some patients, such lists are often insufficient.^62,63 Many patients require active assistance with program enrollment either onsite the day of their clinic visit or through connection with a partnering community-based organization that can, in turn, identify appropriate resources and facilitate program enrollment.^63,64 Planned follow-up is also crucial to determine whether referrals are successful and to assess for ongoing need. Proposed roles for interdisciplinary care team members in addressing a positive food insecurity screen are outlined in Table 1.

VHA-Community Partnerships

In addition to services offered within VA, public and private sector partnerships can greatly enhance the range of resources available to food insecure veterans. Several VA facilities have developed formal community partnerships, such as the Veterans Pantry Pilot (VPP) program, a national partnership between Feeding America food banks and VA medical centers to establish onsite or mobile food pantries. There are currently 17 active Feeding America VPP sites, with a number of additional sites under development. Several of the VPP sites also include other “wraparound services,” such as SNAP application assistance.^65,66

State Veterans Affairs offices⁶⁷ and Veterans Service Organizations (VSOs)⁶⁸ also can serve as valuable partners for connecting veterans with needed resources. VSOs offer a range of services, including assistancewith benefit claims, employment and housing assistance, emergency food assistance, and transportation to medical appointments. Some VSOs also have established local affiliations with Meals on Wheels focused on veteran outreach and providing hot meals for low-income, homebound, and disabled veterans.

 

Additional Resources

Although resources vary by regional setting, several key governmental and community-based food assistance programs are summarized in Table 2. Local community partners and online/phone-based directories, such as United Way’s 2-1-1 can help identify additional local resources. For older adults and individuals with disabilities, local Aging and Disability Resources Centers can provide information and assistance connecting to needed resources.⁶⁹ Finally, there are a number of online resources available for clinicians interested in learning more about the impact of food insecurity on health and tools to use in the clinical setting (Table 3).

Conclusion

The VA has recognized food insecurity as a critical concern for the well-being of our nation’s veterans. Use of the EHR clinical reminder represents a crucial first step toward increasing provider awareness about veteran food insecurity and improving clinical efforts to address food insecurity once identified. Through the reminder, health care teams can connect veterans to needed resources and create both the individual and population-level data necessary to inform VHA and community efforts to address veteran food insecurity. Clinical reminder data are currently being used for local quality improvement efforts and have established the need nationally for formalized partnerships between VHA Social Work Services and Nutrition and Food Services to connect veterans with food and provide them with strategies to best use available food resources.

Moving forward, the Ensuring Veteran Food Security Workgroup continues to work with agencies and organizations across the country to improve food insecure veterans’ access to needed services. In addition to existing VA partnerships with Feeding America for the VPP, memorandums of understanding are currently underway to formalize partnerships with both the Food Research and Action Center (FRAC) and MAZON. Additional research is needed both to formally validate the current food insecurity clinical reminder screening question and to identify best practices and potential models for how to most effectively use VHA-community partnerships to address the unique needs of the veteran population.

Ensuring the food security of our nation’s veterans is essential to VA’s commitment to providing integrated, veteran-centered, whole person care. Toward that goal, VA health care teams are urged to use the clinical reminder and help connect food insecure veterans with relevant resources both within and outside of the VA health care system.

Nearly 1 in 8 households—and 1 in 6 households with children—experienced food insecurity in 2017, defined as limited or uncertain availability of nutritionally adequate and safe foods.¹ Food insecurity is often even more pronounced among households with individuals with acute or chronic medical conditions.^2-6 Moreover, food insecurity is independently associated with a range of adverse health outcomes, including poorer control of diabetes mellitus, hypertension, depression and other major psychiatric disorders, HIV, and chronic lung and kidney disease, as well as poorer overall health status.^7-14 Food insecurity also has been associated with increased health care costs and acute care utilization as well as increased probability of delayed or missed care.^15-19

The relationship between food insecurity and poor health outcomes is a complex and often cyclic phenomenon (Figure 1). Poor nutritional status is fueled by limited access to healthful foods as well as increased reliance on calorie-dense and nutrient-poor “junk” foods, which are less expensive and often more readily available in low-income neighborhoods.^5,20-24 These compensatory dietary patterns place individuals at higher risk for developing cardiometabolic conditions and for poor control of these conditions.^{5,8,9,12,25,26} Additionally, the physiological and psychological stressors of food insecurity may precipitate depression and anxiety or worsen existing mental health conditions, resulting in feelings of overwhelm and decreased self-management capacity.^5,8,27-31 Food insecurity has further been associated with poor sleep, declines in cognitive function, and increased falls, particularly among the frail and elderly.^32-34

Individuals experiencing food insecurity often report having to make trade-offs between food and other necessities, such as paying rent or utilities. Additional strategies to stretch limited resources include cost-related underuse of medication and delays in needed medical care.^4,17,31,35 In a nationally representative survey among adults with at least 1 chronic medical condition, 1 in 3 reported having to choose between food and medicine; 11% were unable to afford either.³ Furthermore, the inability to reliably adhere to medication regimens that need to be taken with food can result in potentially life-threatening hypoglycemia (as can lack of food regardless of medication use).^5,26,36 In addition to the more obvious risks of glucose-lowering medications, such as insulin and long-acting sulfonylureas in patients experiencing food insecurity, many drugs commonly used among nondiabetic adults such as ACE-inhibitors, β blockers, quinolones, and salicylates can also precipitate hypoglycemia, and food insecurity has been associated with experiences of hypoglycemia even among individuals without diabetes mellitus.^32,37 In one study the risk for hospital admissions for hypoglycemia among low-income populations increased by 27% at the end of the month when food budgets were more likely to be exhausted.³⁸ Worsening health status and increased emergency department visits and hospitalizations may then result in lost wages and mounting medical bills, contributing to further financial strain and worsening food insecurity.

Prevalence and Importance of Food Insecurity Among US Veterans

Nearly 1.5 million veterans in the US are living below the federal poverty level (FPL).³⁹ An additional 2.4 million veterans are living paycheck to paycheck at < 200% of the FPL.⁴⁰ Veterans living in poverty are at even higher risk than nonveterans for food insecurity, homelessness, and other material hardship.⁴¹

 

Estimates of food insecurity among veterans vary widely, ranging from 6% to 24%—nearly twice that of the general US population.^8,42-45 Higher rates of food insecurity have been reported among certain high-risk subgroups, including veterans who served in Iraq and Afghanistan (27%), female veterans (28%), homeless and formerly homeless veterans (49%), and veterans with serious mental illness (35%).^6,32,43,46 Additional risk factors for food insecurity specific to veteran populations include younger age, having recently left active-duty military service, and lower final military paygrade.^42,45-47 As in the general population, veteran food insecurity is associated with a range of adverse health outcomes, including poorer overall health status as well as increased probability of delayed or missed care.^{6,8,32,42-44,46}

Even among veterans enrolled in federal food assistance programs, many still struggle to afford nutritionally adequate foods. As one example, in a study of mostly male homeless and formerly homeless veterans, O’Toole and colleagues found that nearly half of those reporting food insecurity were already receiving federal food assistance benefits, and 22% relied on emergency food resources.³² Of households served by Feeding America food pantries and meal programs, 20% have a member who has served in the US military.⁴⁸

Federal Programs To Address Food Insecurity

There are several important federal food assistance programs designed to help alleviate food insecurity. The Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp program) is the largest federal food assistance program and provides low-income Americans with cash benefits to purchase food. SNAP has been shown to substantially reduce food insecurity.^7,49 The program also is associated with significant decreases in cost-related medication nonadherence as well as reductions in health care costs and both acute care and nursing home utilization.^16,50-54 Although nearly 1.4 million veterans live in SNAP-enrolled households, 59% of eligible veterans are not enrolled.^43,55 Closing this SNAP eligibility-enrollment gap, has been a focus of recent efforts to improve long-term food security among veterans. There also are several federal food assistance programs for households with children, including the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and school meals programs. Among federal nutrition programs for seniors, the Older American’s Act contains designated funding to support nutrition services for older adults, including congregate meal programs in community settings like senior centers, places of worship, and housing communities, and home-delivered meals through programs like Meals on Wheels.⁵⁶

VHA Response to Food Insecurity

The Veterans Health Administration (VHA) is the country’s largest integrated, federally funded health care system.⁵⁷ In November 2015, congressional briefings on veteran food insecurity organized by the national non-profit organization MAZON: A Jewish Response to Hunger and hosted with bipartisan support were provided to the US House and Senate. As a result of these briefings, VHA chartered the national Ensuring Veteran Food Security Workgroup with a mandate to partner with governmental and nonprofit agencies to “focus on the issue of food insecurity, the identification of veterans at risk, the needed training of VHA staff and the coordination of resources and initiatives to support the veterans for whom we care.” Building off a pilot in US Department of Veterans Affairs (VA) Homeless Patient Aligned Care Teams (H-PACTs),³² VHA subsequently integrated a single-item food insecurity screening tool into the VA electronic health record (EHR) clinical reminder system (Figure 2). The clinical reminder, which was rolled out across VA medical centers nationally in October 2017, provides an alert to screen all noninstitutionalized veterans for food insecurity. To date, nearly 5 million veterans have been screened. When a veteran endorses food insecurity based on the initial screening question, a prompt appears to offer the veteran a referral to a social worker and/or dietitian. Positive screening results also should be communicated to the patient’s primary care provider. Depending on site-specific clinical flow, the reminders are typically completed in the outpatient setting either by nurses or medical assistants during intake or by providers as part of the clinical visit. However, any member of the health care team can complete the clinical reminder at any time. As of September 2019, approximately 74,000 veterans have been identified as food insecure.⁵⁸

 

Addressing Food Insecurity

VHA has been a recognized leader in addressing homelessness and other social determinants of health through its integrated care and PACT delivery models.^59-61 The food insecurity clinical reminder was designed to facilitate a tailored, interdisciplinary approach to identify and address food insecurity. Interdisciplinary care team members—including medical assistants, clinicians, social workers, registered dietitians, nurse care managers, occupational or physical therapists, and pharmacists—are uniquely positioned to identify veterans impacted by food insecurity, assess for associated clinical and/or social risk factors, and offer appropriate medical and nutrition interventions and resource referrals.

This interdisciplinary team-based model is essential given the range of potential drivers underlying veteran experiences of food insecurity and subsequent health outcomes. It is critically important for clinicians to review the medication list with veterans screening positive for food insecurity to assess for risk of hypoglycemia and/or cost-related nonadherence, make any necessary adjustments to therapeutic regimens, and assess for additional risk factors associated with food insecurity. Examples of tailored nutrition counseling that clinical dietitians may provide include meal preparation strategies for veterans who only have access to a microwave or hotplate, or recommendations for how veterans on medically restricted diets can best navigate food selection at soup kitchens or food pantries. Resource referrals provided by social workers or other care team members may include both emergency food resources to address immediate shortages (eg, food pantries, soup kitchens, or vouchers for free lunch) as well as resources focused on improving longer term food security (eg, federal food assistance programs or home delivered meal programs). Importantly, although providing a list of food resources may be helpful for some patients, such lists are often insufficient.^62,63 Many patients require active assistance with program enrollment either onsite the day of their clinic visit or through connection with a partnering community-based organization that can, in turn, identify appropriate resources and facilitate program enrollment.^63,64 Planned follow-up is also crucial to determine whether referrals are successful and to assess for ongoing need. Proposed roles for interdisciplinary care team members in addressing a positive food insecurity screen are outlined in Table 1.

VHA-Community Partnerships

In addition to services offered within VA, public and private sector partnerships can greatly enhance the range of resources available to food insecure veterans. Several VA facilities have developed formal community partnerships, such as the Veterans Pantry Pilot (VPP) program, a national partnership between Feeding America food banks and VA medical centers to establish onsite or mobile food pantries. There are currently 17 active Feeding America VPP sites, with a number of additional sites under development. Several of the VPP sites also include other “wraparound services,” such as SNAP application assistance.^65,66

State Veterans Affairs offices⁶⁷ and Veterans Service Organizations (VSOs)⁶⁸ also can serve as valuable partners for connecting veterans with needed resources. VSOs offer a range of services, including assistancewith benefit claims, employment and housing assistance, emergency food assistance, and transportation to medical appointments. Some VSOs also have established local affiliations with Meals on Wheels focused on veteran outreach and providing hot meals for low-income, homebound, and disabled veterans.

 

Additional Resources

Although resources vary by regional setting, several key governmental and community-based food assistance programs are summarized in Table 2. Local community partners and online/phone-based directories, such as United Way’s 2-1-1 can help identify additional local resources. For older adults and individuals with disabilities, local Aging and Disability Resources Centers can provide information and assistance connecting to needed resources.⁶⁹ Finally, there are a number of online resources available for clinicians interested in learning more about the impact of food insecurity on health and tools to use in the clinical setting (Table 3).

Conclusion

The VA has recognized food insecurity as a critical concern for the well-being of our nation’s veterans. Use of the EHR clinical reminder represents a crucial first step toward increasing provider awareness about veteran food insecurity and improving clinical efforts to address food insecurity once identified. Through the reminder, health care teams can connect veterans to needed resources and create both the individual and population-level data necessary to inform VHA and community efforts to address veteran food insecurity. Clinical reminder data are currently being used for local quality improvement efforts and have established the need nationally for formalized partnerships between VHA Social Work Services and Nutrition and Food Services to connect veterans with food and provide them with strategies to best use available food resources.

Moving forward, the Ensuring Veteran Food Security Workgroup continues to work with agencies and organizations across the country to improve food insecure veterans’ access to needed services. In addition to existing VA partnerships with Feeding America for the VPP, memorandums of understanding are currently underway to formalize partnerships with both the Food Research and Action Center (FRAC) and MAZON. Additional research is needed both to formally validate the current food insecurity clinical reminder screening question and to identify best practices and potential models for how to most effectively use VHA-community partnerships to address the unique needs of the veteran population.

Ensuring the food security of our nation’s veterans is essential to VA’s commitment to providing integrated, veteran-centered, whole person care. Toward that goal, VA health care teams are urged to use the clinical reminder and help connect food insecure veterans with relevant resources both within and outside of the VA health care system.

Nearly 1 in 8 households—and 1 in 6 households with children—experienced food insecurity in 2017, defined as limited or uncertain availability of nutritionally adequate and safe foods.¹ Food insecurity is often even more pronounced among households with individuals with acute or chronic medical conditions.^2-6 Moreover, food insecurity is independently associated with a range of adverse health outcomes, including poorer control of diabetes mellitus, hypertension, depression and other major psychiatric disorders, HIV, and chronic lung and kidney disease, as well as poorer overall health status.^7-14 Food insecurity also has been associated with increased health care costs and acute care utilization as well as increased probability of delayed or missed care.^15-19

The relationship between food insecurity and poor health outcomes is a complex and often cyclic phenomenon (Figure 1). Poor nutritional status is fueled by limited access to healthful foods as well as increased reliance on calorie-dense and nutrient-poor “junk” foods, which are less expensive and often more readily available in low-income neighborhoods.^5,20-24 These compensatory dietary patterns place individuals at higher risk for developing cardiometabolic conditions and for poor control of these conditions.^{5,8,9,12,25,26} Additionally, the physiological and psychological stressors of food insecurity may precipitate depression and anxiety or worsen existing mental health conditions, resulting in feelings of overwhelm and decreased self-management capacity.^5,8,27-31 Food insecurity has further been associated with poor sleep, declines in cognitive function, and increased falls, particularly among the frail and elderly.^32-34

Individuals experiencing food insecurity often report having to make trade-offs between food and other necessities, such as paying rent or utilities. Additional strategies to stretch limited resources include cost-related underuse of medication and delays in needed medical care.^4,17,31,35 In a nationally representative survey among adults with at least 1 chronic medical condition, 1 in 3 reported having to choose between food and medicine; 11% were unable to afford either.³ Furthermore, the inability to reliably adhere to medication regimens that need to be taken with food can result in potentially life-threatening hypoglycemia (as can lack of food regardless of medication use).^5,26,36 In addition to the more obvious risks of glucose-lowering medications, such as insulin and long-acting sulfonylureas in patients experiencing food insecurity, many drugs commonly used among nondiabetic adults such as ACE-inhibitors, β blockers, quinolones, and salicylates can also precipitate hypoglycemia, and food insecurity has been associated with experiences of hypoglycemia even among individuals without diabetes mellitus.^32,37 In one study the risk for hospital admissions for hypoglycemia among low-income populations increased by 27% at the end of the month when food budgets were more likely to be exhausted.³⁸ Worsening health status and increased emergency department visits and hospitalizations may then result in lost wages and mounting medical bills, contributing to further financial strain and worsening food insecurity.

Prevalence and Importance of Food Insecurity Among US Veterans

Nearly 1.5 million veterans in the US are living below the federal poverty level (FPL).³⁹ An additional 2.4 million veterans are living paycheck to paycheck at < 200% of the FPL.⁴⁰ Veterans living in poverty are at even higher risk than nonveterans for food insecurity, homelessness, and other material hardship.⁴¹

 

Estimates of food insecurity among veterans vary widely, ranging from 6% to 24%—nearly twice that of the general US population.^8,42-45 Higher rates of food insecurity have been reported among certain high-risk subgroups, including veterans who served in Iraq and Afghanistan (27%), female veterans (28%), homeless and formerly homeless veterans (49%), and veterans with serious mental illness (35%).^6,32,43,46 Additional risk factors for food insecurity specific to veteran populations include younger age, having recently left active-duty military service, and lower final military paygrade.^42,45-47 As in the general population, veteran food insecurity is associated with a range of adverse health outcomes, including poorer overall health status as well as increased probability of delayed or missed care.^{6,8,32,42-44,46}

Even among veterans enrolled in federal food assistance programs, many still struggle to afford nutritionally adequate foods. As one example, in a study of mostly male homeless and formerly homeless veterans, O’Toole and colleagues found that nearly half of those reporting food insecurity were already receiving federal food assistance benefits, and 22% relied on emergency food resources.³² Of households served by Feeding America food pantries and meal programs, 20% have a member who has served in the US military.⁴⁸

Federal Programs To Address Food Insecurity

There are several important federal food assistance programs designed to help alleviate food insecurity. The Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp program) is the largest federal food assistance program and provides low-income Americans with cash benefits to purchase food. SNAP has been shown to substantially reduce food insecurity.^7,49 The program also is associated with significant decreases in cost-related medication nonadherence as well as reductions in health care costs and both acute care and nursing home utilization.^16,50-54 Although nearly 1.4 million veterans live in SNAP-enrolled households, 59% of eligible veterans are not enrolled.^43,55 Closing this SNAP eligibility-enrollment gap, has been a focus of recent efforts to improve long-term food security among veterans. There also are several federal food assistance programs for households with children, including the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and school meals programs. Among federal nutrition programs for seniors, the Older American’s Act contains designated funding to support nutrition services for older adults, including congregate meal programs in community settings like senior centers, places of worship, and housing communities, and home-delivered meals through programs like Meals on Wheels.⁵⁶

VHA Response to Food Insecurity

The Veterans Health Administration (VHA) is the country’s largest integrated, federally funded health care system.⁵⁷ In November 2015, congressional briefings on veteran food insecurity organized by the national non-profit organization MAZON: A Jewish Response to Hunger and hosted with bipartisan support were provided to the US House and Senate. As a result of these briefings, VHA chartered the national Ensuring Veteran Food Security Workgroup with a mandate to partner with governmental and nonprofit agencies to “focus on the issue of food insecurity, the identification of veterans at risk, the needed training of VHA staff and the coordination of resources and initiatives to support the veterans for whom we care.” Building off a pilot in US Department of Veterans Affairs (VA) Homeless Patient Aligned Care Teams (H-PACTs),³² VHA subsequently integrated a single-item food insecurity screening tool into the VA electronic health record (EHR) clinical reminder system (Figure 2). The clinical reminder, which was rolled out across VA medical centers nationally in October 2017, provides an alert to screen all noninstitutionalized veterans for food insecurity. To date, nearly 5 million veterans have been screened. When a veteran endorses food insecurity based on the initial screening question, a prompt appears to offer the veteran a referral to a social worker and/or dietitian. Positive screening results also should be communicated to the patient’s primary care provider. Depending on site-specific clinical flow, the reminders are typically completed in the outpatient setting either by nurses or medical assistants during intake or by providers as part of the clinical visit. However, any member of the health care team can complete the clinical reminder at any time. As of September 2019, approximately 74,000 veterans have been identified as food insecure.⁵⁸

 

Addressing Food Insecurity

VHA has been a recognized leader in addressing homelessness and other social determinants of health through its integrated care and PACT delivery models.^59-61 The food insecurity clinical reminder was designed to facilitate a tailored, interdisciplinary approach to identify and address food insecurity. Interdisciplinary care team members—including medical assistants, clinicians, social workers, registered dietitians, nurse care managers, occupational or physical therapists, and pharmacists—are uniquely positioned to identify veterans impacted by food insecurity, assess for associated clinical and/or social risk factors, and offer appropriate medical and nutrition interventions and resource referrals.

This interdisciplinary team-based model is essential given the range of potential drivers underlying veteran experiences of food insecurity and subsequent health outcomes. It is critically important for clinicians to review the medication list with veterans screening positive for food insecurity to assess for risk of hypoglycemia and/or cost-related nonadherence, make any necessary adjustments to therapeutic regimens, and assess for additional risk factors associated with food insecurity. Examples of tailored nutrition counseling that clinical dietitians may provide include meal preparation strategies for veterans who only have access to a microwave or hotplate, or recommendations for how veterans on medically restricted diets can best navigate food selection at soup kitchens or food pantries. Resource referrals provided by social workers or other care team members may include both emergency food resources to address immediate shortages (eg, food pantries, soup kitchens, or vouchers for free lunch) as well as resources focused on improving longer term food security (eg, federal food assistance programs or home delivered meal programs). Importantly, although providing a list of food resources may be helpful for some patients, such lists are often insufficient.^62,63 Many patients require active assistance with program enrollment either onsite the day of their clinic visit or through connection with a partnering community-based organization that can, in turn, identify appropriate resources and facilitate program enrollment.^63,64 Planned follow-up is also crucial to determine whether referrals are successful and to assess for ongoing need. Proposed roles for interdisciplinary care team members in addressing a positive food insecurity screen are outlined in Table 1.

VHA-Community Partnerships

In addition to services offered within VA, public and private sector partnerships can greatly enhance the range of resources available to food insecure veterans. Several VA facilities have developed formal community partnerships, such as the Veterans Pantry Pilot (VPP) program, a national partnership between Feeding America food banks and VA medical centers to establish onsite or mobile food pantries. There are currently 17 active Feeding America VPP sites, with a number of additional sites under development. Several of the VPP sites also include other “wraparound services,” such as SNAP application assistance.^65,66

State Veterans Affairs offices⁶⁷ and Veterans Service Organizations (VSOs)⁶⁸ also can serve as valuable partners for connecting veterans with needed resources. VSOs offer a range of services, including assistancewith benefit claims, employment and housing assistance, emergency food assistance, and transportation to medical appointments. Some VSOs also have established local affiliations with Meals on Wheels focused on veteran outreach and providing hot meals for low-income, homebound, and disabled veterans.

 

Additional Resources

Although resources vary by regional setting, several key governmental and community-based food assistance programs are summarized in Table 2. Local community partners and online/phone-based directories, such as United Way’s 2-1-1 can help identify additional local resources. For older adults and individuals with disabilities, local Aging and Disability Resources Centers can provide information and assistance connecting to needed resources.⁶⁹ Finally, there are a number of online resources available for clinicians interested in learning more about the impact of food insecurity on health and tools to use in the clinical setting (Table 3).

Conclusion

The VA has recognized food insecurity as a critical concern for the well-being of our nation’s veterans. Use of the EHR clinical reminder represents a crucial first step toward increasing provider awareness about veteran food insecurity and improving clinical efforts to address food insecurity once identified. Through the reminder, health care teams can connect veterans to needed resources and create both the individual and population-level data necessary to inform VHA and community efforts to address veteran food insecurity. Clinical reminder data are currently being used for local quality improvement efforts and have established the need nationally for formalized partnerships between VHA Social Work Services and Nutrition and Food Services to connect veterans with food and provide them with strategies to best use available food resources.

Moving forward, the Ensuring Veteran Food Security Workgroup continues to work with agencies and organizations across the country to improve food insecure veterans’ access to needed services. In addition to existing VA partnerships with Feeding America for the VPP, memorandums of understanding are currently underway to formalize partnerships with both the Food Research and Action Center (FRAC) and MAZON. Additional research is needed both to formally validate the current food insecurity clinical reminder screening question and to identify best practices and potential models for how to most effectively use VHA-community partnerships to address the unique needs of the veteran population.

Ensuring the food security of our nation’s veterans is essential to VA’s commitment to providing integrated, veteran-centered, whole person care. Toward that goal, VA health care teams are urged to use the clinical reminder and help connect food insecure veterans with relevant resources both within and outside of the VA health care system.

Medical knowledge is growing faster than ever, as is the challenge of keeping up with this ever-growing body of information. Clinicians need a system or method to help them sort and evaluate the quality of new information before they can apply it to clinical care. Without such a system, when facing an overload of information, most of us tend to take the first or the most easily accessed information, without considering the quality of such information. As a result, the use of poor-quality information affects the quality and outcome of care we provide, and costs billions of dollars annually in problems associated with underuse, overuse, and misuse of treatments.

In an effort to sort and evaluate recently published research that is ready for clinical use, the first author (SAS) used the following 3-step methodology:

1. Searched literature for research findings suggesting readiness for clinical utilization published between July 1, 2018 and June 30, 2019.

2. Surveyed members of the American Association of Chairs of Departments of Psychiatry, the American Association of Community Psychiatrists, the American Association of Psychiatric Administrators, the North Carolina Psychiatric Association, the Group for the Advancement of Psychiatry, and many other colleagues by asking them: “Among the articles published from July 1, 2018 to June 30, 2019, which ones in your opinion have (or are likely to have or should have) affected/changed the clinical practice of psychiatry?”

3. Looked for appraisals in post-publication reviews such as NEJM Journal Watch, F1000 Prime, Evidence-Based Mental Health, commentaries in peer-reviewed journals, and other sources (see Related Resources).

We chose 12 articles based on their clinical relevance/applicability. Here in Part 1 we present brief descriptions of the 6 of top 12 papers chosen by this methodology; these studies are summarized in the Table.^1-6 The order in which they appear in this article is arbitrary. The remaining 6 studies will be reviewed in Part 2 in the February 2020 issue of Current Psychiatry.

1. Ray WA, Stein CM, Murray KT, et al. Association of antipsychotic treatment with risk of unexpected death among children and youths. JAMA Psychiatry. 2019;76(2):162-171.

Children and young adults are increasingly being prescribed antipsychotic medications. Studies have suggested that when these medications are used in adults and older patients, they are associated with an increased risk of death.^7-9 Whether or not these medications are associated with an increased risk of death in children and youth has been unknown. Ray et al¹ compared the risk of unexpected death among children and youths who were beginning treatment with an antipsychotic or control medications.

Study design

• This retrospective cohort study evaluated children and young adults age 5 to 24 who were enrolled in Medicaid in Tennessee between 1999 and 2014.
• New antipsychotic use at both a higher dose (>50 mg chlorpromazine equivalents) and a lower dose (≤50 mg chlorpromazine equivalents) was compared with new use of a control medication, including attention-deficit/hyperactivity disorder medications, antidepressants, and mood stabilizers.
• There were 189,361 participants in the control group, 28,377 participants in the lower-dose antipsychotic group, and 30,120 participants in the higher-dose antipsychotic group.

Outcomes

• The primary outcome was death due to injury or suicide or unexpected death occurring during study follow-up.
• The incidence of death in the higher-dose antipsychotic group (146.2 per 100,000 person-years) was significantly higher (P < .001) than the incidence of death in the control medications group (54.5 per 100,000 person years).
• There was no similar significant difference between the lower-dose antipsychotic group and the control medications group.

Continue to: Conclusion

 

Conclusion

• Higher-dose antipsychotic use is associated with increased rates of unexpected deaths in children and young adults.
• As with all association studies, no direct line connected cause and effect. However, these results reinforce recommendations for careful prescribing and monitoring of antipsychotic regimens for children and youths, and the need for larger antipsychotic safety studies in this population.
• Examining risks associated with specific antipsychotics will require larger datasets, but will be critical for our understanding of the risks and benefits.

2. Daly EJ, Trivedi MH, Janik A, et al. Efficacy of esketamine nasal spray plus oral antidepressant treatment for relapse prevention in patients with treatment-resistant depression: a randomized clinical trial. JAMA Psychiatry. 2019;76(9):893-903.

Controlled studies have shown esketamine has efficacy for treatment-resistant depression (TRD), but these studies have been only short-term, and the long-term effects of esketamine for TRD have not been established. To fill that gap, Daly et al² assessed the efficacy of esketamine nasal spray plus an oral antidepressant vs a placebo nasal spray plus an oral antidepressant in delaying relapse of depressive symptoms in patients with TRD. All patients were in stable remission after an optimization course of esketamine nasal spray plus an oral antidepressant.

Study design

• Between October 2015 and February 2018, researchers conducted a phase III, multicenter, double-blind, randomized withdrawal study to evaluate the effect of continuation of esketamine on rates of relapse in patients with TRD who had responded to initial treatment with esketamine.
• Initially, 705 adults were enrolled. Of these participants, 455 proceeded to the optimization phase, in which they were treated with esketamine nasal spray plus an oral antidepressant.
• After 16 weeks of optimization treatment, 297 participants achieved remission or stable response and were randomized to a treatment group, which received continued esketamine nasal spray plus an oral antidepressant, or to a control group, which received a placebo nasal spray plus an oral antidepressant.

Outcomes

• Treatment with esketamine nasal spray and an oral antidepressant was associated with decreased rates of relapse compared with treatment with placebo nasal spray and an oral antidepressant. This was the case among patients who had achieved remission as well as those who had achieved stable response.
• Continued treatment with esketamine decreased the risk of relapse by 51%, with 40 participants in the treatment group experiencing relapse compared with 73 participants in the placebo group.

Continue to: Conclusion

 

Conclusion

• In patients with TRD who responded to initial treatment with esketamine, continuing esketamine plus an oral antidepressant resulted in clinically meaningful superiority in preventing relapse compared with a placebo nasal spray plus an oral antidepressant.

3. Williams NR, Heifets BD, Blasey C, et al. Attenuation of antidepressant effects of ketamine by opioid receptor antagonism. Am J Psychiatry. 2018;175(12):1205-1215.

Many studies have documented the efficacy of ketamine as a rapid-onset antidepressant. Studies investigating the mechanism of this effect have focused on antagonism of N-methyl-D-aspartate (NMDA) receptors. However, several clinical trials that attempted to replicate this rapid antidepressant effect with other NMDA receptor antagonists had only limited success. Williams et al³ conducted the first human study that presents evidence that opioid receptor activation may be necessary for ketamine’s acute antidepressant effect.

Study design

• This double-blind crossover study evaluated if opioid receptor activation is necessary for ketamine to have an antidepressant effect in patients with TRD.
• Twelve participants completed both sides of the study in a randomized order. Participants received placebo or naltrexone prior to an IV infusion of ketamine.
• Researchers measured patients’ scores on the Hamilton Depression Rating Scale (HAM-D) at baseline and 1 day after infusion. Response was defined as a ≥50% reduction in HAM-D score.

Outcomes

• Reductions in HAM-D scores among participants in the ketamine plus naltrexone group were significantly lower than those of participants in the ketamine plus placebo group.
• Dissociation related to ketamine use did not differ significantly between the naltrexone group and the placebo group.

Continue to: Conclusion

 

Conclusion

• This small study found a significant decrease in the antidepressant effect of ketamine infusion in patients with TRD when opioid receptors are blocked with naltrexone prior to infusion, which suggests opioid receptor activation is necessary for ketamine to be effective as an antidepressant.
• This appears to be consistent with observations of buprenorphine’s antidepressant effects. Caution is indicated until additional studies can further elucidate the mechanism of action of ketamine’s antidepressant effects (see "Ketamine/esketamine: Putative mechanism of action," page 32).

4. Nidich S, Mills PJ, Rainforth M, et al. Non-trauma-focused meditation versus exposure therapy in veterans with post-traumatic stress disorder: a randomised controlled trial. Lancet Psychiatry. 2018;5(12):975-986.

Posttraumatic stress disorder (PTSD) is a common and important public health problem. Evidence-based treatments for PTSD include trauma-focused therapies such as prolonged exposure therapy (PE). However, some patients may not respond to PE, drop out, or elect not to pursue it. Researchers continue to explore treatments that are non-trauma-focused, such as mindfulness meditation and interpersonal psychotherapy. In a 3-group comparative effectiveness trial, Nidich et al⁴ examined the efficacy of a non-trauma-focused intervention, transcendental meditation (TM), in reducing PTSD symptom severity and depression in veterans.

Study design

• Researchers recruited 203 veterans with PTSD from the Department of Veterans Affairs (VA) San Diego Healthcare System between June 2013 and October 2016.
• Participants were randomly assigned to 1 of 3 groups: 68 to TM, 68 to PE, and 67 to PTSD health education (HE).
• Each group received 12 sessions over 12 weeks. In addition to group and individual sessions, all participants received daily practice or assignments.
• The Clinician-Administered PTSD Scale (CAPS) was used to assess symptoms before and after treatment.

Outcomes

• The primary outcome assessed was change in PTSD symptom severity at the end of the study compared with baseline as measured by change in CAPS score.
• Transcendental meditation was found to be significantly non-inferior to PE, with a mean change in CAPS score of −16.1 in the TM group and −11.2 in the PE group.
• Both the TM and PE groups also had significant reductions in CAPS scores compared with the HE group, which had a mean change in CAPS score of −2.5.

Continue to: Conclusion

 

Conclusion

• Transcendental meditation is significantly not inferior to PE in the treatment of veterans with PTSD.
• The findings from this first comparative effectiveness trial comparing TM with an established psychotherapy for PTSD suggests the feasibility and efficacy of TM as an alternative therapy for veterans with PTSD.
• Because TM is self-administered after an initial expert training, it may offer an easy-to-implement approach that may be more accessible to veterans than other treatments.

5. Raskind MA, Peskind ER, Chow B, et al. Trial of prazosin for post-traumatic stress disorder in military veterans. N Engl J Med. 2018;378(6):507-517.

Several smaller randomized trials of prazosin involving a total of 283 active-duty service members, veterans, and civilian participants have shown efficacy of prazosin for PTSD-related nightmares, sleep disturbance, and overall clinical functioning. However, in a recent trial, Raskind et al⁵ failed to demonstrate such efficacy.

Study design

• Veterans with chronic PTSD nightmares were recruited from 13 VA medical centers to participate in a 26-week, double-blind, randomized controlled trial.
• A total of 304 participants were randomized to a prazosin treatment group (n = 152) or a placebo control group (n = 152).
• During the first 10 weeks, prazosin or placebo were administered in an escalating fashion up to a maximum dose.
• The CAPS, Pittsburgh Sleep Quality Index (PSQI), and Clinical Global Impressions of Change (CGIC) scores were measured at baseline, after 10 weeks, and after 26 weeks.

Outcomes

• Three primary outcomes measures were assessed: change in score from baseline to 10 weeks on CAPS item B2, the PSQI, and the CGIC.
• A secondary measure was change in score from baseline of the same measures at 26 weeks.
• There was no significant difference between the prazosin group and the placebo group in any of the primary or secondary measures.

Continue to: Conclusion

 

Conclusion

• Compared with placebo, prazosin was not associated with improvement in nightmares or sleep quality for veterans with chronic PTSD nightmares.
• Because psychosocial instability was an exclusion criterion, it is possible that a selection bias resulting from recruitment of patients who were mainly in clinically stable condition accounted for these negative results, since symptoms in such patients were less likely to be ameliorated with antiadrenergic treatment.

6. Yesavage JA, Fairchild JK, Mi Z, et al. Effect of repetitive transcranial magnetic stimulation on treatment-resistant major depression in US veterans: a randomized clinical trial. JAMA Psychiatry. 2018;75(9):884-893.

Treatment-resistant depression in veterans is a major clinical challenge because of these patients’ increased risk of suicide. Repetitive transcranial magnetic stimulation (rTMS) has shown promising results for TRD. In a randomized trial, Yesavage et al⁶ compared rTMS vs sham rTMS in veterans with TRD.

Study design

• Veterans with TRD were recruited from 9 VA medical centers throughout the United States between September 2012 and May 2016.
• Researchers randomized 164 participants into 1 of 2 groups in a double-blind fashion. The treatment group (n = 81) received left prefrontal rTMS, and the control group (n = 83) received sham rTMS.

Outcomes

• In an intention-to-treat analysis, remission rate (defined as a HAM-D score of ≤10) was assessed as the primary outcome measure.
• Remission was seen in both groups, with 40.7% of the treatment group achieving remission and 37.4% of the control group achieving remission. However, the difference between the 2 groups was not significant (P = .67), with an odds ratio of 1.16.

Continue to: Conclusion

 

Conclusion

• In this study, treatment with rTMS did not show a statistically significant difference in rates of remission from TRD in veterans compared with sham rTMS. This differs from previous rTMS trials in non-veteran patients.
• The findings of this study also differed from those of other rTMS research in terms of the high remission rates that were seen in both the active and sham groups.

Bottom Line

The risk of death might be increased in children and young adults who receive highdose antipsychotics. Continued treatment with intranasal esketamine may help prevent relapse in patients with treatment-resistant depression (TRD) who initially respond to esketamine. The antidepressant effects of ketamine might be associated with opioid receptor activation. Transcendental meditation may be helpful for patients with posttraumatic stress disorder (PTSD), while prazosin might not improve nightmares or sleep quality in patients with PTSD. Repetitive transcranial magnetic stimulation (rTMS) might not be any more effective than sham rTMS for veterans with TRD.

Related Resources

• NEJM Journal Watch. www.jwatch.org.
• F1000 Prime. https://f1000.com/prime/home.
• BMJ Journals Evidence-Based Mental Health. https://ebmh.bmj.com.

Drug Brand Names

Buprenorphine • Subutex
Chlorpromazine • Thorazine
Esketamine nasal spray • Spravato
Ketamine • Ketalar
Naltrexone • Narcan
Prazosin • Minipress

Medical knowledge is growing faster than ever, as is the challenge of keeping up with this ever-growing body of information. Clinicians need a system or method to help them sort and evaluate the quality of new information before they can apply it to clinical care. Without such a system, when facing an overload of information, most of us tend to take the first or the most easily accessed information, without considering the quality of such information. As a result, the use of poor-quality information affects the quality and outcome of care we provide, and costs billions of dollars annually in problems associated with underuse, overuse, and misuse of treatments.

In an effort to sort and evaluate recently published research that is ready for clinical use, the first author (SAS) used the following 3-step methodology:

1. Searched literature for research findings suggesting readiness for clinical utilization published between July 1, 2018 and June 30, 2019.

2. Surveyed members of the American Association of Chairs of Departments of Psychiatry, the American Association of Community Psychiatrists, the American Association of Psychiatric Administrators, the North Carolina Psychiatric Association, the Group for the Advancement of Psychiatry, and many other colleagues by asking them: “Among the articles published from July 1, 2018 to June 30, 2019, which ones in your opinion have (or are likely to have or should have) affected/changed the clinical practice of psychiatry?”

3. Looked for appraisals in post-publication reviews such as NEJM Journal Watch, F1000 Prime, Evidence-Based Mental Health, commentaries in peer-reviewed journals, and other sources (see Related Resources).

We chose 12 articles based on their clinical relevance/applicability. Here in Part 1 we present brief descriptions of the 6 of top 12 papers chosen by this methodology; these studies are summarized in the Table.^1-6 The order in which they appear in this article is arbitrary. The remaining 6 studies will be reviewed in Part 2 in the February 2020 issue of Current Psychiatry.

1. Ray WA, Stein CM, Murray KT, et al. Association of antipsychotic treatment with risk of unexpected death among children and youths. JAMA Psychiatry. 2019;76(2):162-171.

Children and young adults are increasingly being prescribed antipsychotic medications. Studies have suggested that when these medications are used in adults and older patients, they are associated with an increased risk of death.^7-9 Whether or not these medications are associated with an increased risk of death in children and youth has been unknown. Ray et al¹ compared the risk of unexpected death among children and youths who were beginning treatment with an antipsychotic or control medications.

Study design

• This retrospective cohort study evaluated children and young adults age 5 to 24 who were enrolled in Medicaid in Tennessee between 1999 and 2014.
• New antipsychotic use at both a higher dose (>50 mg chlorpromazine equivalents) and a lower dose (≤50 mg chlorpromazine equivalents) was compared with new use of a control medication, including attention-deficit/hyperactivity disorder medications, antidepressants, and mood stabilizers.
• There were 189,361 participants in the control group, 28,377 participants in the lower-dose antipsychotic group, and 30,120 participants in the higher-dose antipsychotic group.

Outcomes

• The primary outcome was death due to injury or suicide or unexpected death occurring during study follow-up.
• The incidence of death in the higher-dose antipsychotic group (146.2 per 100,000 person-years) was significantly higher (P < .001) than the incidence of death in the control medications group (54.5 per 100,000 person years).
• There was no similar significant difference between the lower-dose antipsychotic group and the control medications group.

Continue to: Conclusion

 

Conclusion

• Higher-dose antipsychotic use is associated with increased rates of unexpected deaths in children and young adults.
• As with all association studies, no direct line connected cause and effect. However, these results reinforce recommendations for careful prescribing and monitoring of antipsychotic regimens for children and youths, and the need for larger antipsychotic safety studies in this population.
• Examining risks associated with specific antipsychotics will require larger datasets, but will be critical for our understanding of the risks and benefits.

2. Daly EJ, Trivedi MH, Janik A, et al. Efficacy of esketamine nasal spray plus oral antidepressant treatment for relapse prevention in patients with treatment-resistant depression: a randomized clinical trial. JAMA Psychiatry. 2019;76(9):893-903.

Controlled studies have shown esketamine has efficacy for treatment-resistant depression (TRD), but these studies have been only short-term, and the long-term effects of esketamine for TRD have not been established. To fill that gap, Daly et al² assessed the efficacy of esketamine nasal spray plus an oral antidepressant vs a placebo nasal spray plus an oral antidepressant in delaying relapse of depressive symptoms in patients with TRD. All patients were in stable remission after an optimization course of esketamine nasal spray plus an oral antidepressant.

Study design

• Between October 2015 and February 2018, researchers conducted a phase III, multicenter, double-blind, randomized withdrawal study to evaluate the effect of continuation of esketamine on rates of relapse in patients with TRD who had responded to initial treatment with esketamine.
• Initially, 705 adults were enrolled. Of these participants, 455 proceeded to the optimization phase, in which they were treated with esketamine nasal spray plus an oral antidepressant.
• After 16 weeks of optimization treatment, 297 participants achieved remission or stable response and were randomized to a treatment group, which received continued esketamine nasal spray plus an oral antidepressant, or to a control group, which received a placebo nasal spray plus an oral antidepressant.

Outcomes

• Treatment with esketamine nasal spray and an oral antidepressant was associated with decreased rates of relapse compared with treatment with placebo nasal spray and an oral antidepressant. This was the case among patients who had achieved remission as well as those who had achieved stable response.
• Continued treatment with esketamine decreased the risk of relapse by 51%, with 40 participants in the treatment group experiencing relapse compared with 73 participants in the placebo group.

Continue to: Conclusion

 

Conclusion

• In patients with TRD who responded to initial treatment with esketamine, continuing esketamine plus an oral antidepressant resulted in clinically meaningful superiority in preventing relapse compared with a placebo nasal spray plus an oral antidepressant.

3. Williams NR, Heifets BD, Blasey C, et al. Attenuation of antidepressant effects of ketamine by opioid receptor antagonism. Am J Psychiatry. 2018;175(12):1205-1215.

Many studies have documented the efficacy of ketamine as a rapid-onset antidepressant. Studies investigating the mechanism of this effect have focused on antagonism of N-methyl-D-aspartate (NMDA) receptors. However, several clinical trials that attempted to replicate this rapid antidepressant effect with other NMDA receptor antagonists had only limited success. Williams et al³ conducted the first human study that presents evidence that opioid receptor activation may be necessary for ketamine’s acute antidepressant effect.

Study design

• This double-blind crossover study evaluated if opioid receptor activation is necessary for ketamine to have an antidepressant effect in patients with TRD.
• Twelve participants completed both sides of the study in a randomized order. Participants received placebo or naltrexone prior to an IV infusion of ketamine.
• Researchers measured patients’ scores on the Hamilton Depression Rating Scale (HAM-D) at baseline and 1 day after infusion. Response was defined as a ≥50% reduction in HAM-D score.

Outcomes

• Reductions in HAM-D scores among participants in the ketamine plus naltrexone group were significantly lower than those of participants in the ketamine plus placebo group.
• Dissociation related to ketamine use did not differ significantly between the naltrexone group and the placebo group.

Continue to: Conclusion

 

Conclusion

• This small study found a significant decrease in the antidepressant effect of ketamine infusion in patients with TRD when opioid receptors are blocked with naltrexone prior to infusion, which suggests opioid receptor activation is necessary for ketamine to be effective as an antidepressant.
• This appears to be consistent with observations of buprenorphine’s antidepressant effects. Caution is indicated until additional studies can further elucidate the mechanism of action of ketamine’s antidepressant effects (see "Ketamine/esketamine: Putative mechanism of action," page 32).

4. Nidich S, Mills PJ, Rainforth M, et al. Non-trauma-focused meditation versus exposure therapy in veterans with post-traumatic stress disorder: a randomised controlled trial. Lancet Psychiatry. 2018;5(12):975-986.

Posttraumatic stress disorder (PTSD) is a common and important public health problem. Evidence-based treatments for PTSD include trauma-focused therapies such as prolonged exposure therapy (PE). However, some patients may not respond to PE, drop out, or elect not to pursue it. Researchers continue to explore treatments that are non-trauma-focused, such as mindfulness meditation and interpersonal psychotherapy. In a 3-group comparative effectiveness trial, Nidich et al⁴ examined the efficacy of a non-trauma-focused intervention, transcendental meditation (TM), in reducing PTSD symptom severity and depression in veterans.

Study design

• Researchers recruited 203 veterans with PTSD from the Department of Veterans Affairs (VA) San Diego Healthcare System between June 2013 and October 2016.
• Participants were randomly assigned to 1 of 3 groups: 68 to TM, 68 to PE, and 67 to PTSD health education (HE).
• Each group received 12 sessions over 12 weeks. In addition to group and individual sessions, all participants received daily practice or assignments.
• The Clinician-Administered PTSD Scale (CAPS) was used to assess symptoms before and after treatment.

Outcomes

• The primary outcome assessed was change in PTSD symptom severity at the end of the study compared with baseline as measured by change in CAPS score.
• Transcendental meditation was found to be significantly non-inferior to PE, with a mean change in CAPS score of −16.1 in the TM group and −11.2 in the PE group.
• Both the TM and PE groups also had significant reductions in CAPS scores compared with the HE group, which had a mean change in CAPS score of −2.5.

Continue to: Conclusion

 

Conclusion

• Transcendental meditation is significantly not inferior to PE in the treatment of veterans with PTSD.
• The findings from this first comparative effectiveness trial comparing TM with an established psychotherapy for PTSD suggests the feasibility and efficacy of TM as an alternative therapy for veterans with PTSD.
• Because TM is self-administered after an initial expert training, it may offer an easy-to-implement approach that may be more accessible to veterans than other treatments.

5. Raskind MA, Peskind ER, Chow B, et al. Trial of prazosin for post-traumatic stress disorder in military veterans. N Engl J Med. 2018;378(6):507-517.

Several smaller randomized trials of prazosin involving a total of 283 active-duty service members, veterans, and civilian participants have shown efficacy of prazosin for PTSD-related nightmares, sleep disturbance, and overall clinical functioning. However, in a recent trial, Raskind et al⁵ failed to demonstrate such efficacy.

Study design

• Veterans with chronic PTSD nightmares were recruited from 13 VA medical centers to participate in a 26-week, double-blind, randomized controlled trial.
• A total of 304 participants were randomized to a prazosin treatment group (n = 152) or a placebo control group (n = 152).
• During the first 10 weeks, prazosin or placebo were administered in an escalating fashion up to a maximum dose.
• The CAPS, Pittsburgh Sleep Quality Index (PSQI), and Clinical Global Impressions of Change (CGIC) scores were measured at baseline, after 10 weeks, and after 26 weeks.

Outcomes

• Three primary outcomes measures were assessed: change in score from baseline to 10 weeks on CAPS item B2, the PSQI, and the CGIC.
• A secondary measure was change in score from baseline of the same measures at 26 weeks.
• There was no significant difference between the prazosin group and the placebo group in any of the primary or secondary measures.

Continue to: Conclusion

 

Conclusion

• Compared with placebo, prazosin was not associated with improvement in nightmares or sleep quality for veterans with chronic PTSD nightmares.
• Because psychosocial instability was an exclusion criterion, it is possible that a selection bias resulting from recruitment of patients who were mainly in clinically stable condition accounted for these negative results, since symptoms in such patients were less likely to be ameliorated with antiadrenergic treatment.

6. Yesavage JA, Fairchild JK, Mi Z, et al. Effect of repetitive transcranial magnetic stimulation on treatment-resistant major depression in US veterans: a randomized clinical trial. JAMA Psychiatry. 2018;75(9):884-893.

Treatment-resistant depression in veterans is a major clinical challenge because of these patients’ increased risk of suicide. Repetitive transcranial magnetic stimulation (rTMS) has shown promising results for TRD. In a randomized trial, Yesavage et al⁶ compared rTMS vs sham rTMS in veterans with TRD.

Study design

• Veterans with TRD were recruited from 9 VA medical centers throughout the United States between September 2012 and May 2016.
• Researchers randomized 164 participants into 1 of 2 groups in a double-blind fashion. The treatment group (n = 81) received left prefrontal rTMS, and the control group (n = 83) received sham rTMS.

Outcomes

• In an intention-to-treat analysis, remission rate (defined as a HAM-D score of ≤10) was assessed as the primary outcome measure.
• Remission was seen in both groups, with 40.7% of the treatment group achieving remission and 37.4% of the control group achieving remission. However, the difference between the 2 groups was not significant (P = .67), with an odds ratio of 1.16.

Continue to: Conclusion

 

Conclusion

• In this study, treatment with rTMS did not show a statistically significant difference in rates of remission from TRD in veterans compared with sham rTMS. This differs from previous rTMS trials in non-veteran patients.
• The findings of this study also differed from those of other rTMS research in terms of the high remission rates that were seen in both the active and sham groups.

Bottom Line

The risk of death might be increased in children and young adults who receive highdose antipsychotics. Continued treatment with intranasal esketamine may help prevent relapse in patients with treatment-resistant depression (TRD) who initially respond to esketamine. The antidepressant effects of ketamine might be associated with opioid receptor activation. Transcendental meditation may be helpful for patients with posttraumatic stress disorder (PTSD), while prazosin might not improve nightmares or sleep quality in patients with PTSD. Repetitive transcranial magnetic stimulation (rTMS) might not be any more effective than sham rTMS for veterans with TRD.

Related Resources

• NEJM Journal Watch. www.jwatch.org.
• F1000 Prime. https://f1000.com/prime/home.
• BMJ Journals Evidence-Based Mental Health. https://ebmh.bmj.com.

Drug Brand Names

Buprenorphine • Subutex
Chlorpromazine • Thorazine
Esketamine nasal spray • Spravato
Ketamine • Ketalar
Naltrexone • Narcan
Prazosin • Minipress

Medical knowledge is growing faster than ever, as is the challenge of keeping up with this ever-growing body of information. Clinicians need a system or method to help them sort and evaluate the quality of new information before they can apply it to clinical care. Without such a system, when facing an overload of information, most of us tend to take the first or the most easily accessed information, without considering the quality of such information. As a result, the use of poor-quality information affects the quality and outcome of care we provide, and costs billions of dollars annually in problems associated with underuse, overuse, and misuse of treatments.

In an effort to sort and evaluate recently published research that is ready for clinical use, the first author (SAS) used the following 3-step methodology:

1. Searched literature for research findings suggesting readiness for clinical utilization published between July 1, 2018 and June 30, 2019.

2. Surveyed members of the American Association of Chairs of Departments of Psychiatry, the American Association of Community Psychiatrists, the American Association of Psychiatric Administrators, the North Carolina Psychiatric Association, the Group for the Advancement of Psychiatry, and many other colleagues by asking them: “Among the articles published from July 1, 2018 to June 30, 2019, which ones in your opinion have (or are likely to have or should have) affected/changed the clinical practice of psychiatry?”

3. Looked for appraisals in post-publication reviews such as NEJM Journal Watch, F1000 Prime, Evidence-Based Mental Health, commentaries in peer-reviewed journals, and other sources (see Related Resources).

We chose 12 articles based on their clinical relevance/applicability. Here in Part 1 we present brief descriptions of the 6 of top 12 papers chosen by this methodology; these studies are summarized in the Table.^1-6 The order in which they appear in this article is arbitrary. The remaining 6 studies will be reviewed in Part 2 in the February 2020 issue of Current Psychiatry.

1. Ray WA, Stein CM, Murray KT, et al. Association of antipsychotic treatment with risk of unexpected death among children and youths. JAMA Psychiatry. 2019;76(2):162-171.

Children and young adults are increasingly being prescribed antipsychotic medications. Studies have suggested that when these medications are used in adults and older patients, they are associated with an increased risk of death.^7-9 Whether or not these medications are associated with an increased risk of death in children and youth has been unknown. Ray et al¹ compared the risk of unexpected death among children and youths who were beginning treatment with an antipsychotic or control medications.

Study design

• This retrospective cohort study evaluated children and young adults age 5 to 24 who were enrolled in Medicaid in Tennessee between 1999 and 2014.
• New antipsychotic use at both a higher dose (>50 mg chlorpromazine equivalents) and a lower dose (≤50 mg chlorpromazine equivalents) was compared with new use of a control medication, including attention-deficit/hyperactivity disorder medications, antidepressants, and mood stabilizers.
• There were 189,361 participants in the control group, 28,377 participants in the lower-dose antipsychotic group, and 30,120 participants in the higher-dose antipsychotic group.

Outcomes

• The primary outcome was death due to injury or suicide or unexpected death occurring during study follow-up.
• The incidence of death in the higher-dose antipsychotic group (146.2 per 100,000 person-years) was significantly higher (P < .001) than the incidence of death in the control medications group (54.5 per 100,000 person years).
• There was no similar significant difference between the lower-dose antipsychotic group and the control medications group.

Continue to: Conclusion

 

Conclusion

• Higher-dose antipsychotic use is associated with increased rates of unexpected deaths in children and young adults.
• As with all association studies, no direct line connected cause and effect. However, these results reinforce recommendations for careful prescribing and monitoring of antipsychotic regimens for children and youths, and the need for larger antipsychotic safety studies in this population.
• Examining risks associated with specific antipsychotics will require larger datasets, but will be critical for our understanding of the risks and benefits.

2. Daly EJ, Trivedi MH, Janik A, et al. Efficacy of esketamine nasal spray plus oral antidepressant treatment for relapse prevention in patients with treatment-resistant depression: a randomized clinical trial. JAMA Psychiatry. 2019;76(9):893-903.

Controlled studies have shown esketamine has efficacy for treatment-resistant depression (TRD), but these studies have been only short-term, and the long-term effects of esketamine for TRD have not been established. To fill that gap, Daly et al² assessed the efficacy of esketamine nasal spray plus an oral antidepressant vs a placebo nasal spray plus an oral antidepressant in delaying relapse of depressive symptoms in patients with TRD. All patients were in stable remission after an optimization course of esketamine nasal spray plus an oral antidepressant.

Study design

• Between October 2015 and February 2018, researchers conducted a phase III, multicenter, double-blind, randomized withdrawal study to evaluate the effect of continuation of esketamine on rates of relapse in patients with TRD who had responded to initial treatment with esketamine.
• Initially, 705 adults were enrolled. Of these participants, 455 proceeded to the optimization phase, in which they were treated with esketamine nasal spray plus an oral antidepressant.
• After 16 weeks of optimization treatment, 297 participants achieved remission or stable response and were randomized to a treatment group, which received continued esketamine nasal spray plus an oral antidepressant, or to a control group, which received a placebo nasal spray plus an oral antidepressant.

Outcomes

• Treatment with esketamine nasal spray and an oral antidepressant was associated with decreased rates of relapse compared with treatment with placebo nasal spray and an oral antidepressant. This was the case among patients who had achieved remission as well as those who had achieved stable response.
• Continued treatment with esketamine decreased the risk of relapse by 51%, with 40 participants in the treatment group experiencing relapse compared with 73 participants in the placebo group.

Continue to: Conclusion

 

Conclusion

• In patients with TRD who responded to initial treatment with esketamine, continuing esketamine plus an oral antidepressant resulted in clinically meaningful superiority in preventing relapse compared with a placebo nasal spray plus an oral antidepressant.

3. Williams NR, Heifets BD, Blasey C, et al. Attenuation of antidepressant effects of ketamine by opioid receptor antagonism. Am J Psychiatry. 2018;175(12):1205-1215.

Many studies have documented the efficacy of ketamine as a rapid-onset antidepressant. Studies investigating the mechanism of this effect have focused on antagonism of N-methyl-D-aspartate (NMDA) receptors. However, several clinical trials that attempted to replicate this rapid antidepressant effect with other NMDA receptor antagonists had only limited success. Williams et al³ conducted the first human study that presents evidence that opioid receptor activation may be necessary for ketamine’s acute antidepressant effect.

Study design

• This double-blind crossover study evaluated if opioid receptor activation is necessary for ketamine to have an antidepressant effect in patients with TRD.
• Twelve participants completed both sides of the study in a randomized order. Participants received placebo or naltrexone prior to an IV infusion of ketamine.
• Researchers measured patients’ scores on the Hamilton Depression Rating Scale (HAM-D) at baseline and 1 day after infusion. Response was defined as a ≥50% reduction in HAM-D score.

Outcomes

• Reductions in HAM-D scores among participants in the ketamine plus naltrexone group were significantly lower than those of participants in the ketamine plus placebo group.
• Dissociation related to ketamine use did not differ significantly between the naltrexone group and the placebo group.

Continue to: Conclusion

 

Conclusion

• This small study found a significant decrease in the antidepressant effect of ketamine infusion in patients with TRD when opioid receptors are blocked with naltrexone prior to infusion, which suggests opioid receptor activation is necessary for ketamine to be effective as an antidepressant.
• This appears to be consistent with observations of buprenorphine’s antidepressant effects. Caution is indicated until additional studies can further elucidate the mechanism of action of ketamine’s antidepressant effects (see "Ketamine/esketamine: Putative mechanism of action," page 32).

4. Nidich S, Mills PJ, Rainforth M, et al. Non-trauma-focused meditation versus exposure therapy in veterans with post-traumatic stress disorder: a randomised controlled trial. Lancet Psychiatry. 2018;5(12):975-986.

Posttraumatic stress disorder (PTSD) is a common and important public health problem. Evidence-based treatments for PTSD include trauma-focused therapies such as prolonged exposure therapy (PE). However, some patients may not respond to PE, drop out, or elect not to pursue it. Researchers continue to explore treatments that are non-trauma-focused, such as mindfulness meditation and interpersonal psychotherapy. In a 3-group comparative effectiveness trial, Nidich et al⁴ examined the efficacy of a non-trauma-focused intervention, transcendental meditation (TM), in reducing PTSD symptom severity and depression in veterans.

Study design

• Researchers recruited 203 veterans with PTSD from the Department of Veterans Affairs (VA) San Diego Healthcare System between June 2013 and October 2016.
• Participants were randomly assigned to 1 of 3 groups: 68 to TM, 68 to PE, and 67 to PTSD health education (HE).
• Each group received 12 sessions over 12 weeks. In addition to group and individual sessions, all participants received daily practice or assignments.
• The Clinician-Administered PTSD Scale (CAPS) was used to assess symptoms before and after treatment.

Outcomes

• The primary outcome assessed was change in PTSD symptom severity at the end of the study compared with baseline as measured by change in CAPS score.
• Transcendental meditation was found to be significantly non-inferior to PE, with a mean change in CAPS score of −16.1 in the TM group and −11.2 in the PE group.
• Both the TM and PE groups also had significant reductions in CAPS scores compared with the HE group, which had a mean change in CAPS score of −2.5.

Continue to: Conclusion

 

Conclusion

• Transcendental meditation is significantly not inferior to PE in the treatment of veterans with PTSD.
• The findings from this first comparative effectiveness trial comparing TM with an established psychotherapy for PTSD suggests the feasibility and efficacy of TM as an alternative therapy for veterans with PTSD.
• Because TM is self-administered after an initial expert training, it may offer an easy-to-implement approach that may be more accessible to veterans than other treatments.

5. Raskind MA, Peskind ER, Chow B, et al. Trial of prazosin for post-traumatic stress disorder in military veterans. N Engl J Med. 2018;378(6):507-517.

Several smaller randomized trials of prazosin involving a total of 283 active-duty service members, veterans, and civilian participants have shown efficacy of prazosin for PTSD-related nightmares, sleep disturbance, and overall clinical functioning. However, in a recent trial, Raskind et al⁵ failed to demonstrate such efficacy.

Study design

• Veterans with chronic PTSD nightmares were recruited from 13 VA medical centers to participate in a 26-week, double-blind, randomized controlled trial.
• A total of 304 participants were randomized to a prazosin treatment group (n = 152) or a placebo control group (n = 152).
• During the first 10 weeks, prazosin or placebo were administered in an escalating fashion up to a maximum dose.
• The CAPS, Pittsburgh Sleep Quality Index (PSQI), and Clinical Global Impressions of Change (CGIC) scores were measured at baseline, after 10 weeks, and after 26 weeks.

Outcomes

• Three primary outcomes measures were assessed: change in score from baseline to 10 weeks on CAPS item B2, the PSQI, and the CGIC.
• A secondary measure was change in score from baseline of the same measures at 26 weeks.
• There was no significant difference between the prazosin group and the placebo group in any of the primary or secondary measures.

Continue to: Conclusion

 

Conclusion

• Compared with placebo, prazosin was not associated with improvement in nightmares or sleep quality for veterans with chronic PTSD nightmares.
• Because psychosocial instability was an exclusion criterion, it is possible that a selection bias resulting from recruitment of patients who were mainly in clinically stable condition accounted for these negative results, since symptoms in such patients were less likely to be ameliorated with antiadrenergic treatment.

6. Yesavage JA, Fairchild JK, Mi Z, et al. Effect of repetitive transcranial magnetic stimulation on treatment-resistant major depression in US veterans: a randomized clinical trial. JAMA Psychiatry. 2018;75(9):884-893.

Treatment-resistant depression in veterans is a major clinical challenge because of these patients’ increased risk of suicide. Repetitive transcranial magnetic stimulation (rTMS) has shown promising results for TRD. In a randomized trial, Yesavage et al⁶ compared rTMS vs sham rTMS in veterans with TRD.

Study design

• Veterans with TRD were recruited from 9 VA medical centers throughout the United States between September 2012 and May 2016.
• Researchers randomized 164 participants into 1 of 2 groups in a double-blind fashion. The treatment group (n = 81) received left prefrontal rTMS, and the control group (n = 83) received sham rTMS.

Outcomes

• In an intention-to-treat analysis, remission rate (defined as a HAM-D score of ≤10) was assessed as the primary outcome measure.
• Remission was seen in both groups, with 40.7% of the treatment group achieving remission and 37.4% of the control group achieving remission. However, the difference between the 2 groups was not significant (P = .67), with an odds ratio of 1.16.

Continue to: Conclusion

 

Conclusion

• In this study, treatment with rTMS did not show a statistically significant difference in rates of remission from TRD in veterans compared with sham rTMS. This differs from previous rTMS trials in non-veteran patients.
• The findings of this study also differed from those of other rTMS research in terms of the high remission rates that were seen in both the active and sham groups.

Bottom Line

The risk of death might be increased in children and young adults who receive highdose antipsychotics. Continued treatment with intranasal esketamine may help prevent relapse in patients with treatment-resistant depression (TRD) who initially respond to esketamine. The antidepressant effects of ketamine might be associated with opioid receptor activation. Transcendental meditation may be helpful for patients with posttraumatic stress disorder (PTSD), while prazosin might not improve nightmares or sleep quality in patients with PTSD. Repetitive transcranial magnetic stimulation (rTMS) might not be any more effective than sham rTMS for veterans with TRD.

Related Resources

• NEJM Journal Watch. www.jwatch.org.
• F1000 Prime. https://f1000.com/prime/home.
• BMJ Journals Evidence-Based Mental Health. https://ebmh.bmj.com.

Drug Brand Names

Buprenorphine • Subutex
Chlorpromazine • Thorazine
Esketamine nasal spray • Spravato
Ketamine • Ketalar
Naltrexone • Narcan
Prazosin • Minipress

Hip fractures are a large source of morbidity and mortality in the United States, with >1.5 million patients affected every year.¹ These patients are primarily older adults with a significant burden of associated medical comorbidities.² The outcomes of nonoperative management are poor with regard to mortality,³ although operative management of hip fractures remains associated with a high rate of morbidity and mortality compared with several other surgical procedures, substantial resources remain devoted to the operative repair of hip fractures and to process improvement strategies for perioperative care.

Medical comanagement involves having a second nonsurgical primary team—often an internist, a hospitalist, a geriatrician, or an anesthesiologist—who would follow the patient during the hip fracture admission, and provide daily care directed toward both the hip fracture and its associated management challenges and the patient’s underlying comorbidities. This includes taking a primary or shared role in daily rounding, writing progress notes, writing orders, managing medications and therapies, disposition planning, and discharge. One argument for this practice has centered around an efficiency proposition for surgeons to spend more of their time operating and less time in these tasks of acute care management. The primary argument, though, for medical comanagement has been an outcomes proposition that frail, elderly patients with significant medical comorbidities benefit from a nonsurgeon’s focused attention to their coexisting medical problems and the interaction with the surgical issues posed by operative intervention for hip fracture. A number of previous studies have demonstrated an association between comanagement and improved perioperative outcomes.^4,5 However, the most convincing improvements in several studies have been process indicators (eg, time from admission to surgery, length of stay, nurse/surgeon satisfaction) without significant differences in mortality or major morbidity.^6-8 Several studies were methodologically limited due to the use of historical controls,^9,10 and several were conducted in focused clinical settings (eg, a single tertiary academic center), leaving uncertainty about external validity for other care environments.^6,7 To our knowledge, comanagement has not been examined in the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) dataset of hip fracture patients.

The NSQIP database offers a unique tool for clinical outcomes research because its variables are prospectively collected by a trained clinical reviewer at each participating site. Data are deidentified and aggregated into a national database, which has grown from 121 participating sites in 2005 to 708 participating sites in 2017 and now contains data on more than 6.6 million patients. The targeted hip fracture participant use file (PUF) adds additional variables and is available beginning with 2016. Internal audits ensure a high level of data reliability.¹¹ The NSQIP has compared favorably with single-institution morbidity and mortality conference systems,¹² multi-institution clinical databases,¹³ and administrative databases¹⁴ in accurately capturing 30-day outcomes. Unlike other databases, outcomes are recorded within 30 days even if they occur after the initial postoperative discharge. Comanagement is a dedicated variable in the NSQIP hip fracture dataset.

This study sought to examine the effect of medical comanagement on perioperative outcomes in this contemporary NSQIP database.

 

METHODS

This study was exempt from the Institutional Review Board review because it uses deidentified data.

We used the targeted hip fracture NSQIP PUF for 2016-2017 to examine perioperative outcomes among patients undergoing hip fracture repair and assess the relationship with medical comanagement, which is a dedicated variable in the NSQIP hip fracture database. We included patients in the comanagement cohort if they received comanagement for part or all of their hip fracture hospitalization.

Demographic, comorbidity, and preoperative variables were examined between the two cohorts. Hypoalbuminemia, as a marker of malnutrition and frailty, was defined as a preoperative serum albumin level <3.5 g/dL, which has demonstrated independent predictive value for adverse outcomes in hip fracture patients in the NSQIP.^15,16 Predicted morbidity and mortality rates are calculated as probabilities available for each patient in the PUF based on a NSQIP hierarchical regression analysis of patient-level factors to predict outcomes (eg, not including hospital or provider factors). We also examined the relationship in regard to participation in a standardized hip fracture program (SHFP), which is a multidisciplinary protocolized pathway for hip fracture patients that may include order sets, structured care coordination, involvement of multidisciplinary therapy personnel, and daily milestones and discharge criteria. Participation in an SHFP is recorded in the NSQIP and has demonstrated an association with significantly improved outcomes in this same dataset, the targeted hip fracture PUF.¹⁷

Logistic regression was performed using all baseline variables identified to be significantly different between the cohorts, as well as the following variables with a priori potential importance in predicting membership in the comanagement cohort: admission year, sex, American Society of Anesthesiologists (ASA) physical status ≥4, and participation in an SHFP. Propensity scores were calculated using the significant variables from this model (Table 1) and the abovementioned a priori potential confounders, and then propensity score matching was performed using a greedy matching algorithm (matching ratio 1:1, caliper width = 0.1 pooled standard deviations of the logit of the propensity score) to create comanagement and control cohorts for matched analysis.

The primary outcomes were 30-day mortality and a composite endpoint of major morbidity, including readmission, pulmonary complications (pneumonia, reintubation, prolonged mechanical ventilation, and pulmonary embolism [PE]), septic shock, stroke, myocardial infarction, cardiac arrest, or death. Secondary outcomes included postoperative length of stay, disposition at postoperative day 30, and process compliance measures (proportion of patients allowed to be weight-bearing as tolerated on postoperative day 1, and proportion of patients appropriately prescribed deep venous thrombosis [DVT] prophylaxis for 28 days, proportion of patients appropriately prescribed bone protective medication [eg, vitamin D, bisphosphonates, teriparatide, denosumab, and raloxifene] postoperatively).

Descriptive variables are reported as median (interquartile range) and number (percentage), unless otherwise noted. Continuous outcomes were compared using a Mann–Whitney–Wilcoxon test. Binary outcomes were compared using Fisher’s exact tests (or a Pearson’s Chi-square for more than two response levels) and odds ratios with 95% confidence intervals. Matched pairs binary logistic regression was used to examine the relationship between comanagement and the primary outcomes of mortality and morbidity in the propensity score-matched cohorts, as well as between comanagement and secondary outcomes. Friedman’s test was used for a secondary outcome with more than two response levels (disposition at 30 days). Analyses were performed using SAS (SAS 9.4; SAS Institute, Cary, North Carolina) with a predetermined alpha value of 0.05 to determine statistical significance.

 

RESULTS

A total of 19,896 Hip fracture patients were categorized into a medical comanagement cohort of 17,600 (88.5%) patients and a cohort without comanagement of 2,296 patients (11.5%). Baseline characteristics of the two unadjusted cohorts before propensity score matching are presented in Table 2.

Patients in the comanagement cohort were older and sicker in terms of almost every comorbidity and condition evaluated (Table 2). These differences were also reflected in a higher predicted mortality by the NSQIP hierarchical regression-based equations for mortality (3.5% [1.7%-7.0%] vs 2.5% [0.9%-6.1%], P < .0001) and morbidity (9.1% [6.9%-12.5%] vs 8.5% [6.1%-12.1%], P ≤ .0001). As predicted, the observed, unadjusted rate of death in the comanagement cohort was higher than that in the cohort without comanagement: n = 1,210 (6.9%) vs n = 91 (4.0%), odds ratio (OR) 1.79: 1.44-2.22; P < .0001, as was the unadjusted rate of the composite endpoint of major morbidity: n = 3,425 (19.5%) vs n = 220 (9.6%), OR 2.28: 1.98-2.63, P < .0001. There was no difference in the prevalence of using an SHFP in the comanagement and noncomanagement cohorts (n = 9,441, 53.6% vs n = 1,232, 53.7%, P > .05).

Logistic regression modeling of the probability of membership in the comanagement cohort yielded satisfactory results (convergent model, null hypothesis rejected, area under the curve of the model receiver operating curve [AUROC] = 0.81). Propensity scores were calculated using the significant variables from this model, as detailed in Table 1. Propensity score matching was then performed with excellent results as follows: n = 2,278 of 2,296 (99.2%) potential pairs were successfully matched, residual absolute standardized difference = 0.0039 (99.7% reduction), variance ratio = 1.01. This satisfies the traditional criterion for a satisfactory variable balance in propensity score matching of a standardized difference ≤0.25 and a variance ratio between 0.5 and 2.0. It is also worthy of note that the propensity score matching process successfully eliminated the baseline difference in the NSQIP-predicted probability of mortality (2.7% [1.1%-5.8%] vs 2.5% [0.9%-6.2%], P = .15) and morbidity (8.6% [6.5%-11.7%] vs 8.6% [6.1%-12.2%], P = .80).

The characteristics of the propensity score-matched cohorts (n = 2,278 each) are shown in Table 3. Matching resulted in a satisfactory balance of measurable covariates between the two cohorts, with the exception of small (but statistically significant) differences in the prevalence of hypoalbuminemia and the distribution of fracture type.

The comanagement cohort did not experience superior results for either of the two primary outcomes mortality (OR 1.36: 1.02-1.81; P = .033) or in the composite endpoint of morbidity (OR 1.82: 1.52-2.20; P < .0001). The secondary outcomes of the two cohorts of patients are shown in Table 4. The comanagement cohort did not have superior outcomes in any variable examined, except for a slightly higher proportion of patients who were appropriately prescribed DVT prophylaxis. Despite the prophylaxis, the comanagement cohort did not have a smaller proportion of patients who experienced a DVT or PE.

Post hoc subgroup analysis was performed to assess whether comanagement demonstrated an association with improved outcomes depending on whether patients were or were not treated in an SHFP. This stratified analysis produced the same results as the primary analysis; ie, comanagement was not associated with improved outcomes in either subgroup.

 

DISCUSSION

The primary finding of this study is that even once propensity score matching eliminated nearly all discernible baseline differences between the cohorts of hip fracture patients with and without medical comanagement during their hospitalization, and comanagement was not associated with superior (and in fact was associated with still inferior) perioperative outcomes.

As is evident from the baseline differences shown in Table 2, medical comanagement is utilized in a patient population that has significant comorbidities and adverse patient factors. The NSQIP provides a robust opportunity to remove the effects of these confounding variables because of the richness of variables in the dataset. For instance, some studies used a summary score for patient frailty, which has been an apparent predictor of worse clinical outcomes in this population.^18,19 The NSQIP analyzes each component of the frailty score (diabetic status, history of COPD or current pneumonia, congestive heart failure, hypertension requiring medication, and nonindependent functional status) as well as to add additional variables (eg, low serum albumin level) and propensity score matching on each of these variables individually.

It is also important to note that although prior analyses have demonstrated that SHFPs are associated with better outcomes in this database,¹⁷ comanagement did not correlate with the use of an SHFP, nor did comanagement demonstrate any association with better outcomes in the subgroup who participated in an SHFP or in the subgroup who did not.

This retrospective cohort analysis cannot, of course, demonstrate causation. Several limitations are worth noting. The ability to use any retrospective dataset depends on the quality of the variable definitions and the data quality contained in it. Although the NSQIP has demonstrated high validity and interobserver variability compared with other data sources, some imperfections and heterogeneity (for instance, in the way two different institutions may define comanagement) may be present.

It is important to note that any propensity score-matched analysis incurs the risk of residual/unmeasured confounding, since the power of this technique still depends on the presence of measured variables to match, and no match is ever perfect. For instance, some variables remain imperfectly balanced in the matched cohorts (eg, hypoalbuminemia and fracture type, Table 3). These differences may reach statistical significance because of large sample size without obvious clinical significance, but they illustrate the point that residual confounding may persist. It is also possible that some detection bias is present in the comanagement cohort, if dedicated comanagement personnel are more likely to diagnose complications (eg, pneumonia, PE) that require some clinical suspicion to be identified. We doubt that this plays a dominant role, for the NSQIP is relatively robust to this potential bias because of its rigorous process of relying on a trained clinical reviewer at each site (as opposed, for instance, to using billing codes), and several components of the composite morbidity endpoint (eg, reintubation, prolonged mechanical ventilation, stroke, cardiac arrest, or death) would be difficult to miss even if clinicians have low clinical suspicion or attentiveness. However, some potential remains.

It is also possible that comanagement is applied to sicker patients and functions more as a marker of that population than an intervention that improves results. To take a similar example, past literature has demonstrated a strong association between do-not-resuscitate (DNR) status and adverse outcomes.^20-24 In all likelihood, the DNR status does not directly cause worse outcomes so much as it marks a sick and vulnerable population. Selection bias at the individual patient level may contribute to an association between comanagement and worse outcomes.

Similarly, institutions that routinely apply comanagement may care for a sicker patient population. To this end, institution-level variables may modulate the relationship between comanagement, SHFP participation, and outcomes. Comanagement and SHFP participation may cluster according to the surgeon, the institution, or the patient subtype (eg, ICU vs ward status). Unfortunately, individual hospital and surgeon identifiers are explicitly excluded from the publicly available NSQIP PUF to protect program and patient confidentiality, so that advanced hierarchical modeling techniques cannot explore these relationships with this dataset.

Beyond these limitations, one plausible explanation for the lack of an association between comanagement and improved outcomes is that standardization and other continuous quality improvement processes have already accomplished a great deal, and the addition of comanagement of individual patients is not having an appreciably positive additional impact. Although the acuity and prevalence of comorbidities in the hip fracture population are high, many of their issues may be stereotyped enough that thoughtful, well-designed algorithms and protocols may serve them nearly as well, if not better than individual comanagement.

This admittedly speculative explanation has significant implications for resource utilization and patient care. Medical comanagement involves a heavy investment of time, energy, and money on the part of a second medical team to deliberately duplicate some aspects of daily care with the intended goal of improving patient outcomes. The results of this study may provide motivation for efforts to hybridize or modify the involvement of comanaging physicians and teams—for instance, to guide and refine the creation and revision of SHFP protocols without providing daily comanagement to each individual patient and/or to implement more iterative, continuous process improvement initiatives.²⁵ Our results may also help direct healthcare systems to focus elsewhere in the search for modifiable process and care delivery variables that can move the needle on the significant morbidity and mortality that still exist in this population.

 

Hip fractures are a large source of morbidity and mortality in the United States, with >1.5 million patients affected every year.¹ These patients are primarily older adults with a significant burden of associated medical comorbidities.² The outcomes of nonoperative management are poor with regard to mortality,³ although operative management of hip fractures remains associated with a high rate of morbidity and mortality compared with several other surgical procedures, substantial resources remain devoted to the operative repair of hip fractures and to process improvement strategies for perioperative care.

Medical comanagement involves having a second nonsurgical primary team—often an internist, a hospitalist, a geriatrician, or an anesthesiologist—who would follow the patient during the hip fracture admission, and provide daily care directed toward both the hip fracture and its associated management challenges and the patient’s underlying comorbidities. This includes taking a primary or shared role in daily rounding, writing progress notes, writing orders, managing medications and therapies, disposition planning, and discharge. One argument for this practice has centered around an efficiency proposition for surgeons to spend more of their time operating and less time in these tasks of acute care management. The primary argument, though, for medical comanagement has been an outcomes proposition that frail, elderly patients with significant medical comorbidities benefit from a nonsurgeon’s focused attention to their coexisting medical problems and the interaction with the surgical issues posed by operative intervention for hip fracture. A number of previous studies have demonstrated an association between comanagement and improved perioperative outcomes.^4,5 However, the most convincing improvements in several studies have been process indicators (eg, time from admission to surgery, length of stay, nurse/surgeon satisfaction) without significant differences in mortality or major morbidity.^6-8 Several studies were methodologically limited due to the use of historical controls,^9,10 and several were conducted in focused clinical settings (eg, a single tertiary academic center), leaving uncertainty about external validity for other care environments.^6,7 To our knowledge, comanagement has not been examined in the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) dataset of hip fracture patients.

The NSQIP database offers a unique tool for clinical outcomes research because its variables are prospectively collected by a trained clinical reviewer at each participating site. Data are deidentified and aggregated into a national database, which has grown from 121 participating sites in 2005 to 708 participating sites in 2017 and now contains data on more than 6.6 million patients. The targeted hip fracture participant use file (PUF) adds additional variables and is available beginning with 2016. Internal audits ensure a high level of data reliability.¹¹ The NSQIP has compared favorably with single-institution morbidity and mortality conference systems,¹² multi-institution clinical databases,¹³ and administrative databases¹⁴ in accurately capturing 30-day outcomes. Unlike other databases, outcomes are recorded within 30 days even if they occur after the initial postoperative discharge. Comanagement is a dedicated variable in the NSQIP hip fracture dataset.

This study sought to examine the effect of medical comanagement on perioperative outcomes in this contemporary NSQIP database.

 

METHODS

This study was exempt from the Institutional Review Board review because it uses deidentified data.

We used the targeted hip fracture NSQIP PUF for 2016-2017 to examine perioperative outcomes among patients undergoing hip fracture repair and assess the relationship with medical comanagement, which is a dedicated variable in the NSQIP hip fracture database. We included patients in the comanagement cohort if they received comanagement for part or all of their hip fracture hospitalization.

Demographic, comorbidity, and preoperative variables were examined between the two cohorts. Hypoalbuminemia, as a marker of malnutrition and frailty, was defined as a preoperative serum albumin level <3.5 g/dL, which has demonstrated independent predictive value for adverse outcomes in hip fracture patients in the NSQIP.^15,16 Predicted morbidity and mortality rates are calculated as probabilities available for each patient in the PUF based on a NSQIP hierarchical regression analysis of patient-level factors to predict outcomes (eg, not including hospital or provider factors). We also examined the relationship in regard to participation in a standardized hip fracture program (SHFP), which is a multidisciplinary protocolized pathway for hip fracture patients that may include order sets, structured care coordination, involvement of multidisciplinary therapy personnel, and daily milestones and discharge criteria. Participation in an SHFP is recorded in the NSQIP and has demonstrated an association with significantly improved outcomes in this same dataset, the targeted hip fracture PUF.¹⁷

Logistic regression was performed using all baseline variables identified to be significantly different between the cohorts, as well as the following variables with a priori potential importance in predicting membership in the comanagement cohort: admission year, sex, American Society of Anesthesiologists (ASA) physical status ≥4, and participation in an SHFP. Propensity scores were calculated using the significant variables from this model (Table 1) and the abovementioned a priori potential confounders, and then propensity score matching was performed using a greedy matching algorithm (matching ratio 1:1, caliper width = 0.1 pooled standard deviations of the logit of the propensity score) to create comanagement and control cohorts for matched analysis.

The primary outcomes were 30-day mortality and a composite endpoint of major morbidity, including readmission, pulmonary complications (pneumonia, reintubation, prolonged mechanical ventilation, and pulmonary embolism [PE]), septic shock, stroke, myocardial infarction, cardiac arrest, or death. Secondary outcomes included postoperative length of stay, disposition at postoperative day 30, and process compliance measures (proportion of patients allowed to be weight-bearing as tolerated on postoperative day 1, and proportion of patients appropriately prescribed deep venous thrombosis [DVT] prophylaxis for 28 days, proportion of patients appropriately prescribed bone protective medication [eg, vitamin D, bisphosphonates, teriparatide, denosumab, and raloxifene] postoperatively).

Descriptive variables are reported as median (interquartile range) and number (percentage), unless otherwise noted. Continuous outcomes were compared using a Mann–Whitney–Wilcoxon test. Binary outcomes were compared using Fisher’s exact tests (or a Pearson’s Chi-square for more than two response levels) and odds ratios with 95% confidence intervals. Matched pairs binary logistic regression was used to examine the relationship between comanagement and the primary outcomes of mortality and morbidity in the propensity score-matched cohorts, as well as between comanagement and secondary outcomes. Friedman’s test was used for a secondary outcome with more than two response levels (disposition at 30 days). Analyses were performed using SAS (SAS 9.4; SAS Institute, Cary, North Carolina) with a predetermined alpha value of 0.05 to determine statistical significance.

 

RESULTS

A total of 19,896 Hip fracture patients were categorized into a medical comanagement cohort of 17,600 (88.5%) patients and a cohort without comanagement of 2,296 patients (11.5%). Baseline characteristics of the two unadjusted cohorts before propensity score matching are presented in Table 2.

Patients in the comanagement cohort were older and sicker in terms of almost every comorbidity and condition evaluated (Table 2). These differences were also reflected in a higher predicted mortality by the NSQIP hierarchical regression-based equations for mortality (3.5% [1.7%-7.0%] vs 2.5% [0.9%-6.1%], P < .0001) and morbidity (9.1% [6.9%-12.5%] vs 8.5% [6.1%-12.1%], P ≤ .0001). As predicted, the observed, unadjusted rate of death in the comanagement cohort was higher than that in the cohort without comanagement: n = 1,210 (6.9%) vs n = 91 (4.0%), odds ratio (OR) 1.79: 1.44-2.22; P < .0001, as was the unadjusted rate of the composite endpoint of major morbidity: n = 3,425 (19.5%) vs n = 220 (9.6%), OR 2.28: 1.98-2.63, P < .0001. There was no difference in the prevalence of using an SHFP in the comanagement and noncomanagement cohorts (n = 9,441, 53.6% vs n = 1,232, 53.7%, P > .05).

Logistic regression modeling of the probability of membership in the comanagement cohort yielded satisfactory results (convergent model, null hypothesis rejected, area under the curve of the model receiver operating curve [AUROC] = 0.81). Propensity scores were calculated using the significant variables from this model, as detailed in Table 1. Propensity score matching was then performed with excellent results as follows: n = 2,278 of 2,296 (99.2%) potential pairs were successfully matched, residual absolute standardized difference = 0.0039 (99.7% reduction), variance ratio = 1.01. This satisfies the traditional criterion for a satisfactory variable balance in propensity score matching of a standardized difference ≤0.25 and a variance ratio between 0.5 and 2.0. It is also worthy of note that the propensity score matching process successfully eliminated the baseline difference in the NSQIP-predicted probability of mortality (2.7% [1.1%-5.8%] vs 2.5% [0.9%-6.2%], P = .15) and morbidity (8.6% [6.5%-11.7%] vs 8.6% [6.1%-12.2%], P = .80).

The characteristics of the propensity score-matched cohorts (n = 2,278 each) are shown in Table 3. Matching resulted in a satisfactory balance of measurable covariates between the two cohorts, with the exception of small (but statistically significant) differences in the prevalence of hypoalbuminemia and the distribution of fracture type.

The comanagement cohort did not experience superior results for either of the two primary outcomes mortality (OR 1.36: 1.02-1.81; P = .033) or in the composite endpoint of morbidity (OR 1.82: 1.52-2.20; P < .0001). The secondary outcomes of the two cohorts of patients are shown in Table 4. The comanagement cohort did not have superior outcomes in any variable examined, except for a slightly higher proportion of patients who were appropriately prescribed DVT prophylaxis. Despite the prophylaxis, the comanagement cohort did not have a smaller proportion of patients who experienced a DVT or PE.

Post hoc subgroup analysis was performed to assess whether comanagement demonstrated an association with improved outcomes depending on whether patients were or were not treated in an SHFP. This stratified analysis produced the same results as the primary analysis; ie, comanagement was not associated with improved outcomes in either subgroup.

 

DISCUSSION

The primary finding of this study is that even once propensity score matching eliminated nearly all discernible baseline differences between the cohorts of hip fracture patients with and without medical comanagement during their hospitalization, and comanagement was not associated with superior (and in fact was associated with still inferior) perioperative outcomes.

As is evident from the baseline differences shown in Table 2, medical comanagement is utilized in a patient population that has significant comorbidities and adverse patient factors. The NSQIP provides a robust opportunity to remove the effects of these confounding variables because of the richness of variables in the dataset. For instance, some studies used a summary score for patient frailty, which has been an apparent predictor of worse clinical outcomes in this population.^18,19 The NSQIP analyzes each component of the frailty score (diabetic status, history of COPD or current pneumonia, congestive heart failure, hypertension requiring medication, and nonindependent functional status) as well as to add additional variables (eg, low serum albumin level) and propensity score matching on each of these variables individually.

It is also important to note that although prior analyses have demonstrated that SHFPs are associated with better outcomes in this database,¹⁷ comanagement did not correlate with the use of an SHFP, nor did comanagement demonstrate any association with better outcomes in the subgroup who participated in an SHFP or in the subgroup who did not.

This retrospective cohort analysis cannot, of course, demonstrate causation. Several limitations are worth noting. The ability to use any retrospective dataset depends on the quality of the variable definitions and the data quality contained in it. Although the NSQIP has demonstrated high validity and interobserver variability compared with other data sources, some imperfections and heterogeneity (for instance, in the way two different institutions may define comanagement) may be present.

It is important to note that any propensity score-matched analysis incurs the risk of residual/unmeasured confounding, since the power of this technique still depends on the presence of measured variables to match, and no match is ever perfect. For instance, some variables remain imperfectly balanced in the matched cohorts (eg, hypoalbuminemia and fracture type, Table 3). These differences may reach statistical significance because of large sample size without obvious clinical significance, but they illustrate the point that residual confounding may persist. It is also possible that some detection bias is present in the comanagement cohort, if dedicated comanagement personnel are more likely to diagnose complications (eg, pneumonia, PE) that require some clinical suspicion to be identified. We doubt that this plays a dominant role, for the NSQIP is relatively robust to this potential bias because of its rigorous process of relying on a trained clinical reviewer at each site (as opposed, for instance, to using billing codes), and several components of the composite morbidity endpoint (eg, reintubation, prolonged mechanical ventilation, stroke, cardiac arrest, or death) would be difficult to miss even if clinicians have low clinical suspicion or attentiveness. However, some potential remains.

It is also possible that comanagement is applied to sicker patients and functions more as a marker of that population than an intervention that improves results. To take a similar example, past literature has demonstrated a strong association between do-not-resuscitate (DNR) status and adverse outcomes.^20-24 In all likelihood, the DNR status does not directly cause worse outcomes so much as it marks a sick and vulnerable population. Selection bias at the individual patient level may contribute to an association between comanagement and worse outcomes.

Similarly, institutions that routinely apply comanagement may care for a sicker patient population. To this end, institution-level variables may modulate the relationship between comanagement, SHFP participation, and outcomes. Comanagement and SHFP participation may cluster according to the surgeon, the institution, or the patient subtype (eg, ICU vs ward status). Unfortunately, individual hospital and surgeon identifiers are explicitly excluded from the publicly available NSQIP PUF to protect program and patient confidentiality, so that advanced hierarchical modeling techniques cannot explore these relationships with this dataset.

Beyond these limitations, one plausible explanation for the lack of an association between comanagement and improved outcomes is that standardization and other continuous quality improvement processes have already accomplished a great deal, and the addition of comanagement of individual patients is not having an appreciably positive additional impact. Although the acuity and prevalence of comorbidities in the hip fracture population are high, many of their issues may be stereotyped enough that thoughtful, well-designed algorithms and protocols may serve them nearly as well, if not better than individual comanagement.

This admittedly speculative explanation has significant implications for resource utilization and patient care. Medical comanagement involves a heavy investment of time, energy, and money on the part of a second medical team to deliberately duplicate some aspects of daily care with the intended goal of improving patient outcomes. The results of this study may provide motivation for efforts to hybridize or modify the involvement of comanaging physicians and teams—for instance, to guide and refine the creation and revision of SHFP protocols without providing daily comanagement to each individual patient and/or to implement more iterative, continuous process improvement initiatives.²⁵ Our results may also help direct healthcare systems to focus elsewhere in the search for modifiable process and care delivery variables that can move the needle on the significant morbidity and mortality that still exist in this population.

 

Hip fractures are a large source of morbidity and mortality in the United States, with >1.5 million patients affected every year.¹ These patients are primarily older adults with a significant burden of associated medical comorbidities.² The outcomes of nonoperative management are poor with regard to mortality,³ although operative management of hip fractures remains associated with a high rate of morbidity and mortality compared with several other surgical procedures, substantial resources remain devoted to the operative repair of hip fractures and to process improvement strategies for perioperative care.

Medical comanagement involves having a second nonsurgical primary team—often an internist, a hospitalist, a geriatrician, or an anesthesiologist—who would follow the patient during the hip fracture admission, and provide daily care directed toward both the hip fracture and its associated management challenges and the patient’s underlying comorbidities. This includes taking a primary or shared role in daily rounding, writing progress notes, writing orders, managing medications and therapies, disposition planning, and discharge. One argument for this practice has centered around an efficiency proposition for surgeons to spend more of their time operating and less time in these tasks of acute care management. The primary argument, though, for medical comanagement has been an outcomes proposition that frail, elderly patients with significant medical comorbidities benefit from a nonsurgeon’s focused attention to their coexisting medical problems and the interaction with the surgical issues posed by operative intervention for hip fracture. A number of previous studies have demonstrated an association between comanagement and improved perioperative outcomes.^4,5 However, the most convincing improvements in several studies have been process indicators (eg, time from admission to surgery, length of stay, nurse/surgeon satisfaction) without significant differences in mortality or major morbidity.^6-8 Several studies were methodologically limited due to the use of historical controls,^9,10 and several were conducted in focused clinical settings (eg, a single tertiary academic center), leaving uncertainty about external validity for other care environments.^6,7 To our knowledge, comanagement has not been examined in the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) dataset of hip fracture patients.

The NSQIP database offers a unique tool for clinical outcomes research because its variables are prospectively collected by a trained clinical reviewer at each participating site. Data are deidentified and aggregated into a national database, which has grown from 121 participating sites in 2005 to 708 participating sites in 2017 and now contains data on more than 6.6 million patients. The targeted hip fracture participant use file (PUF) adds additional variables and is available beginning with 2016. Internal audits ensure a high level of data reliability.¹¹ The NSQIP has compared favorably with single-institution morbidity and mortality conference systems,¹² multi-institution clinical databases,¹³ and administrative databases¹⁴ in accurately capturing 30-day outcomes. Unlike other databases, outcomes are recorded within 30 days even if they occur after the initial postoperative discharge. Comanagement is a dedicated variable in the NSQIP hip fracture dataset.

This study sought to examine the effect of medical comanagement on perioperative outcomes in this contemporary NSQIP database.

 

METHODS

This study was exempt from the Institutional Review Board review because it uses deidentified data.

We used the targeted hip fracture NSQIP PUF for 2016-2017 to examine perioperative outcomes among patients undergoing hip fracture repair and assess the relationship with medical comanagement, which is a dedicated variable in the NSQIP hip fracture database. We included patients in the comanagement cohort if they received comanagement for part or all of their hip fracture hospitalization.

Demographic, comorbidity, and preoperative variables were examined between the two cohorts. Hypoalbuminemia, as a marker of malnutrition and frailty, was defined as a preoperative serum albumin level <3.5 g/dL, which has demonstrated independent predictive value for adverse outcomes in hip fracture patients in the NSQIP.^15,16 Predicted morbidity and mortality rates are calculated as probabilities available for each patient in the PUF based on a NSQIP hierarchical regression analysis of patient-level factors to predict outcomes (eg, not including hospital or provider factors). We also examined the relationship in regard to participation in a standardized hip fracture program (SHFP), which is a multidisciplinary protocolized pathway for hip fracture patients that may include order sets, structured care coordination, involvement of multidisciplinary therapy personnel, and daily milestones and discharge criteria. Participation in an SHFP is recorded in the NSQIP and has demonstrated an association with significantly improved outcomes in this same dataset, the targeted hip fracture PUF.¹⁷

Logistic regression was performed using all baseline variables identified to be significantly different between the cohorts, as well as the following variables with a priori potential importance in predicting membership in the comanagement cohort: admission year, sex, American Society of Anesthesiologists (ASA) physical status ≥4, and participation in an SHFP. Propensity scores were calculated using the significant variables from this model (Table 1) and the abovementioned a priori potential confounders, and then propensity score matching was performed using a greedy matching algorithm (matching ratio 1:1, caliper width = 0.1 pooled standard deviations of the logit of the propensity score) to create comanagement and control cohorts for matched analysis.

The primary outcomes were 30-day mortality and a composite endpoint of major morbidity, including readmission, pulmonary complications (pneumonia, reintubation, prolonged mechanical ventilation, and pulmonary embolism [PE]), septic shock, stroke, myocardial infarction, cardiac arrest, or death. Secondary outcomes included postoperative length of stay, disposition at postoperative day 30, and process compliance measures (proportion of patients allowed to be weight-bearing as tolerated on postoperative day 1, and proportion of patients appropriately prescribed deep venous thrombosis [DVT] prophylaxis for 28 days, proportion of patients appropriately prescribed bone protective medication [eg, vitamin D, bisphosphonates, teriparatide, denosumab, and raloxifene] postoperatively).

Descriptive variables are reported as median (interquartile range) and number (percentage), unless otherwise noted. Continuous outcomes were compared using a Mann–Whitney–Wilcoxon test. Binary outcomes were compared using Fisher’s exact tests (or a Pearson’s Chi-square for more than two response levels) and odds ratios with 95% confidence intervals. Matched pairs binary logistic regression was used to examine the relationship between comanagement and the primary outcomes of mortality and morbidity in the propensity score-matched cohorts, as well as between comanagement and secondary outcomes. Friedman’s test was used for a secondary outcome with more than two response levels (disposition at 30 days). Analyses were performed using SAS (SAS 9.4; SAS Institute, Cary, North Carolina) with a predetermined alpha value of 0.05 to determine statistical significance.

 

RESULTS

A total of 19,896 Hip fracture patients were categorized into a medical comanagement cohort of 17,600 (88.5%) patients and a cohort without comanagement of 2,296 patients (11.5%). Baseline characteristics of the two unadjusted cohorts before propensity score matching are presented in Table 2.

Patients in the comanagement cohort were older and sicker in terms of almost every comorbidity and condition evaluated (Table 2). These differences were also reflected in a higher predicted mortality by the NSQIP hierarchical regression-based equations for mortality (3.5% [1.7%-7.0%] vs 2.5% [0.9%-6.1%], P < .0001) and morbidity (9.1% [6.9%-12.5%] vs 8.5% [6.1%-12.1%], P ≤ .0001). As predicted, the observed, unadjusted rate of death in the comanagement cohort was higher than that in the cohort without comanagement: n = 1,210 (6.9%) vs n = 91 (4.0%), odds ratio (OR) 1.79: 1.44-2.22; P < .0001, as was the unadjusted rate of the composite endpoint of major morbidity: n = 3,425 (19.5%) vs n = 220 (9.6%), OR 2.28: 1.98-2.63, P < .0001. There was no difference in the prevalence of using an SHFP in the comanagement and noncomanagement cohorts (n = 9,441, 53.6% vs n = 1,232, 53.7%, P > .05).

Logistic regression modeling of the probability of membership in the comanagement cohort yielded satisfactory results (convergent model, null hypothesis rejected, area under the curve of the model receiver operating curve [AUROC] = 0.81). Propensity scores were calculated using the significant variables from this model, as detailed in Table 1. Propensity score matching was then performed with excellent results as follows: n = 2,278 of 2,296 (99.2%) potential pairs were successfully matched, residual absolute standardized difference = 0.0039 (99.7% reduction), variance ratio = 1.01. This satisfies the traditional criterion for a satisfactory variable balance in propensity score matching of a standardized difference ≤0.25 and a variance ratio between 0.5 and 2.0. It is also worthy of note that the propensity score matching process successfully eliminated the baseline difference in the NSQIP-predicted probability of mortality (2.7% [1.1%-5.8%] vs 2.5% [0.9%-6.2%], P = .15) and morbidity (8.6% [6.5%-11.7%] vs 8.6% [6.1%-12.2%], P = .80).

The characteristics of the propensity score-matched cohorts (n = 2,278 each) are shown in Table 3. Matching resulted in a satisfactory balance of measurable covariates between the two cohorts, with the exception of small (but statistically significant) differences in the prevalence of hypoalbuminemia and the distribution of fracture type.

The comanagement cohort did not experience superior results for either of the two primary outcomes mortality (OR 1.36: 1.02-1.81; P = .033) or in the composite endpoint of morbidity (OR 1.82: 1.52-2.20; P < .0001). The secondary outcomes of the two cohorts of patients are shown in Table 4. The comanagement cohort did not have superior outcomes in any variable examined, except for a slightly higher proportion of patients who were appropriately prescribed DVT prophylaxis. Despite the prophylaxis, the comanagement cohort did not have a smaller proportion of patients who experienced a DVT or PE.

Post hoc subgroup analysis was performed to assess whether comanagement demonstrated an association with improved outcomes depending on whether patients were or were not treated in an SHFP. This stratified analysis produced the same results as the primary analysis; ie, comanagement was not associated with improved outcomes in either subgroup.

 

DISCUSSION

The primary finding of this study is that even once propensity score matching eliminated nearly all discernible baseline differences between the cohorts of hip fracture patients with and without medical comanagement during their hospitalization, and comanagement was not associated with superior (and in fact was associated with still inferior) perioperative outcomes.

As is evident from the baseline differences shown in Table 2, medical comanagement is utilized in a patient population that has significant comorbidities and adverse patient factors. The NSQIP provides a robust opportunity to remove the effects of these confounding variables because of the richness of variables in the dataset. For instance, some studies used a summary score for patient frailty, which has been an apparent predictor of worse clinical outcomes in this population.^18,19 The NSQIP analyzes each component of the frailty score (diabetic status, history of COPD or current pneumonia, congestive heart failure, hypertension requiring medication, and nonindependent functional status) as well as to add additional variables (eg, low serum albumin level) and propensity score matching on each of these variables individually.

It is also important to note that although prior analyses have demonstrated that SHFPs are associated with better outcomes in this database,¹⁷ comanagement did not correlate with the use of an SHFP, nor did comanagement demonstrate any association with better outcomes in the subgroup who participated in an SHFP or in the subgroup who did not.

This retrospective cohort analysis cannot, of course, demonstrate causation. Several limitations are worth noting. The ability to use any retrospective dataset depends on the quality of the variable definitions and the data quality contained in it. Although the NSQIP has demonstrated high validity and interobserver variability compared with other data sources, some imperfections and heterogeneity (for instance, in the way two different institutions may define comanagement) may be present.

It is important to note that any propensity score-matched analysis incurs the risk of residual/unmeasured confounding, since the power of this technique still depends on the presence of measured variables to match, and no match is ever perfect. For instance, some variables remain imperfectly balanced in the matched cohorts (eg, hypoalbuminemia and fracture type, Table 3). These differences may reach statistical significance because of large sample size without obvious clinical significance, but they illustrate the point that residual confounding may persist. It is also possible that some detection bias is present in the comanagement cohort, if dedicated comanagement personnel are more likely to diagnose complications (eg, pneumonia, PE) that require some clinical suspicion to be identified. We doubt that this plays a dominant role, for the NSQIP is relatively robust to this potential bias because of its rigorous process of relying on a trained clinical reviewer at each site (as opposed, for instance, to using billing codes), and several components of the composite morbidity endpoint (eg, reintubation, prolonged mechanical ventilation, stroke, cardiac arrest, or death) would be difficult to miss even if clinicians have low clinical suspicion or attentiveness. However, some potential remains.

It is also possible that comanagement is applied to sicker patients and functions more as a marker of that population than an intervention that improves results. To take a similar example, past literature has demonstrated a strong association between do-not-resuscitate (DNR) status and adverse outcomes.^20-24 In all likelihood, the DNR status does not directly cause worse outcomes so much as it marks a sick and vulnerable population. Selection bias at the individual patient level may contribute to an association between comanagement and worse outcomes.

Similarly, institutions that routinely apply comanagement may care for a sicker patient population. To this end, institution-level variables may modulate the relationship between comanagement, SHFP participation, and outcomes. Comanagement and SHFP participation may cluster according to the surgeon, the institution, or the patient subtype (eg, ICU vs ward status). Unfortunately, individual hospital and surgeon identifiers are explicitly excluded from the publicly available NSQIP PUF to protect program and patient confidentiality, so that advanced hierarchical modeling techniques cannot explore these relationships with this dataset.

Beyond these limitations, one plausible explanation for the lack of an association between comanagement and improved outcomes is that standardization and other continuous quality improvement processes have already accomplished a great deal, and the addition of comanagement of individual patients is not having an appreciably positive additional impact. Although the acuity and prevalence of comorbidities in the hip fracture population are high, many of their issues may be stereotyped enough that thoughtful, well-designed algorithms and protocols may serve them nearly as well, if not better than individual comanagement.

This admittedly speculative explanation has significant implications for resource utilization and patient care. Medical comanagement involves a heavy investment of time, energy, and money on the part of a second medical team to deliberately duplicate some aspects of daily care with the intended goal of improving patient outcomes. The results of this study may provide motivation for efforts to hybridize or modify the involvement of comanaging physicians and teams—for instance, to guide and refine the creation and revision of SHFP protocols without providing daily comanagement to each individual patient and/or to implement more iterative, continuous process improvement initiatives.²⁵ Our results may also help direct healthcare systems to focus elsewhere in the search for modifiable process and care delivery variables that can move the needle on the significant morbidity and mortality that still exist in this population.

 

Introduction

The development of new cancer therapies relies on the successful development and completion of clinical trials. While clinical trials have led to significant improvements in cancer treatment, the success is dependent upon patient enrollment and participation. Unfortunately, fewer than 5% of adult patients enroll in trials.^1-3 This represents a significant barrier to the development and approval of new cancer treatments. Reasons for low accrual into trials are multifactorial, but include structural barriers (eg, clinic access), clinical barriers (eg, eligibility criteria), and physician and patient attitudes towards trial enrollment.^4,5 One study at the University of California Davis Cancer Center reported 49% of patients declined participation despite meeting eligibility criteria,^3,6 suggesting that psychosocial barriers such as knowledge of trials and attitudes towards clinical research are a major impediment to accrual.^7-9

Bone and soft tissue sarcoma represent a heterogeneous group of tumors of mesenchymal origin that are an important cause of morbidity and mortality. Local disease is often treated with a multidisciplinary approach including surgery, radiation, and systemic therapy. Metastatic disease is predominantly treated palliatively with systemic therapy.¹⁰ Given its rarity and heterogeneity, trial accrual is of particular importance in sarcoma and often requires multiple sites to enroll adequate numbers of patients. While sarcoma represents <1% of adult malignancies overall, it constitutes ~15% of malignancies in the adolescent and young adult (AYA) population (15- 39 years old).^11,12 Sarcoma represents a patient population in which low trial accrual has been correlated with lack of progress in cancer-related outcomes in both the adult and AYA populations.¹³ The reasons for low accrual rates among patients with sarcoma are poorly understood.

Sarcomas represent a molecularly and biologically heterogeneous group of malignancies with over 100 different subtypes.¹² As a result, there has been significant interest in performing molecular profiling, or genetic sequencing, to identify “targetable” mutations. Targetable mutations refer to a specific genetic change identified within the tumor molecular profile for which there is a specific drug that may demonstrate activity against a particular tumor. Given the widespread utilization of this technology in sarcoma, identifying and understanding patient perceptions with regard to molecular profiling is critically important in this disease.¹⁴

In this study, we use a cross-sectional design to describe patient perceptions of trial enrollment among patients with bone and soft tissue sarcoma through validated measures, including attitudes towards clinical trials, knowledge of clinical trials, and perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about clinical trial participation, receptivity to learning more about clinical trials, and willingness to participate in clinical trials.6 In addition, we describe this patient cohort’s perceptions of molecular profiling, as current and future trials are increasingly driven by molecular or other biomarkers.

Methods

This was a cross-sectional electronic survey study of patients with bone and soft tissue sarcoma treated at Northwestern Medicine (NM) over a 5-year period. NM Enterprise Data Warehouse (NMEDW) is a single, comprehensive, and integrated repository of all clinical and research data sources within NM. The study was approved by the Northwestern University Institutional Review Board.

Survey

The investigators designed a self-administered, online survey, which was built using Research Electronic Data Capture (REDCap). The survey consisted of three sections that were answered using skip logic—a custom path through the survey that varied based on patients’ answers: (1) Patient demographic information and trial perceptions (answered by all patients); (2) Thoughts about molecular profiling (answered by patients who answered “yes” to the question, “Have you heard about molecular profiling of tumors?”); and (3) Considerations to undergo molecular profiling (answered by patients who answered “yes” to the question, “Have you undergone profiling of your cancer?”).

 

Clinical trial perceptions included questions assessing (1) patient knowledge about trials; (2) patient attitudes toward trials; (3) perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about trial participation; (4) receptivity to learning more about trials; and (5) willingness to participate in trials. These outcome measures had been previously developed and pilot tested for reliability and validity (TABLE 1).⁶

Thoughts about molecular profiling of tumors were assessed using nine items (TABLE 1). Of these, items assessing potential benefit or harm of molecular profiling were assessed using a 7-step Likert scale. Items assessing maximal benefit or harm of therapy, importance of quality vs length of life, and concern about the cost of molecular testing were assessed using a 5-step Likert scale. The study team developed and piloted these questions because there is no validated survey assessing these domains.

Considerations to undergo molecular profiling were assessed using 17 items. Items were in response to the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” Responses were assessed using a 5-point Likert scale.

Data Collection

Patients 18 years and older evaluated at NM between November 20, 2012, and November 20, 2017, with a diagnosis of sarcoma were identified by query of the NMEDW by ICD-10 codes (C40, C41.9, C44.99, C45-49, C55, C71.9, D48, D49.9, and M12.20) or equivalent ICD-9 codes. Patients were subsequently excluded if they did not have a diagnosis of bone or soft tissue sarcoma, no e-mail address listed, had died, or had not been evaluated at an NM clinic in the previous 5 years. Patients with a diagnosis of gastrointestinal stromal tumor and Kaposi’s sarcoma were also excluded.

A personalized contact e-mail was sent to patients containing an explanation of the survey and an internet link to the electronic survey through REDCap from January 2018 to March 2018. If patients did not respond to the survey, two follow-up reminder e-mails were sent 2 and 4 days following the initial survey. The link was protected so that each patient could complete the survey only once. Responses were collected through the REDCap platform. Patients read and signed an electronic consent form prior to completing the survey.

Upon completion of the survey, patients were offered a $50 VISA gift card as compensation, with an option to donate their compensation to the Robert H. Lurie Comprehensive Cancer Center Sarcoma Research Fund.

Over the described survey period, open clinical trials for patients with bone and soft tissue sarcoma available at NM were evaluated. The number of patients screened and accrued to each trial were recorded.

 

Statistical analysis

Responses were separated from the personal data for complete anonymization. Descriptive statistical analysis was performed for demographics and disease variables and were summarized using frequencies and percentages. Median and range were used for age. Correlations between continuous variables were analyzed using Spearman correlations. Scores were compared between subgroups using the Mann-Whitney test. Descriptive statistics for knowledge, attitude, and ability scores include means and 95% confidence intervals. Correlations were interpreted as small (r=0.10), medium (r=0.30), or large (r=0.50).15 Statistical significance was indicated when P<0.05.

Results

Patients

Seven hundred fifty patients were eligible to participate in the survey and received the initial and two follow-up e-mails. Twenty e-mailed surveys bounced back. Three hundred nine patients opened the initial e-mail and 283 patients (37.7% of total and 91.6% of opened) completed at least a portion of the survey, with 182 patients completing the entire survey (FIGURE 1). Data for analysis were used from patients who completed at least a portion of the survey.

Baseline characteristics of patients who responded can be seen in TABLE 2. Patients had a median age of 56, the majority were female (59.4%), white (88.2%), and most had college or university graduate degrees or higher educational level (69.0%). Patients had various different histological subtypes, with the most common being liposarcoma (16.5%) and leiomyosarcoma (16.0%). Slightly more than a quarter (26.8%) of patients had metastatic disease, and 84.2% had never been enrolled in a clinical trial. Previous treatments included surgery (91.1%), radiation (53.2%), and chemotherapy (51.6%). Prior to completing the survey, 85.4% reported being receptive to a cancer clinical trial, while 60.7% of patients reported willingness to participate in a clinical trial.

 

Knowledge, attitudes, and perceived ability

A statistically significant correlation was observed between greater knowledge of trials and more positive attitudes towards trials (P<0.001; r=0.5, FIGURE 2A). In relating patient attitudes with perceived ability, again a significant correlation was seen (P<0.001; r=0.4, FIGURE 2B). In contrast, knowledge had a weak correlation with perceived ability (P=0.024; r=0.2, FIGURE 2C). There was no difference regarding patient knowledge, attitudes, or perceived ability by age, gender, race, or income.

Knowledge, attitudes, perceived ability, and clinical trial enrollment

Thirty patients reported clinical trial experience (either previously or currently enrolled in trials) and 160 patients were never enrolled. Of the 30 patients with trial experience, 7 reported being currently enrolled, while 23 reported previous enrollment. Of these patients, 16 had metastatic disease, while 12 had non-metastatic disease, and 2 were unsure whether or not they had metastatic disease.

Patients with previous clinical trial exposure (currently or previously enrolled in clinical trials) demonstrated significantly greater trial knowledge, with a mean knowledge score of 9.3 (CI 8.5-10.0) compared with 7.7 (CI 7.3-8.1) among patients without trial exposure (P=0.002; FIGURE 3A). Similarly, patients with trial experience also had statistically significant more positive attitudes towards trials as compared with patients with no trial experience, with a mean attitude score of 3.8 (CI 3.6-4.0) and 3.5 (CI 3.4-3.6), respectively (P=0.001; FIGURE 3B). While numerically patients with trial experience have greater perceived ability compared with patients with no trial experience, with a mean score of 4.4 (CI 4.2-4.6) and 4.2 (CI 4.1-4.3), respectively, this difference did not reach statistical significance (FIGURE 3C).

Knowledge, attitudes, perceived ability, and disease stage

An analysis was performed comparing patients with metastatic vs non-metastatic disease. It was observed that patients with metastatic disease had similar knowledge of trials compared with non-metastatic patients, with a mean knowledge score of 8.4 (CI 7.7- 9.1) and 7.9 (CI 7.5-8.4), respectively, (P=0.3; FIGURE 4A). In contrast, patients with metastatic disease had more positive attitudes compared with non-metastatic patients, with a mean score of 3.7 (CI 3.5-3.8) and 3.5 (CI 3.4-3.6), respectively, which was statistically significant (P=0.03; FIGURE 4B). There was no difference in perceived ability in metastatic vs non-metastatic patients (FIGURE 4C).

Thoughts about molecular profiling

Of the total number of patients, 46 patients had heard of molecular profiling and were presented with questions regarding their thoughts (TABLE 3). Approximately two-thirds (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their tumor molecular profile. A majority (71.7%) of patients thought that a new experimental therapy chosen based on a patient’s tumor molecular profile would have at least a 50% chance of controlling the cancer. Somewhat less than a third (30.4%) of patients thought that total cure is the maximal benefit a patient could experience as a result of a treatment on a clinical trial using a drug chosen based on molecular tests. About half (52.2%) of patients agreed with the statement, “I am concerned about the cost of the test to molecularly profile my cancer.”

Considerations to undergo molecular profiling

Eighteen patients had undergone molecular profiling of their tumor. These patients were posed the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” (TABLE 4). A majority (83.3%) of patients stated that wanting to live as long as possible was important, and 72.2% of patients stated that quality of life was important. A majority (83.3%) of patients stated that hope for a cure was an extremely or quite a bit important consideration. Helping future cancer patients was extremely or quite a bit important for 77.8% of patients, while wanting to be a part of research was not at all or of little importance in 50.0% of patients.

Clinical trials at NM

Twenty-four clinical trials were available at NM between the years 2012 and 2017 for patients with bone and soft tissue sarcoma. Of these trials, 3 of 24 were for non-metastatic patients, while the remaining 21 were open only to metastatic patients. The median number of patients screened per trial was 11 (range 0-66) and the median number of patients accrued per trial was 9 (range 0-58). Of the 24 trials, 17 were not subtype specific (13 included soft tissue sarcoma alone while 4 included both bone and soft tissue sarcoma). The remaining 7 trials were sarcoma subtype specific (eg, angiosarcoma, liposarcoma, etc). Trials available at NM during this period are included in TABLE 5. There were 318 patients screened and 262 patients accrued to sarcoma trials over this time period, with a screen failure rate of 17.6% overall.

Discussion

Our study sought to describe perceptions of clinical trial enrollment among patients with bone and soft tissue sarcoma in order to elucidate and overcome barriers to enrollment, which to the best of our knowledge had not been previously described. Using previously validated patient- reported outcomes in the literature,⁶ our data reveal a correlation between knowledge of trials and more positive attitudes towards trials. This underscores the importance of awareness and educational strategies in this cancer population as a whole. Interventions should focus on patient perceptions that contribute to lack of participation, such as fear of side effects, loss of control (eg, idea of placebo or randomization), logistical challenges (eg, additional time or convenient location), and cost.^3,5,7,16,17 For example, patients concerned about randomization should be educated on equipoise and other ethical considerations in trial design.⁵ Previous research has suggested that a multimedia psychoeducational intervention was effective in improving attitudes toward trials.⁶ Educating patients on the essential role of trials in oncology care, as demonstrated by the vast number of new drug approvals in recent years, is an essential strategy to improve attitudes, and subsequently leads to higher patient accrual rates. 

 

In our study, both knowledge and at titudes were increased in patients with previous trial exposure. This suggests that either patients with greater knowledge and more positive attitudes are more likely to enroll in trials, or that patients with direct trial exposure are more knowledgeable and develop more positive attitudes. Our patient population was overall receptive to learning more about clinical trials (85.4%) and willing to participate (65.8%). At the same time, our study demonstrated low to medium correlations between attitudes and perceived ability to take steps towards making an informed decision to enroll in a trial (r=0.4), which may partially be explained by the absence of a tangible trial opportunity. While we did not assess specifically whether patients in our study were offered a trial, there was a substantial trial menu at NM with limited screen failures and decent trial accrual over the time frame of our study. This underscores the importance not only of patient-focused strategies to increase educational and attitudinal resources, but also a need to focus on research-site optimization that includes opening of multiple trials in various settings, systematic pre-screening of patients, and eligibility criteria that are inclusive and rational.⁵

The patient population with metastatic disease demonstrated more positive attitudes towards enrolling in clinical trials. This cohort accrued well to clinical trials, with 21 of 24 trials enrolling specifically patients with metastatic disease. Of the patients who responded to our survey, patients with previous trial exposure were enriched for patients with metastatic disease (53.3% metastatic among previous trial exposure versus 26.8% metastatic overall). These observations are likely reflective of the need for novel therapies in this disease setting. At the same time, approximately 25% of patients with localized soft tissue sarcoma will develop distant metastatic disease after successful treatment of their primary tumor, which increases to 40% to 50% in larger and higher-grade tumors.¹⁸ Three of 24 trials were open for patients with non-metastatic disease, of which one managed to accrue patients. Patients with non-metastatic disease had more negative attitudes towards trial enrollment. These disproportionate findings suggest a need for interventions to increase patient awareness and attitudes towards trial enrollment among this patient population and the importance of research-site optimization for trial opportunities across disease states.

Molecular profiling of tumors and biomarker identification has become a critical component of further characterizing cancer subtypes. In our study, a majority (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their molecular profile. Molecular data on 5,749 bone and soft tissue sarcomas suggested that 9.5% of tumors demonstrate a “targetable result,” defined as a new molecular finding for which there is an FDA-approved drug for malignancies other than sarcoma (eg, BRAF V600E, Her2, etc.),¹⁹ suggesting an overestimation in our patient cohort of the likelihood of benefit of molecular profiling. These results highlight that the growing use of molecular profiling has increased the need for educational and supportive resources to help patients understand the utility of molecular profiling and aid in shared decision-making surrounding the results.

At the same time, the importance of identifying a targetable mutation in patients with sarcoma cannot be understated. As a recent example of this paradigm, tumors that harbor fusions with the neurotrophic receptor tyrosine kinase 1, 2, or 3 (NTRK1, 2, and 3) have a high response rate (~75%) to drugs that target these fusions, such as larotrectinib and entrectinib.¹³ Molecular profiling and identification of predictive biomarkers in small patient subsets has led to great challenges in trial design and research-site optimization. Novel designs that incorporate molecular profiling,²⁰ such as the Lung- MAP trial²¹ and NCI’s Molecular Analysis for Therapy Choice (MATCH) trial,²² are emerging to identify new therapies for small patient subsets. As a rare and increasingly heterogeneous cancer, sarcoma represents a paradigm to provide insight into optimizing patient perceptions and research enterprises to maximize clinical trial enrollment. 

Some limitations of our study include a homogeneous and selected patient population that was predominantly Caucasian and highly educated. Therefore, these findings should not be extrapolated to other populations with barriers to trial accrual, such as lower socioeconomic or minority populations. The low response rate and failure of some to complete the survey may have introduced some bias. Additionally, our data include self-reported outcomes, which could have affected our results. Finally, the limited number of patients who had undergone or heard of molecular profiling limited our ability to draw definitive conclusions, and should be assessed in larger patient cohorts.

While our paper addresses a unique population—the sarcoma patient—similar themes and issues pertain to all oncology patients. A recent review was published in the American Society of Clinical Oncology Educational Book²³ looking at methods to overcome barriers to clinical trial enrollment. Their paper clearly illustrates mechanisms to assist with overcoming financial burdens associated with cancer clinical trials, overcoming barriers as they relate to patient and clinician difficulty in coping with the uncertainty inherent in clinical trial participation, and highlight the role of a patient navigator in clinical trial participation.

Conclusions

Interventions aimed at increasing awareness, knowledge, and attitudes towards clinical trials among sarcoma patients may lead to increased trial enrollment and greater progress in cancer treatment in this population. In addition to patient- focused interventions, thoughtful and strategic clinical trial designs that allow for the development of biomarker- driven therapeutics, while at the same time optimizing patient accrual rates, should be developed. Evaluation of barriers to clinical trial enrollment and molecular profiling of tumors among bone and soft tissue sarcoma patients at an academic center can serve as a paradigm to overcome barriers to enrollment in the era of an increasingly heterogeneous cancer population. TSJ

Introduction

The development of new cancer therapies relies on the successful development and completion of clinical trials. While clinical trials have led to significant improvements in cancer treatment, the success is dependent upon patient enrollment and participation. Unfortunately, fewer than 5% of adult patients enroll in trials.^1-3 This represents a significant barrier to the development and approval of new cancer treatments. Reasons for low accrual into trials are multifactorial, but include structural barriers (eg, clinic access), clinical barriers (eg, eligibility criteria), and physician and patient attitudes towards trial enrollment.^4,5 One study at the University of California Davis Cancer Center reported 49% of patients declined participation despite meeting eligibility criteria,^3,6 suggesting that psychosocial barriers such as knowledge of trials and attitudes towards clinical research are a major impediment to accrual.^7-9

Bone and soft tissue sarcoma represent a heterogeneous group of tumors of mesenchymal origin that are an important cause of morbidity and mortality. Local disease is often treated with a multidisciplinary approach including surgery, radiation, and systemic therapy. Metastatic disease is predominantly treated palliatively with systemic therapy.¹⁰ Given its rarity and heterogeneity, trial accrual is of particular importance in sarcoma and often requires multiple sites to enroll adequate numbers of patients. While sarcoma represents <1% of adult malignancies overall, it constitutes ~15% of malignancies in the adolescent and young adult (AYA) population (15- 39 years old).^11,12 Sarcoma represents a patient population in which low trial accrual has been correlated with lack of progress in cancer-related outcomes in both the adult and AYA populations.¹³ The reasons for low accrual rates among patients with sarcoma are poorly understood.

Sarcomas represent a molecularly and biologically heterogeneous group of malignancies with over 100 different subtypes.¹² As a result, there has been significant interest in performing molecular profiling, or genetic sequencing, to identify “targetable” mutations. Targetable mutations refer to a specific genetic change identified within the tumor molecular profile for which there is a specific drug that may demonstrate activity against a particular tumor. Given the widespread utilization of this technology in sarcoma, identifying and understanding patient perceptions with regard to molecular profiling is critically important in this disease.¹⁴

In this study, we use a cross-sectional design to describe patient perceptions of trial enrollment among patients with bone and soft tissue sarcoma through validated measures, including attitudes towards clinical trials, knowledge of clinical trials, and perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about clinical trial participation, receptivity to learning more about clinical trials, and willingness to participate in clinical trials.6 In addition, we describe this patient cohort’s perceptions of molecular profiling, as current and future trials are increasingly driven by molecular or other biomarkers.

Methods

This was a cross-sectional electronic survey study of patients with bone and soft tissue sarcoma treated at Northwestern Medicine (NM) over a 5-year period. NM Enterprise Data Warehouse (NMEDW) is a single, comprehensive, and integrated repository of all clinical and research data sources within NM. The study was approved by the Northwestern University Institutional Review Board.

Survey

The investigators designed a self-administered, online survey, which was built using Research Electronic Data Capture (REDCap). The survey consisted of three sections that were answered using skip logic—a custom path through the survey that varied based on patients’ answers: (1) Patient demographic information and trial perceptions (answered by all patients); (2) Thoughts about molecular profiling (answered by patients who answered “yes” to the question, “Have you heard about molecular profiling of tumors?”); and (3) Considerations to undergo molecular profiling (answered by patients who answered “yes” to the question, “Have you undergone profiling of your cancer?”).

 

Clinical trial perceptions included questions assessing (1) patient knowledge about trials; (2) patient attitudes toward trials; (3) perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about trial participation; (4) receptivity to learning more about trials; and (5) willingness to participate in trials. These outcome measures had been previously developed and pilot tested for reliability and validity (TABLE 1).⁶

Thoughts about molecular profiling of tumors were assessed using nine items (TABLE 1). Of these, items assessing potential benefit or harm of molecular profiling were assessed using a 7-step Likert scale. Items assessing maximal benefit or harm of therapy, importance of quality vs length of life, and concern about the cost of molecular testing were assessed using a 5-step Likert scale. The study team developed and piloted these questions because there is no validated survey assessing these domains.

Considerations to undergo molecular profiling were assessed using 17 items. Items were in response to the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” Responses were assessed using a 5-point Likert scale.

Data Collection

Patients 18 years and older evaluated at NM between November 20, 2012, and November 20, 2017, with a diagnosis of sarcoma were identified by query of the NMEDW by ICD-10 codes (C40, C41.9, C44.99, C45-49, C55, C71.9, D48, D49.9, and M12.20) or equivalent ICD-9 codes. Patients were subsequently excluded if they did not have a diagnosis of bone or soft tissue sarcoma, no e-mail address listed, had died, or had not been evaluated at an NM clinic in the previous 5 years. Patients with a diagnosis of gastrointestinal stromal tumor and Kaposi’s sarcoma were also excluded.

A personalized contact e-mail was sent to patients containing an explanation of the survey and an internet link to the electronic survey through REDCap from January 2018 to March 2018. If patients did not respond to the survey, two follow-up reminder e-mails were sent 2 and 4 days following the initial survey. The link was protected so that each patient could complete the survey only once. Responses were collected through the REDCap platform. Patients read and signed an electronic consent form prior to completing the survey.

Upon completion of the survey, patients were offered a $50 VISA gift card as compensation, with an option to donate their compensation to the Robert H. Lurie Comprehensive Cancer Center Sarcoma Research Fund.

Over the described survey period, open clinical trials for patients with bone and soft tissue sarcoma available at NM were evaluated. The number of patients screened and accrued to each trial were recorded.

 

Statistical analysis

Responses were separated from the personal data for complete anonymization. Descriptive statistical analysis was performed for demographics and disease variables and were summarized using frequencies and percentages. Median and range were used for age. Correlations between continuous variables were analyzed using Spearman correlations. Scores were compared between subgroups using the Mann-Whitney test. Descriptive statistics for knowledge, attitude, and ability scores include means and 95% confidence intervals. Correlations were interpreted as small (r=0.10), medium (r=0.30), or large (r=0.50).15 Statistical significance was indicated when P<0.05.

Results

Patients

Seven hundred fifty patients were eligible to participate in the survey and received the initial and two follow-up e-mails. Twenty e-mailed surveys bounced back. Three hundred nine patients opened the initial e-mail and 283 patients (37.7% of total and 91.6% of opened) completed at least a portion of the survey, with 182 patients completing the entire survey (FIGURE 1). Data for analysis were used from patients who completed at least a portion of the survey.

Baseline characteristics of patients who responded can be seen in TABLE 2. Patients had a median age of 56, the majority were female (59.4%), white (88.2%), and most had college or university graduate degrees or higher educational level (69.0%). Patients had various different histological subtypes, with the most common being liposarcoma (16.5%) and leiomyosarcoma (16.0%). Slightly more than a quarter (26.8%) of patients had metastatic disease, and 84.2% had never been enrolled in a clinical trial. Previous treatments included surgery (91.1%), radiation (53.2%), and chemotherapy (51.6%). Prior to completing the survey, 85.4% reported being receptive to a cancer clinical trial, while 60.7% of patients reported willingness to participate in a clinical trial.

 

Knowledge, attitudes, and perceived ability

A statistically significant correlation was observed between greater knowledge of trials and more positive attitudes towards trials (P<0.001; r=0.5, FIGURE 2A). In relating patient attitudes with perceived ability, again a significant correlation was seen (P<0.001; r=0.4, FIGURE 2B). In contrast, knowledge had a weak correlation with perceived ability (P=0.024; r=0.2, FIGURE 2C). There was no difference regarding patient knowledge, attitudes, or perceived ability by age, gender, race, or income.

Knowledge, attitudes, perceived ability, and clinical trial enrollment

Thirty patients reported clinical trial experience (either previously or currently enrolled in trials) and 160 patients were never enrolled. Of the 30 patients with trial experience, 7 reported being currently enrolled, while 23 reported previous enrollment. Of these patients, 16 had metastatic disease, while 12 had non-metastatic disease, and 2 were unsure whether or not they had metastatic disease.

Patients with previous clinical trial exposure (currently or previously enrolled in clinical trials) demonstrated significantly greater trial knowledge, with a mean knowledge score of 9.3 (CI 8.5-10.0) compared with 7.7 (CI 7.3-8.1) among patients without trial exposure (P=0.002; FIGURE 3A). Similarly, patients with trial experience also had statistically significant more positive attitudes towards trials as compared with patients with no trial experience, with a mean attitude score of 3.8 (CI 3.6-4.0) and 3.5 (CI 3.4-3.6), respectively (P=0.001; FIGURE 3B). While numerically patients with trial experience have greater perceived ability compared with patients with no trial experience, with a mean score of 4.4 (CI 4.2-4.6) and 4.2 (CI 4.1-4.3), respectively, this difference did not reach statistical significance (FIGURE 3C).

Knowledge, attitudes, perceived ability, and disease stage

An analysis was performed comparing patients with metastatic vs non-metastatic disease. It was observed that patients with metastatic disease had similar knowledge of trials compared with non-metastatic patients, with a mean knowledge score of 8.4 (CI 7.7- 9.1) and 7.9 (CI 7.5-8.4), respectively, (P=0.3; FIGURE 4A). In contrast, patients with metastatic disease had more positive attitudes compared with non-metastatic patients, with a mean score of 3.7 (CI 3.5-3.8) and 3.5 (CI 3.4-3.6), respectively, which was statistically significant (P=0.03; FIGURE 4B). There was no difference in perceived ability in metastatic vs non-metastatic patients (FIGURE 4C).

Thoughts about molecular profiling

Of the total number of patients, 46 patients had heard of molecular profiling and were presented with questions regarding their thoughts (TABLE 3). Approximately two-thirds (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their tumor molecular profile. A majority (71.7%) of patients thought that a new experimental therapy chosen based on a patient’s tumor molecular profile would have at least a 50% chance of controlling the cancer. Somewhat less than a third (30.4%) of patients thought that total cure is the maximal benefit a patient could experience as a result of a treatment on a clinical trial using a drug chosen based on molecular tests. About half (52.2%) of patients agreed with the statement, “I am concerned about the cost of the test to molecularly profile my cancer.”

Considerations to undergo molecular profiling

Eighteen patients had undergone molecular profiling of their tumor. These patients were posed the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” (TABLE 4). A majority (83.3%) of patients stated that wanting to live as long as possible was important, and 72.2% of patients stated that quality of life was important. A majority (83.3%) of patients stated that hope for a cure was an extremely or quite a bit important consideration. Helping future cancer patients was extremely or quite a bit important for 77.8% of patients, while wanting to be a part of research was not at all or of little importance in 50.0% of patients.

Clinical trials at NM

Twenty-four clinical trials were available at NM between the years 2012 and 2017 for patients with bone and soft tissue sarcoma. Of these trials, 3 of 24 were for non-metastatic patients, while the remaining 21 were open only to metastatic patients. The median number of patients screened per trial was 11 (range 0-66) and the median number of patients accrued per trial was 9 (range 0-58). Of the 24 trials, 17 were not subtype specific (13 included soft tissue sarcoma alone while 4 included both bone and soft tissue sarcoma). The remaining 7 trials were sarcoma subtype specific (eg, angiosarcoma, liposarcoma, etc). Trials available at NM during this period are included in TABLE 5. There were 318 patients screened and 262 patients accrued to sarcoma trials over this time period, with a screen failure rate of 17.6% overall.

Discussion

Our study sought to describe perceptions of clinical trial enrollment among patients with bone and soft tissue sarcoma in order to elucidate and overcome barriers to enrollment, which to the best of our knowledge had not been previously described. Using previously validated patient- reported outcomes in the literature,⁶ our data reveal a correlation between knowledge of trials and more positive attitudes towards trials. This underscores the importance of awareness and educational strategies in this cancer population as a whole. Interventions should focus on patient perceptions that contribute to lack of participation, such as fear of side effects, loss of control (eg, idea of placebo or randomization), logistical challenges (eg, additional time or convenient location), and cost.^3,5,7,16,17 For example, patients concerned about randomization should be educated on equipoise and other ethical considerations in trial design.⁵ Previous research has suggested that a multimedia psychoeducational intervention was effective in improving attitudes toward trials.⁶ Educating patients on the essential role of trials in oncology care, as demonstrated by the vast number of new drug approvals in recent years, is an essential strategy to improve attitudes, and subsequently leads to higher patient accrual rates. 

 

In our study, both knowledge and at titudes were increased in patients with previous trial exposure. This suggests that either patients with greater knowledge and more positive attitudes are more likely to enroll in trials, or that patients with direct trial exposure are more knowledgeable and develop more positive attitudes. Our patient population was overall receptive to learning more about clinical trials (85.4%) and willing to participate (65.8%). At the same time, our study demonstrated low to medium correlations between attitudes and perceived ability to take steps towards making an informed decision to enroll in a trial (r=0.4), which may partially be explained by the absence of a tangible trial opportunity. While we did not assess specifically whether patients in our study were offered a trial, there was a substantial trial menu at NM with limited screen failures and decent trial accrual over the time frame of our study. This underscores the importance not only of patient-focused strategies to increase educational and attitudinal resources, but also a need to focus on research-site optimization that includes opening of multiple trials in various settings, systematic pre-screening of patients, and eligibility criteria that are inclusive and rational.⁵

The patient population with metastatic disease demonstrated more positive attitudes towards enrolling in clinical trials. This cohort accrued well to clinical trials, with 21 of 24 trials enrolling specifically patients with metastatic disease. Of the patients who responded to our survey, patients with previous trial exposure were enriched for patients with metastatic disease (53.3% metastatic among previous trial exposure versus 26.8% metastatic overall). These observations are likely reflective of the need for novel therapies in this disease setting. At the same time, approximately 25% of patients with localized soft tissue sarcoma will develop distant metastatic disease after successful treatment of their primary tumor, which increases to 40% to 50% in larger and higher-grade tumors.¹⁸ Three of 24 trials were open for patients with non-metastatic disease, of which one managed to accrue patients. Patients with non-metastatic disease had more negative attitudes towards trial enrollment. These disproportionate findings suggest a need for interventions to increase patient awareness and attitudes towards trial enrollment among this patient population and the importance of research-site optimization for trial opportunities across disease states.

Molecular profiling of tumors and biomarker identification has become a critical component of further characterizing cancer subtypes. In our study, a majority (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their molecular profile. Molecular data on 5,749 bone and soft tissue sarcomas suggested that 9.5% of tumors demonstrate a “targetable result,” defined as a new molecular finding for which there is an FDA-approved drug for malignancies other than sarcoma (eg, BRAF V600E, Her2, etc.),¹⁹ suggesting an overestimation in our patient cohort of the likelihood of benefit of molecular profiling. These results highlight that the growing use of molecular profiling has increased the need for educational and supportive resources to help patients understand the utility of molecular profiling and aid in shared decision-making surrounding the results.

At the same time, the importance of identifying a targetable mutation in patients with sarcoma cannot be understated. As a recent example of this paradigm, tumors that harbor fusions with the neurotrophic receptor tyrosine kinase 1, 2, or 3 (NTRK1, 2, and 3) have a high response rate (~75%) to drugs that target these fusions, such as larotrectinib and entrectinib.¹³ Molecular profiling and identification of predictive biomarkers in small patient subsets has led to great challenges in trial design and research-site optimization. Novel designs that incorporate molecular profiling,²⁰ such as the Lung- MAP trial²¹ and NCI’s Molecular Analysis for Therapy Choice (MATCH) trial,²² are emerging to identify new therapies for small patient subsets. As a rare and increasingly heterogeneous cancer, sarcoma represents a paradigm to provide insight into optimizing patient perceptions and research enterprises to maximize clinical trial enrollment. 

Some limitations of our study include a homogeneous and selected patient population that was predominantly Caucasian and highly educated. Therefore, these findings should not be extrapolated to other populations with barriers to trial accrual, such as lower socioeconomic or minority populations. The low response rate and failure of some to complete the survey may have introduced some bias. Additionally, our data include self-reported outcomes, which could have affected our results. Finally, the limited number of patients who had undergone or heard of molecular profiling limited our ability to draw definitive conclusions, and should be assessed in larger patient cohorts.

While our paper addresses a unique population—the sarcoma patient—similar themes and issues pertain to all oncology patients. A recent review was published in the American Society of Clinical Oncology Educational Book²³ looking at methods to overcome barriers to clinical trial enrollment. Their paper clearly illustrates mechanisms to assist with overcoming financial burdens associated with cancer clinical trials, overcoming barriers as they relate to patient and clinician difficulty in coping with the uncertainty inherent in clinical trial participation, and highlight the role of a patient navigator in clinical trial participation.

Conclusions

Interventions aimed at increasing awareness, knowledge, and attitudes towards clinical trials among sarcoma patients may lead to increased trial enrollment and greater progress in cancer treatment in this population. In addition to patient- focused interventions, thoughtful and strategic clinical trial designs that allow for the development of biomarker- driven therapeutics, while at the same time optimizing patient accrual rates, should be developed. Evaluation of barriers to clinical trial enrollment and molecular profiling of tumors among bone and soft tissue sarcoma patients at an academic center can serve as a paradigm to overcome barriers to enrollment in the era of an increasingly heterogeneous cancer population. TSJ

Introduction

The development of new cancer therapies relies on the successful development and completion of clinical trials. While clinical trials have led to significant improvements in cancer treatment, the success is dependent upon patient enrollment and participation. Unfortunately, fewer than 5% of adult patients enroll in trials.^1-3 This represents a significant barrier to the development and approval of new cancer treatments. Reasons for low accrual into trials are multifactorial, but include structural barriers (eg, clinic access), clinical barriers (eg, eligibility criteria), and physician and patient attitudes towards trial enrollment.^4,5 One study at the University of California Davis Cancer Center reported 49% of patients declined participation despite meeting eligibility criteria,^3,6 suggesting that psychosocial barriers such as knowledge of trials and attitudes towards clinical research are a major impediment to accrual.^7-9

Bone and soft tissue sarcoma represent a heterogeneous group of tumors of mesenchymal origin that are an important cause of morbidity and mortality. Local disease is often treated with a multidisciplinary approach including surgery, radiation, and systemic therapy. Metastatic disease is predominantly treated palliatively with systemic therapy.¹⁰ Given its rarity and heterogeneity, trial accrual is of particular importance in sarcoma and often requires multiple sites to enroll adequate numbers of patients. While sarcoma represents <1% of adult malignancies overall, it constitutes ~15% of malignancies in the adolescent and young adult (AYA) population (15- 39 years old).^11,12 Sarcoma represents a patient population in which low trial accrual has been correlated with lack of progress in cancer-related outcomes in both the adult and AYA populations.¹³ The reasons for low accrual rates among patients with sarcoma are poorly understood.

Sarcomas represent a molecularly and biologically heterogeneous group of malignancies with over 100 different subtypes.¹² As a result, there has been significant interest in performing molecular profiling, or genetic sequencing, to identify “targetable” mutations. Targetable mutations refer to a specific genetic change identified within the tumor molecular profile for which there is a specific drug that may demonstrate activity against a particular tumor. Given the widespread utilization of this technology in sarcoma, identifying and understanding patient perceptions with regard to molecular profiling is critically important in this disease.¹⁴

In this study, we use a cross-sectional design to describe patient perceptions of trial enrollment among patients with bone and soft tissue sarcoma through validated measures, including attitudes towards clinical trials, knowledge of clinical trials, and perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about clinical trial participation, receptivity to learning more about clinical trials, and willingness to participate in clinical trials.6 In addition, we describe this patient cohort’s perceptions of molecular profiling, as current and future trials are increasingly driven by molecular or other biomarkers.

Methods

This was a cross-sectional electronic survey study of patients with bone and soft tissue sarcoma treated at Northwestern Medicine (NM) over a 5-year period. NM Enterprise Data Warehouse (NMEDW) is a single, comprehensive, and integrated repository of all clinical and research data sources within NM. The study was approved by the Northwestern University Institutional Review Board.

Survey

The investigators designed a self-administered, online survey, which was built using Research Electronic Data Capture (REDCap). The survey consisted of three sections that were answered using skip logic—a custom path through the survey that varied based on patients’ answers: (1) Patient demographic information and trial perceptions (answered by all patients); (2) Thoughts about molecular profiling (answered by patients who answered “yes” to the question, “Have you heard about molecular profiling of tumors?”); and (3) Considerations to undergo molecular profiling (answered by patients who answered “yes” to the question, “Have you undergone profiling of your cancer?”).

 

Clinical trial perceptions included questions assessing (1) patient knowledge about trials; (2) patient attitudes toward trials; (3) perceived ability (ie, self-efficacy) to carry out actions involved in making an informed decision about trial participation; (4) receptivity to learning more about trials; and (5) willingness to participate in trials. These outcome measures had been previously developed and pilot tested for reliability and validity (TABLE 1).⁶

Thoughts about molecular profiling of tumors were assessed using nine items (TABLE 1). Of these, items assessing potential benefit or harm of molecular profiling were assessed using a 7-step Likert scale. Items assessing maximal benefit or harm of therapy, importance of quality vs length of life, and concern about the cost of molecular testing were assessed using a 5-step Likert scale. The study team developed and piloted these questions because there is no validated survey assessing these domains.

Considerations to undergo molecular profiling were assessed using 17 items. Items were in response to the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” Responses were assessed using a 5-point Likert scale.

Data Collection

Patients 18 years and older evaluated at NM between November 20, 2012, and November 20, 2017, with a diagnosis of sarcoma were identified by query of the NMEDW by ICD-10 codes (C40, C41.9, C44.99, C45-49, C55, C71.9, D48, D49.9, and M12.20) or equivalent ICD-9 codes. Patients were subsequently excluded if they did not have a diagnosis of bone or soft tissue sarcoma, no e-mail address listed, had died, or had not been evaluated at an NM clinic in the previous 5 years. Patients with a diagnosis of gastrointestinal stromal tumor and Kaposi’s sarcoma were also excluded.

A personalized contact e-mail was sent to patients containing an explanation of the survey and an internet link to the electronic survey through REDCap from January 2018 to March 2018. If patients did not respond to the survey, two follow-up reminder e-mails were sent 2 and 4 days following the initial survey. The link was protected so that each patient could complete the survey only once. Responses were collected through the REDCap platform. Patients read and signed an electronic consent form prior to completing the survey.

Upon completion of the survey, patients were offered a $50 VISA gift card as compensation, with an option to donate their compensation to the Robert H. Lurie Comprehensive Cancer Center Sarcoma Research Fund.

Over the described survey period, open clinical trials for patients with bone and soft tissue sarcoma available at NM were evaluated. The number of patients screened and accrued to each trial were recorded.

 

Statistical analysis

Responses were separated from the personal data for complete anonymization. Descriptive statistical analysis was performed for demographics and disease variables and were summarized using frequencies and percentages. Median and range were used for age. Correlations between continuous variables were analyzed using Spearman correlations. Scores were compared between subgroups using the Mann-Whitney test. Descriptive statistics for knowledge, attitude, and ability scores include means and 95% confidence intervals. Correlations were interpreted as small (r=0.10), medium (r=0.30), or large (r=0.50).15 Statistical significance was indicated when P<0.05.

Results

Patients

Seven hundred fifty patients were eligible to participate in the survey and received the initial and two follow-up e-mails. Twenty e-mailed surveys bounced back. Three hundred nine patients opened the initial e-mail and 283 patients (37.7% of total and 91.6% of opened) completed at least a portion of the survey, with 182 patients completing the entire survey (FIGURE 1). Data for analysis were used from patients who completed at least a portion of the survey.

Baseline characteristics of patients who responded can be seen in TABLE 2. Patients had a median age of 56, the majority were female (59.4%), white (88.2%), and most had college or university graduate degrees or higher educational level (69.0%). Patients had various different histological subtypes, with the most common being liposarcoma (16.5%) and leiomyosarcoma (16.0%). Slightly more than a quarter (26.8%) of patients had metastatic disease, and 84.2% had never been enrolled in a clinical trial. Previous treatments included surgery (91.1%), radiation (53.2%), and chemotherapy (51.6%). Prior to completing the survey, 85.4% reported being receptive to a cancer clinical trial, while 60.7% of patients reported willingness to participate in a clinical trial.

 

Knowledge, attitudes, and perceived ability

A statistically significant correlation was observed between greater knowledge of trials and more positive attitudes towards trials (P<0.001; r=0.5, FIGURE 2A). In relating patient attitudes with perceived ability, again a significant correlation was seen (P<0.001; r=0.4, FIGURE 2B). In contrast, knowledge had a weak correlation with perceived ability (P=0.024; r=0.2, FIGURE 2C). There was no difference regarding patient knowledge, attitudes, or perceived ability by age, gender, race, or income.

Knowledge, attitudes, perceived ability, and clinical trial enrollment

Thirty patients reported clinical trial experience (either previously or currently enrolled in trials) and 160 patients were never enrolled. Of the 30 patients with trial experience, 7 reported being currently enrolled, while 23 reported previous enrollment. Of these patients, 16 had metastatic disease, while 12 had non-metastatic disease, and 2 were unsure whether or not they had metastatic disease.

Patients with previous clinical trial exposure (currently or previously enrolled in clinical trials) demonstrated significantly greater trial knowledge, with a mean knowledge score of 9.3 (CI 8.5-10.0) compared with 7.7 (CI 7.3-8.1) among patients without trial exposure (P=0.002; FIGURE 3A). Similarly, patients with trial experience also had statistically significant more positive attitudes towards trials as compared with patients with no trial experience, with a mean attitude score of 3.8 (CI 3.6-4.0) and 3.5 (CI 3.4-3.6), respectively (P=0.001; FIGURE 3B). While numerically patients with trial experience have greater perceived ability compared with patients with no trial experience, with a mean score of 4.4 (CI 4.2-4.6) and 4.2 (CI 4.1-4.3), respectively, this difference did not reach statistical significance (FIGURE 3C).

Knowledge, attitudes, perceived ability, and disease stage

An analysis was performed comparing patients with metastatic vs non-metastatic disease. It was observed that patients with metastatic disease had similar knowledge of trials compared with non-metastatic patients, with a mean knowledge score of 8.4 (CI 7.7- 9.1) and 7.9 (CI 7.5-8.4), respectively, (P=0.3; FIGURE 4A). In contrast, patients with metastatic disease had more positive attitudes compared with non-metastatic patients, with a mean score of 3.7 (CI 3.5-3.8) and 3.5 (CI 3.4-3.6), respectively, which was statistically significant (P=0.03; FIGURE 4B). There was no difference in perceived ability in metastatic vs non-metastatic patients (FIGURE 4C).

Thoughts about molecular profiling

Of the total number of patients, 46 patients had heard of molecular profiling and were presented with questions regarding their thoughts (TABLE 3). Approximately two-thirds (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their tumor molecular profile. A majority (71.7%) of patients thought that a new experimental therapy chosen based on a patient’s tumor molecular profile would have at least a 50% chance of controlling the cancer. Somewhat less than a third (30.4%) of patients thought that total cure is the maximal benefit a patient could experience as a result of a treatment on a clinical trial using a drug chosen based on molecular tests. About half (52.2%) of patients agreed with the statement, “I am concerned about the cost of the test to molecularly profile my cancer.”

Considerations to undergo molecular profiling

Eighteen patients had undergone molecular profiling of their tumor. These patients were posed the question, “To what extent did you consider the following issues or concerns at the time you decided to get molecular testing of your cancer?” (TABLE 4). A majority (83.3%) of patients stated that wanting to live as long as possible was important, and 72.2% of patients stated that quality of life was important. A majority (83.3%) of patients stated that hope for a cure was an extremely or quite a bit important consideration. Helping future cancer patients was extremely or quite a bit important for 77.8% of patients, while wanting to be a part of research was not at all or of little importance in 50.0% of patients.

Clinical trials at NM

Twenty-four clinical trials were available at NM between the years 2012 and 2017 for patients with bone and soft tissue sarcoma. Of these trials, 3 of 24 were for non-metastatic patients, while the remaining 21 were open only to metastatic patients. The median number of patients screened per trial was 11 (range 0-66) and the median number of patients accrued per trial was 9 (range 0-58). Of the 24 trials, 17 were not subtype specific (13 included soft tissue sarcoma alone while 4 included both bone and soft tissue sarcoma). The remaining 7 trials were sarcoma subtype specific (eg, angiosarcoma, liposarcoma, etc). Trials available at NM during this period are included in TABLE 5. There were 318 patients screened and 262 patients accrued to sarcoma trials over this time period, with a screen failure rate of 17.6% overall.

Discussion

Our study sought to describe perceptions of clinical trial enrollment among patients with bone and soft tissue sarcoma in order to elucidate and overcome barriers to enrollment, which to the best of our knowledge had not been previously described. Using previously validated patient- reported outcomes in the literature,⁶ our data reveal a correlation between knowledge of trials and more positive attitudes towards trials. This underscores the importance of awareness and educational strategies in this cancer population as a whole. Interventions should focus on patient perceptions that contribute to lack of participation, such as fear of side effects, loss of control (eg, idea of placebo or randomization), logistical challenges (eg, additional time or convenient location), and cost.^3,5,7,16,17 For example, patients concerned about randomization should be educated on equipoise and other ethical considerations in trial design.⁵ Previous research has suggested that a multimedia psychoeducational intervention was effective in improving attitudes toward trials.⁶ Educating patients on the essential role of trials in oncology care, as demonstrated by the vast number of new drug approvals in recent years, is an essential strategy to improve attitudes, and subsequently leads to higher patient accrual rates. 

 

In our study, both knowledge and at titudes were increased in patients with previous trial exposure. This suggests that either patients with greater knowledge and more positive attitudes are more likely to enroll in trials, or that patients with direct trial exposure are more knowledgeable and develop more positive attitudes. Our patient population was overall receptive to learning more about clinical trials (85.4%) and willing to participate (65.8%). At the same time, our study demonstrated low to medium correlations between attitudes and perceived ability to take steps towards making an informed decision to enroll in a trial (r=0.4), which may partially be explained by the absence of a tangible trial opportunity. While we did not assess specifically whether patients in our study were offered a trial, there was a substantial trial menu at NM with limited screen failures and decent trial accrual over the time frame of our study. This underscores the importance not only of patient-focused strategies to increase educational and attitudinal resources, but also a need to focus on research-site optimization that includes opening of multiple trials in various settings, systematic pre-screening of patients, and eligibility criteria that are inclusive and rational.⁵

The patient population with metastatic disease demonstrated more positive attitudes towards enrolling in clinical trials. This cohort accrued well to clinical trials, with 21 of 24 trials enrolling specifically patients with metastatic disease. Of the patients who responded to our survey, patients with previous trial exposure were enriched for patients with metastatic disease (53.3% metastatic among previous trial exposure versus 26.8% metastatic overall). These observations are likely reflective of the need for novel therapies in this disease setting. At the same time, approximately 25% of patients with localized soft tissue sarcoma will develop distant metastatic disease after successful treatment of their primary tumor, which increases to 40% to 50% in larger and higher-grade tumors.¹⁸ Three of 24 trials were open for patients with non-metastatic disease, of which one managed to accrue patients. Patients with non-metastatic disease had more negative attitudes towards trial enrollment. These disproportionate findings suggest a need for interventions to increase patient awareness and attitudes towards trial enrollment among this patient population and the importance of research-site optimization for trial opportunities across disease states.

Molecular profiling of tumors and biomarker identification has become a critical component of further characterizing cancer subtypes. In our study, a majority (65.2%) thought there would be a 50% or greater likelihood of finding a targetable result in their molecular profile. Molecular data on 5,749 bone and soft tissue sarcomas suggested that 9.5% of tumors demonstrate a “targetable result,” defined as a new molecular finding for which there is an FDA-approved drug for malignancies other than sarcoma (eg, BRAF V600E, Her2, etc.),¹⁹ suggesting an overestimation in our patient cohort of the likelihood of benefit of molecular profiling. These results highlight that the growing use of molecular profiling has increased the need for educational and supportive resources to help patients understand the utility of molecular profiling and aid in shared decision-making surrounding the results.

At the same time, the importance of identifying a targetable mutation in patients with sarcoma cannot be understated. As a recent example of this paradigm, tumors that harbor fusions with the neurotrophic receptor tyrosine kinase 1, 2, or 3 (NTRK1, 2, and 3) have a high response rate (~75%) to drugs that target these fusions, such as larotrectinib and entrectinib.¹³ Molecular profiling and identification of predictive biomarkers in small patient subsets has led to great challenges in trial design and research-site optimization. Novel designs that incorporate molecular profiling,²⁰ such as the Lung- MAP trial²¹ and NCI’s Molecular Analysis for Therapy Choice (MATCH) trial,²² are emerging to identify new therapies for small patient subsets. As a rare and increasingly heterogeneous cancer, sarcoma represents a paradigm to provide insight into optimizing patient perceptions and research enterprises to maximize clinical trial enrollment. 

Some limitations of our study include a homogeneous and selected patient population that was predominantly Caucasian and highly educated. Therefore, these findings should not be extrapolated to other populations with barriers to trial accrual, such as lower socioeconomic or minority populations. The low response rate and failure of some to complete the survey may have introduced some bias. Additionally, our data include self-reported outcomes, which could have affected our results. Finally, the limited number of patients who had undergone or heard of molecular profiling limited our ability to draw definitive conclusions, and should be assessed in larger patient cohorts.

While our paper addresses a unique population—the sarcoma patient—similar themes and issues pertain to all oncology patients. A recent review was published in the American Society of Clinical Oncology Educational Book²³ looking at methods to overcome barriers to clinical trial enrollment. Their paper clearly illustrates mechanisms to assist with overcoming financial burdens associated with cancer clinical trials, overcoming barriers as they relate to patient and clinician difficulty in coping with the uncertainty inherent in clinical trial participation, and highlight the role of a patient navigator in clinical trial participation.

Conclusions

Interventions aimed at increasing awareness, knowledge, and attitudes towards clinical trials among sarcoma patients may lead to increased trial enrollment and greater progress in cancer treatment in this population. In addition to patient- focused interventions, thoughtful and strategic clinical trial designs that allow for the development of biomarker- driven therapeutics, while at the same time optimizing patient accrual rates, should be developed. Evaluation of barriers to clinical trial enrollment and molecular profiling of tumors among bone and soft tissue sarcoma patients at an academic center can serve as a paradigm to overcome barriers to enrollment in the era of an increasingly heterogeneous cancer population. TSJ