Practice Management

Study Overview

Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.

Design. Single-blinded multicenter randomized controlled trial.

Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.

Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.

The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.

Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.

Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ² or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.

Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.

In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).

In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).

Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.

Commentary

Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.^1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.^1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.

The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.⁴ Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.^4-9

This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.

While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.

Applications for Clinical Practice

While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.

Study Overview

Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.

Design. Single-blinded multicenter randomized controlled trial.

Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.

Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.

The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.

Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.

Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ² or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.

Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.

In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).

In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).

Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.

Commentary

Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.^1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.^1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.

The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.⁴ Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.^4-9

This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.

While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.

Applications for Clinical Practice

While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.

Study Overview

Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.

Design. Single-blinded multicenter randomized controlled trial.

Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.

Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.

The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.

Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.

Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ² or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.

Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.

In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).

In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).

Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.

Commentary

Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.^1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.^1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.

The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.⁴ Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.^4-9

This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.

While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.

Applications for Clinical Practice

While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

Study Overview

Objective: To assess whether ticagrelor was superior to clopidogrel in reducing periprocedural myocardial necrosis in stable coronary patients undergoing elective percutaneous coronary intervention (PCI).

Design: Multicenter, open-label, and prospective randomized control trial. Setting and participants: A total of 1910 patients with indication for PCI and at least 1 high risk characteristic were randomized to either ticagrelor or clopidogrel.

Main outcome measures: The primary outcome was the composite of PCI-related type 4a or 4b myocardial infarction or major myocardial injury. The primary safety outcome was major bleeding, evaluated within 48 hours of PCI.

Main results: At 48 hours, the primary outcome was observed in 334 of 941 patients (35%) in the ticagrelor group and 341 of 942 patients (36%) in the clopidogrel group (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.80-1.17; P = .75). The primary safety outcome did not differ between groups. Minor bleeding events at 30 days were more frequently observed with ticagrelor (11%) than clopidogrel (8%) (1.54; 95% CI 1.12-2.11; P = .007).

Conclusion: Among patients undergoing elective PCI, ticagrelor was not superior to clopidogrel in reducing periprocedural myocardial necrosis. Ticagrelor did not cause increase in major bleeding compared to clopidogrel but did increase the rate of minor bleeding at 30 days.

Commentary

Standard treatment after PCI includes dual antiplatelet therapy combining adenosine diphosphate (ADP) receptor antagonist and aspirin. The newer generation thienopyridine prasugrel and the reversible direct acting oral antagonist of the ADP receptor ticagrelor, provides consistent and greater antiplatelet effect compared to clopidogrel, and are superior in reducing ischemic events when compared to clopidogrel in patients presenting with acute coronary syndrome (ACS).^1,2 Therefore, current guidelines recommend ticagrelor and prasugrel in preference to clopidogrel in patients presenting with ACS.^3,4 However, whether these findings of improved outcomes with newer agents compared to clopidogrel extends to patients with stable ischemic heart disease presenting for elective PCI is unknown.

In this context, Silvain et al investigated this clinical question and compared ticagrelor and clopidogrel by performing a well-designed multicenter randomized control trial in patients presenting with elective PCI. At 48 hours and at 30 days the composite of PCI-related type 4 myocardial infarction or major myocardial injury defined by the third universal definition⁵ was similar between the ticagrelor and clopidogrel groups. Although the incidence of major bleeding was not significantly different between the 2 groups, minor bleeding at 30 days was higher in the ticagrelor group (11%) than clopidogrel (8%) (1.54; 95% CI, 1.12-2.11, P = .007).

The strengths of this current study include the randomized design and the large number of patients enrolled with adequate power to evaluate for superiority of ticagrelor compared to clopidogrel. This was a multicenter trial in Europe with 49 participating centers from France and Czech, and the interventional technique used by the operators reflects contemporary technique with 95% use of radial or ulnar access.

There are a few important points to consider in this study. First, the primary outcome was biomarker assessed myocardial necrosis and myocardial injury, and the study was not powered to assess the hard outcomes such as death and myocardial infarction. Although there have been previous reports describing the relationship between the postprocedural myocardial necrosis with worse outcomes, the definition of myocardial necrosis post-PCI and its relationship with hard outcomes remains controversial. Second, half of the patients enrolled were on chronic clopidogrel therapy which suggests that patients with inadequate platelet inhibition with clopidogrel may be under-represented in this cohort. Third, this was an open-label study and the knowledge of agent used could have affected the study results. Finally, whether the population included represents a true high-risk population is questionable. Some of the prespecified high-risk features necessary to enter the study was relatively light, such as presence of diabetes mellitus or body mass index > 30 kg/m² compared to other criteria such as bifurcation stenting or left main stenting.

Currently, when treating patients with stable ischemic heart disease with higher risk anatomy, some operators may use ticagrelor over clopidogrel by extrapolating the study results from the ACS population. However, the results from the current study do not support the uniform use of ticagrelor in stable patients and suggests that the use of clopidogrel continues to be the standard of care. This is especially relevant considering the cost difference for the 2 agents studied. Whether there is a subgroup that benefits from ticagrelor use, such as patients with unprotected left main stenting or bifurcation stenting with 2 stent strategies, requires further investigation.

Applications for Clinical Practice

In patients presenting with stable ischemic heart disease undergoing elective PCI, ticagrelor did not lower composite of periprocedural myocardial infarction and myocardial injury at 48 hours. Clopidogrel continues to be a first line treatment after elective PCI.

From Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA (Drs. Chu and Ma and Mimi Lou), and Department of Family Medicine, Keck Medicine, University of Southern California, Los Angeles, CA (Dr. Suh).

Objective: The objective of this study is to describe HbA_1c changes in patients who maintained continuous pharmacist care vs patients who had a gap in pharmacist care of 3 months or longer. 

Methods: This retrospective study was conducted from October 1, 2018, to September 30, 2019. Electronic health record data from an academic-affiliated, safety-net resident physician primary care clinic were collected to observe HbA_1c changes between patients with continuous pharmacist care and patients who had a gap of 3 months or longer in pharmacist care. A total of 189 patients met the inclusion criteria and were divided into 2 groups: those with continuous care and those with gaps in care. Data were analyzed using the Mann-Whitney test for continuous variables and the χ² (or Fisher exact) test for categorical variables. The differences-in-differences model was used to compare the changes in HbA_1c between the 2 groups.

Results: There was no significant difference in changes in HbA_1c between the continuous care group and the gaps in care group, although the mean magnitude of HbA_1c changes was numerically greater in the continuous care group (-1.48% vs -0.97%). Overall, both groups showed improvement in their HbA_1c levels and had similar numbers of primary care physician visits and acute care utilizations, while the gaps in care group had longer duration with pharmacists and between the adjacent pharmacist visits.

Conclusion: Maintaining continuous, regular visits with a pharmacist at a safety-net resident physician primary care clinic did not show a significant difference in HbA_1c changes compared to having gaps in pharmacist care. Future studies on socioeconomic and behavioral burden on HbA_1c improvement and on pharmacist visits in these populations should be explored.

Keywords: clinical pharmacist; diabetes management; continuous visit; primary care clinic.

Pharmacists have unique skills in identifying and resolving problems related to the safety and efficacy of drug therapy while addressing medication adherence and access for patients. Their expertise is especially important to meet the care needs of a growing population with chronic conditions amidst a primary care physician shortage.¹ As health care systems move toward value-based care, emphasis on improvement in quality and health measures have become central in care delivery. Pharmacists have been integrated into team-based care in primary care settings, but the value-based shift has opened more opportunities for pharmacists to address unmet quality standards.^2-5

Many studies have reported that the integration of pharmacists into team-based care improves health outcomes and reduces overall health care costs.^6-9 Specifically, when pharmacists were added to primary care teams to provide diabetes management, hemoglobin HbA_1c levels were reduced compared to teams without pharmacists.^10-13 Offering pharmacist visits as often as every 2 weeks to 3 months, with each patient having an average of 4.7 visits, resulted in improved therapeutic outcomes.^3,7 During visits, pharmacists address the need for additional drug therapy, deprescribe unnecessary therapy, correct insufficient doses or durations, and switch patients to more cost-efficient drug therapy.⁹ Likewise, patients who visit pharmacists in addition to seeing their primary care physician can have medication-related concerns resolved and improve their therapeutic outcomes.^10,11

Not much is known about the magnitude of HbA_1c change based on the regularity of pharmacist visits. Although pharmacists offer follow-up appointments in reasonable time intervals, patients do not keep every appointment for a variety of reasons, including forgetfulness, personal issues, and a lack of transportation.¹⁴ Such missed appointments can negatively impact health outcomes.^14-16 The purpose of this study is to describe HbA_1c changes in patients who maintained continuous, regular pharmacist visits without a 3-month gap and in patients who had history of inconsistent pharmacist visits with a gap of 3 months or longer. Furthermore, this study describes the frequency of health care utilization for these 2 groups.

Methods

Setting

The Internal Medicine resident physician primary care clinic is 1 of 2 adult primary care clinics at an academic, urban, public medical center. It is in the heart of East Los Angeles, where predominantly Spanish-speaking and minority populations reside. The clinic has approximately 19000 empaneled patients and is the largest resident primary care clinic in the public health system. The clinical pharmacy service addresses unmet quality standards, specifically HbA_1c. The clinical pharmacists are co-located and collaborate with resident physicians, attending physicians, care managers, nurses, social workers, and community health workers at the clinic. They operate under collaborative practice agreements with prescriptive authority, except for controlled substances, specialty drugs, and antipsychotic medications.

Pharmacist visit

Patients are primarily referred by resident physicians to clinical pharmacists when their HbA_1c level is above 8% for an extended period, when poor adherence and low health literacy are evident regardless of HbA_1c level, or when a complex medication regimen requires comprehensive medication review and reconciliation. The referral occurs through warm handoff by resident physicians as well as clinic nurses, and it is embedded in the clinic flow. Patients continue their visits with resident physicians for issues other than their referral to clinical pharmacists. The visits with pharmacists are appointment-based, occur independently from resident physician visits, and continue until the patient’s HbA_1c level or adherence is optimized. Clinical pharmacists continue to follow up with patients who may have reached their target HbA_1c level but still are deemed unstable due to inconsistency in their self-management and medication adherence.

After the desirable HbA_1c target is achieved along with full adherence to medications and self-management, clinical pharmacists will hand off patients back to resident physicians. At each visit, pharmacists perform a comprehensive medication assessment and reconciliation that includes adjusting medication therapy, placing orders for necessary laboratory tests and prescriptions, and assessing medication adherence. They also evaluate patients’ signs and symptoms for hyperglycemic complications, hypoglycemia, and other potential treatment-related adverse events. These are all within the pharmacist’s scope of practice in comprehensive medication management. Patient education is provided with the teach-back method and includes lifestyle modifications and medication counseling (Table 1). Pharmacists offer face-to-face visits as frequently as every 1 to 2 weeks to every 4 to 6 weeks, depending on the level of complexity and the severity of a patient’s conditions and medications. For patients whose HbA_1c has reached the target range but have not been deemed stable, pharmacists continue to check in with them every 2 months. Phone visits are also utilized as an additional care delivery method for patients having difficulty showing up for face-to-face visits or needing quick assessment of medication adherence and responses to changes in drug treatment in between the face-to-face visits. The maximal interval between pharmacist visits is offered no longer than every 8 weeks. Patients are contacted via phone or mail by the nursing staff to reschedule if they miss their appointments with pharmacists. Every pharmacy visit is documented in the patient’s electronic medical record.

Study design

This is a retrospective study describing the HbA_1c changes in a patient group that maintained pharmacist visits, with each interval less than 3 months, and in another group, who had a history of a 3-month or longer gap between pharmacist visits. The data were obtained from patients’ electronic medical records during the study period of October 1, 2018, and September 30, 2019, and collected using a HIPAA-compliant, electronic data storage website, REDCap. The institutional review board approval was obtained under HS-19-00929. Patients 18 years and older who were referred by primary care resident physicians for diabetes management, and had 2 or more visits with a pharmacist within the study period, were included. Patients were excluded if they had only 1 HbA_1c drawn during the study period, were referred to a pharmacist for reasons other than diabetes management, were concurrently managed by an endocrinologist, had only 1 visit with a pharmacist, or had no visits with their primary care resident physician for over a year. The patients were then divided into 2 groups: continuous care cohort (CCC) and gap in care cohort (GCC). Both face-to-face and phone visits were counted as pharmacist visits for each group.

Outcomes

The primary outcome was the change in HbA_1c from baseline between the 2 groups. Baseline HbA_1c was considered as the HbA_1c value obtained within 3 months prior to, or within 1 month, of the first visit with the pharmacist during the study period. The final HbA_1c was considered the value measured within 1 month of, or 3 months after, the patient’s last visit with the pharmacist during the study period.

Several subgroup analyses were conducted to examine the relationship between HbA_1c and each group. Among patients whose baseline HbA_1c was ≥ 8%, we looked at the percentage of patients reaching HbA_1c < 8%, the percentage of patients showing any level of improvement in HbA_1c, and the change in HbA_1c for each group. We also looked at the percentage of patients with baseline HbA_1c < 8% maintaining the level throughout the study period and the change in HbA_1c for each group. Additionally, we looked at health care utilization, which included pharmacist visits, primary care physician visits, emergency room and urgent care visits, and hospitalizations for each group. The latter 3 types of utilization were grouped as acute care utilization and further analyzed for visit reasons, which were subsequently categorized as diabetes related and non-diabetes related. The diabetes related reasons linking to acute care utilization were defined as any episodes related to hypoglycemia, diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), foot ulcers, retinopathy, and osteomyelitis infection. All other reasons leading to acute care utilization were categorized as non-diabetes related.

Statistical analysis

Descriptive analyses were conducted using the Mann-Whitney test for continuous data and χ² (or Fisher exact) test for categorical data. A basic difference-in-differences (D-I-D) method was used to compare the changes of HbA_1c between the CCC and GCC over 2 time points: baseline and final measurements. The repeated measures ANOVA was used for analyzing D-I-D. P < .05 was considered significant. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Results

Baseline data

A total of 1272 patients were identified within the study period, and 189 met the study inclusion criteria. The CCC included 132 patients, the GCC 57. The mean age of patients in both groups was similar at 57 years old (P = .39). Most patients had Medicaid as their primary insurance. About one-third of patients in each group experienced clinical atherosclerotic cardiovascular disease, and about 12% overall had chronic kidney disease stage 3 and higher. The average number of days that patients were under pharmacist care during the study period was longer in the GCC compared to the CCC, and it was statistically significant (P < .001) (Table 2). The mean ± SD baseline HbA_1c for the CCC and GCC was 10.0% ± 2.0% and 9.9% ± 1.7%, respectively, and the difference was not statistically significant (P = .93). About 86% of patients in the CCC and 90% in the GCC had a baseline HbA_1c of ≥ 8%.

The mean change in HbA_1c between the 2 groups was not statistically significant (-1.5% ± 2.0% in the CCC vs -1.0% ± 2.1% in the GCC, P = .36) (Table 3). However, an absolute mean HbA_1c reduction of 1.3% was observed in both groups combined at the end of the study. Figure 1 shows a D-I-D model of the 2 groups. Based on the output, the P value of .11 on the interaction term (time*group) indicates that the D-I-D in HbA_1c change from baseline to final between the CCC and GCC is not statistically different. However, the magnitude of the difference calculated from the LSMEANS results showed a trend. The HbA_1c from baseline to final measurement of patients in the GCC declined by 0.97 percentage points (from 9.94% to 8.97%), while those in the CCC saw their HbA_1c decline by 1.48 percentage points (from 9.96% to 8.48%), for a D-I-D of 0.51. In other words, those in the GCC had an HbA_1c that decreased by 0.51% less than that of patients in the CCC, suggesting that the CCC shows a steeper line declining from baseline to final HbA_1c compared to the GCC, whose line declines less sharply.

In the subgroup analysis of patients whose baseline HbA_1c was ≥ 8%, about 42% in the CCC and 37% in the GCC achieved an HbA_1c < 8% (P = .56) (Table 4). Approximately 83% of patients in the CCC had some degree of HbA_1c improvement—the final HbA_1c was lower than their baseline HbA_1c—whereas this was observed in about 75% of patients in the GCC (P = .19). Of patients whose baseline HbA_1c was < 8%, there was no significant difference in proportion of patients maintaining an HbA_1c < 8% between the groups (P = .57), although some increases in HbA_1c and HbA_1c changes were observed in the GCC (Table 5).

Health care utilization

Patients in the CCC visited pharmacists 5 times on average over 12 months, whereas patients in the GCC had an average of 6 visits (5 ± 2.6 in the CCC vs 6 ± 2.6 in the GCC, P = .01) (Table 6). The mean length between any 2 adjacent visits was significantly different, averaging about 33 days in the CCC compared to 64 days in the GCC (33.2 ± 10 in the CCC vs 63.7 ± 39.4 in the GCC, P < .001). As shown in Figure 2, the GCC shows wider ranges between any adjacent pharmacy visits throughout until the 10th visit. Both groups had a similar number of visits with primary care physicians during the same time period (4.6 ± 1.86 in the CCC vs 4.3 ± 2.51 in the GCC, P = .44). About 30% of patients in the CCC and 47% in the GCC had at least 1 visit to the emergency room or urgent care or had at least 1 hospital admission, for a total of 124 acute care utilizations between the 2 groups combined. Only a small fraction of acute care visits with or without hospitalizations were related to diabetes and its complications (23.1% in the CCC vs 22.0% in the GCC).

Discussion

This is a real-world study that describes HbA_1c changes in patients who maintained pharmacy visits regularly and in those who had a history of a 3-month or longer gap in pharmacy visits. Although the study did not show statistically significant differences in HbA_1c reduction between the 2 groups, pharmacists’ care, overall, provided mean HbA_1c reductions of 1.3%. This result is consistent with those from multiple previous studies.^10-13 It is worth noting that the final HbA_1c was numerically lower in patients who followed up with pharmacists regularly than in patients with gaps in visits, with a difference of about 0.5 percentage points. This difference is considered clinically significant,¹⁷ and potentially could be even greater if the study duration was longer, as depicted by the slope of HbA_1c reductions in the D-I-D model (Figure 1).

Previous studies have shown that pharmacist visits are conducted in shorter intervals than primary care physician visits to provide closer follow-up and to resolve any medication-related problems that may hinder therapeutic outcome improvements.^3-4,7-9 Increasing access via pharmacists is particularly important in this clinic, where resident physician continuity and access is challenging. The pharmacist-driven program described in this study does not deviate from the norm, and this study confirms that pharmacist care, regardless of gaps in pharmacist visits, may still be beneficial.

Another notable finding from this study was that although the average number of pharmacist visits per patient was significantly different, this difference of 1 visit did not result in a statistically significant improvement in HbA_1c. In fact, the average number of pharmacist visits per patient seemed to be within the reported range by Choe et al in a similar setting.⁷ Conversely, patients with a history of a gap in pharmacist visits spent longer durations under pharmacist care compared to those who had continuous follow-up. This could mean that it may take longer times or 1 additional visit to achieve similar HbA_1c results with continuous pharmacist care. Higher number of visits with pharmacists in the group with the history of gaps between pharmacist visits could have been facilitated by resident physicians, as both groups had a similar number of visits with them. Although this is not conclusive, identifying the optimal number of visits with pharmacists in this underserved population could be beneficial in strategizing pharmacist visits. Acute care utilization was not different between the 2 groups, and most cases that led to acute care utilization were not directly related to diabetes or its complications.

The average HbA_1c at the end of the study did not measure < 8%, a target that was reached by less than half of patients from each group; however, this study is a snapshot of a series of ongoing clinical pharmacy services. About 25% of our patients started their first visit with a pharmacist less than 6 months from the study end date, and these patients may not have had enough time with pharmacists for their HbA_1c to reach below the target goal. In addition, most patients in this clinic were enrolled in public health plans and may carry a significant burden of social and behavioral factors that can affect diabetes management.^18,19 These patients may need longer care by pharmacists along with other integrated services, such as behavioral health and social work, to achieve optimal HbA_1c levels.²⁰

There are several limitations to this study, including the lack of a propensity matched control group of patients who only had resident physician visits; thus, it is hard to test the true impact of continuous or intermittent pharmacist visits on the therapeutic outcomes. The study also does not address potential social, economic, and physical environment factors that might have contributed to pharmacist visits and to overall diabetes care. These factors can negatively impact diabetes control and addressing them could help with an individualized diabetes management approach.^17,18 Additionally, by nature of being a descriptive study, the results may be subject to undetermined confounding factors.

Conclusion

Patients maintaining continuous pharmacist visits do not have statistically significant differences in change in HbA_1c compared to patients who had a history of 3-month or longer gaps in pharmacist visits at a resident physician primary care safety-net clinic. However, patients with diabetes will likely derive a benefit in HbA_1c reduction regardless of regularity of pharmacist care. This finding still holds true in collaboration with resident physicians who also regularly meet with patients.

The study highlights that it is important to integrate clinical pharmacists into primary care teams for improved therapeutic outcomes. It is our hope that regular visits to pharmacists can be a gateway for behavioral health and social work referrals, thereby addressing pharmacist-identified social barriers. Furthermore, exploration of socioeconomic and behavioral barriers to pharmacist visits is necessary to address and improve the patient experience, health care delivery, and health outcomes.

Acknowledgments: The authors thank Roxanna Perez, PharmD, Amy Li, and Julie Dopheide, PharmD, BCPP, FASHP for their contributions to this project.

Corresponding author: Michelle Koun Lee Chu, PharmD, BCACP, APh, Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, CA 90089-9121; [email protected].

Financial disclosures: None.

From Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA (Drs. Chu and Ma and Mimi Lou), and Department of Family Medicine, Keck Medicine, University of Southern California, Los Angeles, CA (Dr. Suh).

Objective: The objective of this study is to describe HbA_1c changes in patients who maintained continuous pharmacist care vs patients who had a gap in pharmacist care of 3 months or longer. 

Methods: This retrospective study was conducted from October 1, 2018, to September 30, 2019. Electronic health record data from an academic-affiliated, safety-net resident physician primary care clinic were collected to observe HbA_1c changes between patients with continuous pharmacist care and patients who had a gap of 3 months or longer in pharmacist care. A total of 189 patients met the inclusion criteria and were divided into 2 groups: those with continuous care and those with gaps in care. Data were analyzed using the Mann-Whitney test for continuous variables and the χ² (or Fisher exact) test for categorical variables. The differences-in-differences model was used to compare the changes in HbA_1c between the 2 groups.

Results: There was no significant difference in changes in HbA_1c between the continuous care group and the gaps in care group, although the mean magnitude of HbA_1c changes was numerically greater in the continuous care group (-1.48% vs -0.97%). Overall, both groups showed improvement in their HbA_1c levels and had similar numbers of primary care physician visits and acute care utilizations, while the gaps in care group had longer duration with pharmacists and between the adjacent pharmacist visits.

Conclusion: Maintaining continuous, regular visits with a pharmacist at a safety-net resident physician primary care clinic did not show a significant difference in HbA_1c changes compared to having gaps in pharmacist care. Future studies on socioeconomic and behavioral burden on HbA_1c improvement and on pharmacist visits in these populations should be explored.

Keywords: clinical pharmacist; diabetes management; continuous visit; primary care clinic.

Pharmacists have unique skills in identifying and resolving problems related to the safety and efficacy of drug therapy while addressing medication adherence and access for patients. Their expertise is especially important to meet the care needs of a growing population with chronic conditions amidst a primary care physician shortage.¹ As health care systems move toward value-based care, emphasis on improvement in quality and health measures have become central in care delivery. Pharmacists have been integrated into team-based care in primary care settings, but the value-based shift has opened more opportunities for pharmacists to address unmet quality standards.^2-5

Many studies have reported that the integration of pharmacists into team-based care improves health outcomes and reduces overall health care costs.^6-9 Specifically, when pharmacists were added to primary care teams to provide diabetes management, hemoglobin HbA_1c levels were reduced compared to teams without pharmacists.^10-13 Offering pharmacist visits as often as every 2 weeks to 3 months, with each patient having an average of 4.7 visits, resulted in improved therapeutic outcomes.^3,7 During visits, pharmacists address the need for additional drug therapy, deprescribe unnecessary therapy, correct insufficient doses or durations, and switch patients to more cost-efficient drug therapy.⁹ Likewise, patients who visit pharmacists in addition to seeing their primary care physician can have medication-related concerns resolved and improve their therapeutic outcomes.^10,11

Not much is known about the magnitude of HbA_1c change based on the regularity of pharmacist visits. Although pharmacists offer follow-up appointments in reasonable time intervals, patients do not keep every appointment for a variety of reasons, including forgetfulness, personal issues, and a lack of transportation.¹⁴ Such missed appointments can negatively impact health outcomes.^14-16 The purpose of this study is to describe HbA_1c changes in patients who maintained continuous, regular pharmacist visits without a 3-month gap and in patients who had history of inconsistent pharmacist visits with a gap of 3 months or longer. Furthermore, this study describes the frequency of health care utilization for these 2 groups.

Methods

Setting

The Internal Medicine resident physician primary care clinic is 1 of 2 adult primary care clinics at an academic, urban, public medical center. It is in the heart of East Los Angeles, where predominantly Spanish-speaking and minority populations reside. The clinic has approximately 19000 empaneled patients and is the largest resident primary care clinic in the public health system. The clinical pharmacy service addresses unmet quality standards, specifically HbA_1c. The clinical pharmacists are co-located and collaborate with resident physicians, attending physicians, care managers, nurses, social workers, and community health workers at the clinic. They operate under collaborative practice agreements with prescriptive authority, except for controlled substances, specialty drugs, and antipsychotic medications.

Pharmacist visit

Patients are primarily referred by resident physicians to clinical pharmacists when their HbA_1c level is above 8% for an extended period, when poor adherence and low health literacy are evident regardless of HbA_1c level, or when a complex medication regimen requires comprehensive medication review and reconciliation. The referral occurs through warm handoff by resident physicians as well as clinic nurses, and it is embedded in the clinic flow. Patients continue their visits with resident physicians for issues other than their referral to clinical pharmacists. The visits with pharmacists are appointment-based, occur independently from resident physician visits, and continue until the patient’s HbA_1c level or adherence is optimized. Clinical pharmacists continue to follow up with patients who may have reached their target HbA_1c level but still are deemed unstable due to inconsistency in their self-management and medication adherence.

After the desirable HbA_1c target is achieved along with full adherence to medications and self-management, clinical pharmacists will hand off patients back to resident physicians. At each visit, pharmacists perform a comprehensive medication assessment and reconciliation that includes adjusting medication therapy, placing orders for necessary laboratory tests and prescriptions, and assessing medication adherence. They also evaluate patients’ signs and symptoms for hyperglycemic complications, hypoglycemia, and other potential treatment-related adverse events. These are all within the pharmacist’s scope of practice in comprehensive medication management. Patient education is provided with the teach-back method and includes lifestyle modifications and medication counseling (Table 1). Pharmacists offer face-to-face visits as frequently as every 1 to 2 weeks to every 4 to 6 weeks, depending on the level of complexity and the severity of a patient’s conditions and medications. For patients whose HbA_1c has reached the target range but have not been deemed stable, pharmacists continue to check in with them every 2 months. Phone visits are also utilized as an additional care delivery method for patients having difficulty showing up for face-to-face visits or needing quick assessment of medication adherence and responses to changes in drug treatment in between the face-to-face visits. The maximal interval between pharmacist visits is offered no longer than every 8 weeks. Patients are contacted via phone or mail by the nursing staff to reschedule if they miss their appointments with pharmacists. Every pharmacy visit is documented in the patient’s electronic medical record.

Study design

This is a retrospective study describing the HbA_1c changes in a patient group that maintained pharmacist visits, with each interval less than 3 months, and in another group, who had a history of a 3-month or longer gap between pharmacist visits. The data were obtained from patients’ electronic medical records during the study period of October 1, 2018, and September 30, 2019, and collected using a HIPAA-compliant, electronic data storage website, REDCap. The institutional review board approval was obtained under HS-19-00929. Patients 18 years and older who were referred by primary care resident physicians for diabetes management, and had 2 or more visits with a pharmacist within the study period, were included. Patients were excluded if they had only 1 HbA_1c drawn during the study period, were referred to a pharmacist for reasons other than diabetes management, were concurrently managed by an endocrinologist, had only 1 visit with a pharmacist, or had no visits with their primary care resident physician for over a year. The patients were then divided into 2 groups: continuous care cohort (CCC) and gap in care cohort (GCC). Both face-to-face and phone visits were counted as pharmacist visits for each group.

Outcomes

The primary outcome was the change in HbA_1c from baseline between the 2 groups. Baseline HbA_1c was considered as the HbA_1c value obtained within 3 months prior to, or within 1 month, of the first visit with the pharmacist during the study period. The final HbA_1c was considered the value measured within 1 month of, or 3 months after, the patient’s last visit with the pharmacist during the study period.

Several subgroup analyses were conducted to examine the relationship between HbA_1c and each group. Among patients whose baseline HbA_1c was ≥ 8%, we looked at the percentage of patients reaching HbA_1c < 8%, the percentage of patients showing any level of improvement in HbA_1c, and the change in HbA_1c for each group. We also looked at the percentage of patients with baseline HbA_1c < 8% maintaining the level throughout the study period and the change in HbA_1c for each group. Additionally, we looked at health care utilization, which included pharmacist visits, primary care physician visits, emergency room and urgent care visits, and hospitalizations for each group. The latter 3 types of utilization were grouped as acute care utilization and further analyzed for visit reasons, which were subsequently categorized as diabetes related and non-diabetes related. The diabetes related reasons linking to acute care utilization were defined as any episodes related to hypoglycemia, diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), foot ulcers, retinopathy, and osteomyelitis infection. All other reasons leading to acute care utilization were categorized as non-diabetes related.

Statistical analysis

Descriptive analyses were conducted using the Mann-Whitney test for continuous data and χ² (or Fisher exact) test for categorical data. A basic difference-in-differences (D-I-D) method was used to compare the changes of HbA_1c between the CCC and GCC over 2 time points: baseline and final measurements. The repeated measures ANOVA was used for analyzing D-I-D. P < .05 was considered significant. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Results

Baseline data

A total of 1272 patients were identified within the study period, and 189 met the study inclusion criteria. The CCC included 132 patients, the GCC 57. The mean age of patients in both groups was similar at 57 years old (P = .39). Most patients had Medicaid as their primary insurance. About one-third of patients in each group experienced clinical atherosclerotic cardiovascular disease, and about 12% overall had chronic kidney disease stage 3 and higher. The average number of days that patients were under pharmacist care during the study period was longer in the GCC compared to the CCC, and it was statistically significant (P < .001) (Table 2). The mean ± SD baseline HbA_1c for the CCC and GCC was 10.0% ± 2.0% and 9.9% ± 1.7%, respectively, and the difference was not statistically significant (P = .93). About 86% of patients in the CCC and 90% in the GCC had a baseline HbA_1c of ≥ 8%.

The mean change in HbA_1c between the 2 groups was not statistically significant (-1.5% ± 2.0% in the CCC vs -1.0% ± 2.1% in the GCC, P = .36) (Table 3). However, an absolute mean HbA_1c reduction of 1.3% was observed in both groups combined at the end of the study. Figure 1 shows a D-I-D model of the 2 groups. Based on the output, the P value of .11 on the interaction term (time*group) indicates that the D-I-D in HbA_1c change from baseline to final between the CCC and GCC is not statistically different. However, the magnitude of the difference calculated from the LSMEANS results showed a trend. The HbA_1c from baseline to final measurement of patients in the GCC declined by 0.97 percentage points (from 9.94% to 8.97%), while those in the CCC saw their HbA_1c decline by 1.48 percentage points (from 9.96% to 8.48%), for a D-I-D of 0.51. In other words, those in the GCC had an HbA_1c that decreased by 0.51% less than that of patients in the CCC, suggesting that the CCC shows a steeper line declining from baseline to final HbA_1c compared to the GCC, whose line declines less sharply.

In the subgroup analysis of patients whose baseline HbA_1c was ≥ 8%, about 42% in the CCC and 37% in the GCC achieved an HbA_1c < 8% (P = .56) (Table 4). Approximately 83% of patients in the CCC had some degree of HbA_1c improvement—the final HbA_1c was lower than their baseline HbA_1c—whereas this was observed in about 75% of patients in the GCC (P = .19). Of patients whose baseline HbA_1c was < 8%, there was no significant difference in proportion of patients maintaining an HbA_1c < 8% between the groups (P = .57), although some increases in HbA_1c and HbA_1c changes were observed in the GCC (Table 5).

Health care utilization

Patients in the CCC visited pharmacists 5 times on average over 12 months, whereas patients in the GCC had an average of 6 visits (5 ± 2.6 in the CCC vs 6 ± 2.6 in the GCC, P = .01) (Table 6). The mean length between any 2 adjacent visits was significantly different, averaging about 33 days in the CCC compared to 64 days in the GCC (33.2 ± 10 in the CCC vs 63.7 ± 39.4 in the GCC, P < .001). As shown in Figure 2, the GCC shows wider ranges between any adjacent pharmacy visits throughout until the 10th visit. Both groups had a similar number of visits with primary care physicians during the same time period (4.6 ± 1.86 in the CCC vs 4.3 ± 2.51 in the GCC, P = .44). About 30% of patients in the CCC and 47% in the GCC had at least 1 visit to the emergency room or urgent care or had at least 1 hospital admission, for a total of 124 acute care utilizations between the 2 groups combined. Only a small fraction of acute care visits with or without hospitalizations were related to diabetes and its complications (23.1% in the CCC vs 22.0% in the GCC).

Discussion

This is a real-world study that describes HbA_1c changes in patients who maintained pharmacy visits regularly and in those who had a history of a 3-month or longer gap in pharmacy visits. Although the study did not show statistically significant differences in HbA_1c reduction between the 2 groups, pharmacists’ care, overall, provided mean HbA_1c reductions of 1.3%. This result is consistent with those from multiple previous studies.^10-13 It is worth noting that the final HbA_1c was numerically lower in patients who followed up with pharmacists regularly than in patients with gaps in visits, with a difference of about 0.5 percentage points. This difference is considered clinically significant,¹⁷ and potentially could be even greater if the study duration was longer, as depicted by the slope of HbA_1c reductions in the D-I-D model (Figure 1).

Previous studies have shown that pharmacist visits are conducted in shorter intervals than primary care physician visits to provide closer follow-up and to resolve any medication-related problems that may hinder therapeutic outcome improvements.^3-4,7-9 Increasing access via pharmacists is particularly important in this clinic, where resident physician continuity and access is challenging. The pharmacist-driven program described in this study does not deviate from the norm, and this study confirms that pharmacist care, regardless of gaps in pharmacist visits, may still be beneficial.

Another notable finding from this study was that although the average number of pharmacist visits per patient was significantly different, this difference of 1 visit did not result in a statistically significant improvement in HbA_1c. In fact, the average number of pharmacist visits per patient seemed to be within the reported range by Choe et al in a similar setting.⁷ Conversely, patients with a history of a gap in pharmacist visits spent longer durations under pharmacist care compared to those who had continuous follow-up. This could mean that it may take longer times or 1 additional visit to achieve similar HbA_1c results with continuous pharmacist care. Higher number of visits with pharmacists in the group with the history of gaps between pharmacist visits could have been facilitated by resident physicians, as both groups had a similar number of visits with them. Although this is not conclusive, identifying the optimal number of visits with pharmacists in this underserved population could be beneficial in strategizing pharmacist visits. Acute care utilization was not different between the 2 groups, and most cases that led to acute care utilization were not directly related to diabetes or its complications.

The average HbA_1c at the end of the study did not measure < 8%, a target that was reached by less than half of patients from each group; however, this study is a snapshot of a series of ongoing clinical pharmacy services. About 25% of our patients started their first visit with a pharmacist less than 6 months from the study end date, and these patients may not have had enough time with pharmacists for their HbA_1c to reach below the target goal. In addition, most patients in this clinic were enrolled in public health plans and may carry a significant burden of social and behavioral factors that can affect diabetes management.^18,19 These patients may need longer care by pharmacists along with other integrated services, such as behavioral health and social work, to achieve optimal HbA_1c levels.²⁰

There are several limitations to this study, including the lack of a propensity matched control group of patients who only had resident physician visits; thus, it is hard to test the true impact of continuous or intermittent pharmacist visits on the therapeutic outcomes. The study also does not address potential social, economic, and physical environment factors that might have contributed to pharmacist visits and to overall diabetes care. These factors can negatively impact diabetes control and addressing them could help with an individualized diabetes management approach.^17,18 Additionally, by nature of being a descriptive study, the results may be subject to undetermined confounding factors.

Conclusion

Patients maintaining continuous pharmacist visits do not have statistically significant differences in change in HbA_1c compared to patients who had a history of 3-month or longer gaps in pharmacist visits at a resident physician primary care safety-net clinic. However, patients with diabetes will likely derive a benefit in HbA_1c reduction regardless of regularity of pharmacist care. This finding still holds true in collaboration with resident physicians who also regularly meet with patients.

The study highlights that it is important to integrate clinical pharmacists into primary care teams for improved therapeutic outcomes. It is our hope that regular visits to pharmacists can be a gateway for behavioral health and social work referrals, thereby addressing pharmacist-identified social barriers. Furthermore, exploration of socioeconomic and behavioral barriers to pharmacist visits is necessary to address and improve the patient experience, health care delivery, and health outcomes.

Acknowledgments: The authors thank Roxanna Perez, PharmD, Amy Li, and Julie Dopheide, PharmD, BCPP, FASHP for their contributions to this project.

Corresponding author: Michelle Koun Lee Chu, PharmD, BCACP, APh, Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, CA 90089-9121; [email protected].

Financial disclosures: None.

From Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA (Drs. Chu and Ma and Mimi Lou), and Department of Family Medicine, Keck Medicine, University of Southern California, Los Angeles, CA (Dr. Suh).

Objective: The objective of this study is to describe HbA_1c changes in patients who maintained continuous pharmacist care vs patients who had a gap in pharmacist care of 3 months or longer. 

Methods: This retrospective study was conducted from October 1, 2018, to September 30, 2019. Electronic health record data from an academic-affiliated, safety-net resident physician primary care clinic were collected to observe HbA_1c changes between patients with continuous pharmacist care and patients who had a gap of 3 months or longer in pharmacist care. A total of 189 patients met the inclusion criteria and were divided into 2 groups: those with continuous care and those with gaps in care. Data were analyzed using the Mann-Whitney test for continuous variables and the χ² (or Fisher exact) test for categorical variables. The differences-in-differences model was used to compare the changes in HbA_1c between the 2 groups.

Results: There was no significant difference in changes in HbA_1c between the continuous care group and the gaps in care group, although the mean magnitude of HbA_1c changes was numerically greater in the continuous care group (-1.48% vs -0.97%). Overall, both groups showed improvement in their HbA_1c levels and had similar numbers of primary care physician visits and acute care utilizations, while the gaps in care group had longer duration with pharmacists and between the adjacent pharmacist visits.

Conclusion: Maintaining continuous, regular visits with a pharmacist at a safety-net resident physician primary care clinic did not show a significant difference in HbA_1c changes compared to having gaps in pharmacist care. Future studies on socioeconomic and behavioral burden on HbA_1c improvement and on pharmacist visits in these populations should be explored.

Keywords: clinical pharmacist; diabetes management; continuous visit; primary care clinic.

Pharmacists have unique skills in identifying and resolving problems related to the safety and efficacy of drug therapy while addressing medication adherence and access for patients. Their expertise is especially important to meet the care needs of a growing population with chronic conditions amidst a primary care physician shortage.¹ As health care systems move toward value-based care, emphasis on improvement in quality and health measures have become central in care delivery. Pharmacists have been integrated into team-based care in primary care settings, but the value-based shift has opened more opportunities for pharmacists to address unmet quality standards.^2-5

Many studies have reported that the integration of pharmacists into team-based care improves health outcomes and reduces overall health care costs.^6-9 Specifically, when pharmacists were added to primary care teams to provide diabetes management, hemoglobin HbA_1c levels were reduced compared to teams without pharmacists.^10-13 Offering pharmacist visits as often as every 2 weeks to 3 months, with each patient having an average of 4.7 visits, resulted in improved therapeutic outcomes.^3,7 During visits, pharmacists address the need for additional drug therapy, deprescribe unnecessary therapy, correct insufficient doses or durations, and switch patients to more cost-efficient drug therapy.⁹ Likewise, patients who visit pharmacists in addition to seeing their primary care physician can have medication-related concerns resolved and improve their therapeutic outcomes.^10,11

Not much is known about the magnitude of HbA_1c change based on the regularity of pharmacist visits. Although pharmacists offer follow-up appointments in reasonable time intervals, patients do not keep every appointment for a variety of reasons, including forgetfulness, personal issues, and a lack of transportation.¹⁴ Such missed appointments can negatively impact health outcomes.^14-16 The purpose of this study is to describe HbA_1c changes in patients who maintained continuous, regular pharmacist visits without a 3-month gap and in patients who had history of inconsistent pharmacist visits with a gap of 3 months or longer. Furthermore, this study describes the frequency of health care utilization for these 2 groups.

Methods

Setting

The Internal Medicine resident physician primary care clinic is 1 of 2 adult primary care clinics at an academic, urban, public medical center. It is in the heart of East Los Angeles, where predominantly Spanish-speaking and minority populations reside. The clinic has approximately 19000 empaneled patients and is the largest resident primary care clinic in the public health system. The clinical pharmacy service addresses unmet quality standards, specifically HbA_1c. The clinical pharmacists are co-located and collaborate with resident physicians, attending physicians, care managers, nurses, social workers, and community health workers at the clinic. They operate under collaborative practice agreements with prescriptive authority, except for controlled substances, specialty drugs, and antipsychotic medications.

Pharmacist visit

Patients are primarily referred by resident physicians to clinical pharmacists when their HbA_1c level is above 8% for an extended period, when poor adherence and low health literacy are evident regardless of HbA_1c level, or when a complex medication regimen requires comprehensive medication review and reconciliation. The referral occurs through warm handoff by resident physicians as well as clinic nurses, and it is embedded in the clinic flow. Patients continue their visits with resident physicians for issues other than their referral to clinical pharmacists. The visits with pharmacists are appointment-based, occur independently from resident physician visits, and continue until the patient’s HbA_1c level or adherence is optimized. Clinical pharmacists continue to follow up with patients who may have reached their target HbA_1c level but still are deemed unstable due to inconsistency in their self-management and medication adherence.

After the desirable HbA_1c target is achieved along with full adherence to medications and self-management, clinical pharmacists will hand off patients back to resident physicians. At each visit, pharmacists perform a comprehensive medication assessment and reconciliation that includes adjusting medication therapy, placing orders for necessary laboratory tests and prescriptions, and assessing medication adherence. They also evaluate patients’ signs and symptoms for hyperglycemic complications, hypoglycemia, and other potential treatment-related adverse events. These are all within the pharmacist’s scope of practice in comprehensive medication management. Patient education is provided with the teach-back method and includes lifestyle modifications and medication counseling (Table 1). Pharmacists offer face-to-face visits as frequently as every 1 to 2 weeks to every 4 to 6 weeks, depending on the level of complexity and the severity of a patient’s conditions and medications. For patients whose HbA_1c has reached the target range but have not been deemed stable, pharmacists continue to check in with them every 2 months. Phone visits are also utilized as an additional care delivery method for patients having difficulty showing up for face-to-face visits or needing quick assessment of medication adherence and responses to changes in drug treatment in between the face-to-face visits. The maximal interval between pharmacist visits is offered no longer than every 8 weeks. Patients are contacted via phone or mail by the nursing staff to reschedule if they miss their appointments with pharmacists. Every pharmacy visit is documented in the patient’s electronic medical record.

Study design

This is a retrospective study describing the HbA_1c changes in a patient group that maintained pharmacist visits, with each interval less than 3 months, and in another group, who had a history of a 3-month or longer gap between pharmacist visits. The data were obtained from patients’ electronic medical records during the study period of October 1, 2018, and September 30, 2019, and collected using a HIPAA-compliant, electronic data storage website, REDCap. The institutional review board approval was obtained under HS-19-00929. Patients 18 years and older who were referred by primary care resident physicians for diabetes management, and had 2 or more visits with a pharmacist within the study period, were included. Patients were excluded if they had only 1 HbA_1c drawn during the study period, were referred to a pharmacist for reasons other than diabetes management, were concurrently managed by an endocrinologist, had only 1 visit with a pharmacist, or had no visits with their primary care resident physician for over a year. The patients were then divided into 2 groups: continuous care cohort (CCC) and gap in care cohort (GCC). Both face-to-face and phone visits were counted as pharmacist visits for each group.

Outcomes

The primary outcome was the change in HbA_1c from baseline between the 2 groups. Baseline HbA_1c was considered as the HbA_1c value obtained within 3 months prior to, or within 1 month, of the first visit with the pharmacist during the study period. The final HbA_1c was considered the value measured within 1 month of, or 3 months after, the patient’s last visit with the pharmacist during the study period.

Several subgroup analyses were conducted to examine the relationship between HbA_1c and each group. Among patients whose baseline HbA_1c was ≥ 8%, we looked at the percentage of patients reaching HbA_1c < 8%, the percentage of patients showing any level of improvement in HbA_1c, and the change in HbA_1c for each group. We also looked at the percentage of patients with baseline HbA_1c < 8% maintaining the level throughout the study period and the change in HbA_1c for each group. Additionally, we looked at health care utilization, which included pharmacist visits, primary care physician visits, emergency room and urgent care visits, and hospitalizations for each group. The latter 3 types of utilization were grouped as acute care utilization and further analyzed for visit reasons, which were subsequently categorized as diabetes related and non-diabetes related. The diabetes related reasons linking to acute care utilization were defined as any episodes related to hypoglycemia, diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), foot ulcers, retinopathy, and osteomyelitis infection. All other reasons leading to acute care utilization were categorized as non-diabetes related.

Statistical analysis

Descriptive analyses were conducted using the Mann-Whitney test for continuous data and χ² (or Fisher exact) test for categorical data. A basic difference-in-differences (D-I-D) method was used to compare the changes of HbA_1c between the CCC and GCC over 2 time points: baseline and final measurements. The repeated measures ANOVA was used for analyzing D-I-D. P < .05 was considered significant. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Results

Baseline data

A total of 1272 patients were identified within the study period, and 189 met the study inclusion criteria. The CCC included 132 patients, the GCC 57. The mean age of patients in both groups was similar at 57 years old (P = .39). Most patients had Medicaid as their primary insurance. About one-third of patients in each group experienced clinical atherosclerotic cardiovascular disease, and about 12% overall had chronic kidney disease stage 3 and higher. The average number of days that patients were under pharmacist care during the study period was longer in the GCC compared to the CCC, and it was statistically significant (P < .001) (Table 2). The mean ± SD baseline HbA_1c for the CCC and GCC was 10.0% ± 2.0% and 9.9% ± 1.7%, respectively, and the difference was not statistically significant (P = .93). About 86% of patients in the CCC and 90% in the GCC had a baseline HbA_1c of ≥ 8%.

The mean change in HbA_1c between the 2 groups was not statistically significant (-1.5% ± 2.0% in the CCC vs -1.0% ± 2.1% in the GCC, P = .36) (Table 3). However, an absolute mean HbA_1c reduction of 1.3% was observed in both groups combined at the end of the study. Figure 1 shows a D-I-D model of the 2 groups. Based on the output, the P value of .11 on the interaction term (time*group) indicates that the D-I-D in HbA_1c change from baseline to final between the CCC and GCC is not statistically different. However, the magnitude of the difference calculated from the LSMEANS results showed a trend. The HbA_1c from baseline to final measurement of patients in the GCC declined by 0.97 percentage points (from 9.94% to 8.97%), while those in the CCC saw their HbA_1c decline by 1.48 percentage points (from 9.96% to 8.48%), for a D-I-D of 0.51. In other words, those in the GCC had an HbA_1c that decreased by 0.51% less than that of patients in the CCC, suggesting that the CCC shows a steeper line declining from baseline to final HbA_1c compared to the GCC, whose line declines less sharply.

In the subgroup analysis of patients whose baseline HbA_1c was ≥ 8%, about 42% in the CCC and 37% in the GCC achieved an HbA_1c < 8% (P = .56) (Table 4). Approximately 83% of patients in the CCC had some degree of HbA_1c improvement—the final HbA_1c was lower than their baseline HbA_1c—whereas this was observed in about 75% of patients in the GCC (P = .19). Of patients whose baseline HbA_1c was < 8%, there was no significant difference in proportion of patients maintaining an HbA_1c < 8% between the groups (P = .57), although some increases in HbA_1c and HbA_1c changes were observed in the GCC (Table 5).

Health care utilization

Patients in the CCC visited pharmacists 5 times on average over 12 months, whereas patients in the GCC had an average of 6 visits (5 ± 2.6 in the CCC vs 6 ± 2.6 in the GCC, P = .01) (Table 6). The mean length between any 2 adjacent visits was significantly different, averaging about 33 days in the CCC compared to 64 days in the GCC (33.2 ± 10 in the CCC vs 63.7 ± 39.4 in the GCC, P < .001). As shown in Figure 2, the GCC shows wider ranges between any adjacent pharmacy visits throughout until the 10th visit. Both groups had a similar number of visits with primary care physicians during the same time period (4.6 ± 1.86 in the CCC vs 4.3 ± 2.51 in the GCC, P = .44). About 30% of patients in the CCC and 47% in the GCC had at least 1 visit to the emergency room or urgent care or had at least 1 hospital admission, for a total of 124 acute care utilizations between the 2 groups combined. Only a small fraction of acute care visits with or without hospitalizations were related to diabetes and its complications (23.1% in the CCC vs 22.0% in the GCC).

Discussion

This is a real-world study that describes HbA_1c changes in patients who maintained pharmacy visits regularly and in those who had a history of a 3-month or longer gap in pharmacy visits. Although the study did not show statistically significant differences in HbA_1c reduction between the 2 groups, pharmacists’ care, overall, provided mean HbA_1c reductions of 1.3%. This result is consistent with those from multiple previous studies.^10-13 It is worth noting that the final HbA_1c was numerically lower in patients who followed up with pharmacists regularly than in patients with gaps in visits, with a difference of about 0.5 percentage points. This difference is considered clinically significant,¹⁷ and potentially could be even greater if the study duration was longer, as depicted by the slope of HbA_1c reductions in the D-I-D model (Figure 1).

Previous studies have shown that pharmacist visits are conducted in shorter intervals than primary care physician visits to provide closer follow-up and to resolve any medication-related problems that may hinder therapeutic outcome improvements.^3-4,7-9 Increasing access via pharmacists is particularly important in this clinic, where resident physician continuity and access is challenging. The pharmacist-driven program described in this study does not deviate from the norm, and this study confirms that pharmacist care, regardless of gaps in pharmacist visits, may still be beneficial.

Another notable finding from this study was that although the average number of pharmacist visits per patient was significantly different, this difference of 1 visit did not result in a statistically significant improvement in HbA_1c. In fact, the average number of pharmacist visits per patient seemed to be within the reported range by Choe et al in a similar setting.⁷ Conversely, patients with a history of a gap in pharmacist visits spent longer durations under pharmacist care compared to those who had continuous follow-up. This could mean that it may take longer times or 1 additional visit to achieve similar HbA_1c results with continuous pharmacist care. Higher number of visits with pharmacists in the group with the history of gaps between pharmacist visits could have been facilitated by resident physicians, as both groups had a similar number of visits with them. Although this is not conclusive, identifying the optimal number of visits with pharmacists in this underserved population could be beneficial in strategizing pharmacist visits. Acute care utilization was not different between the 2 groups, and most cases that led to acute care utilization were not directly related to diabetes or its complications.

The average HbA_1c at the end of the study did not measure < 8%, a target that was reached by less than half of patients from each group; however, this study is a snapshot of a series of ongoing clinical pharmacy services. About 25% of our patients started their first visit with a pharmacist less than 6 months from the study end date, and these patients may not have had enough time with pharmacists for their HbA_1c to reach below the target goal. In addition, most patients in this clinic were enrolled in public health plans and may carry a significant burden of social and behavioral factors that can affect diabetes management.^18,19 These patients may need longer care by pharmacists along with other integrated services, such as behavioral health and social work, to achieve optimal HbA_1c levels.²⁰

There are several limitations to this study, including the lack of a propensity matched control group of patients who only had resident physician visits; thus, it is hard to test the true impact of continuous or intermittent pharmacist visits on the therapeutic outcomes. The study also does not address potential social, economic, and physical environment factors that might have contributed to pharmacist visits and to overall diabetes care. These factors can negatively impact diabetes control and addressing them could help with an individualized diabetes management approach.^17,18 Additionally, by nature of being a descriptive study, the results may be subject to undetermined confounding factors.

Conclusion

Patients maintaining continuous pharmacist visits do not have statistically significant differences in change in HbA_1c compared to patients who had a history of 3-month or longer gaps in pharmacist visits at a resident physician primary care safety-net clinic. However, patients with diabetes will likely derive a benefit in HbA_1c reduction regardless of regularity of pharmacist care. This finding still holds true in collaboration with resident physicians who also regularly meet with patients.

The study highlights that it is important to integrate clinical pharmacists into primary care teams for improved therapeutic outcomes. It is our hope that regular visits to pharmacists can be a gateway for behavioral health and social work referrals, thereby addressing pharmacist-identified social barriers. Furthermore, exploration of socioeconomic and behavioral barriers to pharmacist visits is necessary to address and improve the patient experience, health care delivery, and health outcomes.

Acknowledgments: The authors thank Roxanna Perez, PharmD, Amy Li, and Julie Dopheide, PharmD, BCPP, FASHP for their contributions to this project.

Corresponding author: Michelle Koun Lee Chu, PharmD, BCACP, APh, Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, CA 90089-9121; [email protected].

Financial disclosures: None.

From the Fraser Health Authority, Surrey, BC, Canada (Drs. Yousefi and Paletta), and Catalyst Consulting Inc., Vancouver, BC, Canada (Elayne McIvor).

Objective: Despite the ongoing growth in the number of hospitalist programs in Canada, their impact on the quality of interprofessional communication, teamwork, and staff satisfaction is not well known. This study aimed to evaluate perceptions of frontline care providers and hospital managers about the impact of the implementation of 3 new hospitalist services on care quality, teamwork, and interprofessional communication.

Design: We used an online survey and semistructured interviews to evaluate respondents’ views on quality of interprofessional communication and collaboration, impact of the new services on quality of care, and overall staff satisfaction with the new inpatient care model.

Setting: Integrated Regional Health Authority in British Columbia, Canada.

Participants: Participants included hospital administrators, frontline care providers (across a range of professions), and hospital and community-based physicians.

Results: The majority of respondents reported high levels of satisfaction with their new hospital medicine services. They identified improvements in interprofessional collaboration and communication between hospitalists and other professionals, which were attributed to enhanced onsite presence of physicians. They also perceived improvements in quality of care and efficiency. On the other hand, they identified a number of challenges with the change process, and raised concerns about the impact of patient handoffs on care quality and efficiency.

Conclusion: Across 3 very different acute care settings, the implementation of a hospitalist service was widely perceived to have resulted in improved teamwork, quality of care, and interprofessional communication.

Keywords: hospital medicine; hospitalist; teamwork; interprofessional collaboration.

Fraser Health Authority (FH) is an integrated regional health system with one of the largest regional Hospital Medicine (HM) networks in Canada.⁹ Over the past 2 decades, FH has implemented a number of HM services in its acute care facilities across a range of small and large community and academic hospitals. More recently, 3 hospitalist services were implemented over a 2-year period: new HM services in a tertiary referral center (Site A, July 2016) and a small community hospital (Site B, December 2016), and reintroduction of a hospitalist service in a medium-sized community hospital (Site C, January 2017). This provided a unique opportunity to assess the impact of the implementation of the hospitalist model across a range of facilities. The main objectives of this evaluation were to understand the level of physician, nursing, allied staff, and hospital administration satisfaction with the new hospitalist model, as well as the perceived impact of the service on efficiency and quality of care. As such, FH engaged an external consultant (EM) to conduct a comprehensive evaluation of the introduction of its latest HM services.

Methods

Setting

Hospital medicine services are currently available in 10 of 12 acute care facilities within the FH system. The 3 sites described in this evaluation constitute the most recent sites where a hospitalist service was implemented.

Site A is a 272-bed tertiary referral center situated in a rapidly growing community. At the time of our evaluation, 21 Full Time Equivalent (FTE) hospitalists cared for an average of 126 patients, which constituted the majority of adult medical patients. Each day, 8 individuals rounded on admitted patients (average individual census: 16) with another person providing in-house, evening, and overnight coverage. An additional flexible shift during the early afternoon helped with Emergency Department (ED) admissions.

Site B is small, 45-bed community hospital in a semi-rural community. The hospitalist service began in December 2016, with 4 FTE hospitalists caring for an average of 28 patients daily. This constituted 2 hospitalists rounding daily on admitted patients, with on-call coverage provided from home.

Site C is a 188-bed community hospital with a hospitalist service initially introduced in 2005. In 2016, the program was disbanded and the site moved back to a primarily community-based model, in which family physicians in the community were invited to assume the care of hospitalized patients. However, the hospitalist program had to be reintroduced in January 2017 due to poor uptake among PCPs in the community. At the time of evaluation, 19 FTE hospitalists (with 7 hospitalists working daily) provided most responsible physician care to a daily census of 116 patients (average individual census: 16). The program also covered ED admissions in-house until midnight, with overnight call provided from home.

Approach

We adopted a utilization-focused evaluation approach to guide our investigation. In this approach, the assessment is deliberately planned and conducted in a way that it maximizes the likelihood that findings would be used by the organization to inform learning, adaptations, and decision-making.¹¹ To enable this, the evaluator identified the primary intended recipients and engaged them at the start of the evaluation process to understand the main intended uses of the project. Moreover, the evaluator ensured that these intended uses of the evaluation guided all other decisions made throughout the process.

We collected data using an online survey of the staff at the 3 facilities, complemented by a series of semistructured qualitative interviews with FH administrators and frontline providers.

Online survey

We conducted an open online survey of a broad range of stakeholders who worked in the 3 facilities. To develop the questionnaire, we searched our department’s archives for previous surveys conducted from 2001 to 2005. We also interviewed the regional HM program management team to identify priority areas and reached out to the local leadership of the 3 acute care facilities for their input and support of the project. We refined the survey through several iterations, seeking input from experts in the FH Department of Evaluation and Research. The final questionnaire contained 10 items, including a mix of closed- and open-ended questions (Appendix A).

To reach the target audience, we collaborated with each hospital’s local leadership as well as the Divisions of Family Practice (DFP) that support local community PCPs in each hospital community.¹⁰ Existing email lists were compiled to create a master electronic survey distribution list. The initial invitation and 3 subsequent reminders were disseminated to the following target groups: hospital physicians (both hospitalists and nonhospitalists), PCPs, nursing and other allied professionals, administrators, and DFP leadership.

The survey consent form, background information, questions, and online platform (SimpleSurvey, Montreal, QC) were approved by FH’s Privacy Department. All respondents were required to provide their consent and able to withdraw at any time. Survey responses were kept anonymous and confidential, with results captured automatically into a spreadsheet by the survey platform. As an incentive for participation, respondents had the opportunity to win 1 of 3 $100 Visa gift cards. Personal contact information provided for the prize draw was collected in a separate survey that could not link back to respondents’ answers. The survey was trialed several times by the evaluation team to address any technical challenges before dissemination to the targeted participants.

Qualitative interviews

We conducted semistructured interviews with a purposive sample of FH administrators and frontline providers (Appendix B). The interview questions broadly mirrored the survey but allowed for more in-depth exploration of constructs. Interviewees were recruited through email invitations to selected senior and mid-level local and regional administrators, asking interviewees to refer our team to other contacts, and inviting survey respondents to voluntarily participate in a follow-up interview. One of the authors (EM), a Credentialed Evaluator, conducted all the one-time interviews either in-person at the individual participant’s workplace or by telephone. She did not have pre-existing relationships with any of the interviewees. Interviews were recorded and transcribed for analysis. Interviewees were required to consent to participate and understood that they could withdraw at any point. They were not offered incentives to participate. Interviews were carried out until thematic saturation was reached.

Analysis

A content analysis approach was employed for all qualitative data, which included open-ended responses from the online survey and interview transcripts. One of the authors (EM) conducted the analysis. The following steps were followed in the inductive content analysis process: repeated reading of the raw data, generation of initial thematic codes, organizing and sorting codes into categories (ie, main vs subcategories), coding of all data, quantifying codes, and interpreting themes. When responding to open-ended questions, respondents often provided multiple answers per question. Each of the respondents’ answers were coded. In alignment with the inductive nature of the analysis process, themes emerged organically from the data rather than the researchers using preconceived theories and categories to code the text. This was achieved by postponing the review of relevant literature on the topic until after the analysis was complete and using an external evaluation consultant (with no prior relationship to FH and limited theoretical knowledge of the topic matter) to analyze the data. Descriptive statistics were run on quantitative data in SPSS (v.24, IBM, Armonk, NY). For survey responses to be included in the analysis, the respondents needed to indicate which site they worked at and were required to answer at least 1 other survey question. One interviewee was excluded from the analysis since they were not familiar with the hospitalist model at their site.

Ethics approval

The evaluation protocol was reviewed by FH Department of Evaluation and Research and was deemed exempt from formal research ethics review.

A total of 377 individuals responded to the online survey between January 8 and February 28, 2018 (response rate 14%). The distribution of respondents generally reflected the size of the respective acute care facilities. Compared to the overall sampled population, fewer nurses participated in the survey (45% vs 64%) while the rate of participation for Unit Clerks (14% vs 16%) and allied professionals (12% vs 16%) were similar.

Out of the 45 people approached for an interview, a total of 38 were conducted from January 3 to March 5, 2018 (response rate 84%). The interviews lasted an average of 42 minutes. Interviewees represented a range of administrative and health professional roles (Figure 1). Some interviewees held multiple positions.

Satisfaction with HM service

Across all sites, survey respondents reported high levels of satisfaction with their respective HM services and identified positive impacts on their job satisfaction (Figure 2). Almost all interviewees similarly expressed high satisfaction levels with their HM services (95%; n = 36).

Perceptions of HM service performance

Survey respondents rated the strength of hospitalists’ interprofessional communication and collaboration with other physicians and with care teams. Roughly two-thirds reported that overall hospitalist communication was “good” or “very good.” We also asked participants to rate the frequency at which hospitalists met best practice expectations related to interprofessional teamwork. Across all sites, similar proportions of respondents (23% to 39%) reported that these best practices were met “most of the time” or “always” (Figure 3). Survey questions also assessed perceptions of respondents about the quality and safety of care provided by hospitalists (Figure 4).

Perceptions of the impact of the HM service postimplementation

The majority of survey respondents reported improvements in the quality of communication, professional relationships, and coordination of inpatient care at transition points after the implementation of the HM service (Figure 5). This was also reflected in interviews, where some indicated that it was easier to communicate with hospitalists due to their on-site presence, accessibility, and 24/7 availability (n = 21). They also described improved collaboration within the care teams (n = 7), and easier communication with hospitalists because they were approachable, willing, and receptive (n = 4).

We also asked the survey respondents to assess the impact of the new hospitalist model on different dimensions of care quality, including patient satisfaction, patient experience, efficiency, and overall quality of care (Figure 6). Findings were comparable across these dimensions, with roughly 50-60% of respondents noting positive changes compared to before the implementation of the programs. However, most interviewees identified both positive and negative effects in these areas. Positive impacts included hospitalist on-site presence leading to better accessibility and timeliness of care (n = 5), hospitalists providing continuity to patients/families by working for weeklong rotations (n = 6), hospitalists being particularly skilled at managing complex clinical presentations (n = 2), and hospitalists being able to spend more time with patients (n = 2). On the other hand, some interviewees noted that patients and families did not like seeing multiple doctors due to frequent handoffs between hospitalists (n = 12). They also raised concerns that hospitalists did not know patients’ histories or had relationships with them, potentially leading to longer length of stay and unnecessary investigations (n = 8).

Site-to-site ratings of satisfaction and performance

Survey respondents’ satisfaction and performance ratings varied substantially site-to-site. Across all areas assessed, ratings were consistently highest at Site B (the smallest institution in our evaluation and the most recent addition to the HM network in the health authority). These differences were statistically significant across all survey questions asked.

Discussion

Findings from this study provide insight into the experiences of frontline health care professionals and administrators with the implementation of new HM services across a range of small to large acute care facilities. They indicate that the majority of respondents reported high levels of satisfaction with their hospitalist services. Most also indicated that the service had resulted in improvements compared to prior inpatient care models.

Over half of the survey respondents, and the majority of interviewees, reported a positive impact on interprofessional communication and collaboration. This was largely attributed to enhanced accessibility and availability of hospitalists:

• "Being on-site lends itself to better communication because they’re accessible. Hospitalists always answer the phone, but the general practitioners (GP) don’t always since they may be with other patients." (Dietician, Site A)
• "A big strength is that we have physician presence on the unit all day during scheduled hours, which makes us more accessible to nurses and more able to follow up on patients that we have concerns about." (Physician Leader, Site B)

However, the ratings dropped substantially when they were asked to assess adherence to specific best practices of such communication and collaboration, such as participation in daily check-ins or attendance at team care rounds (Figure 3). Interdisciplinary clinical rounds have been identified as a tool to improve the effectiveness of care teams.¹² A number of elements have been identified as key components of effective rounds.¹³ Bedside rounds have also been found to enhance communication and teamwork.^14,15 In our study, the discrepancy between overall high levels of satisfaction with hospitalists’ communication/collaboration despite low scores on participation in more concrete activities may illustrate the importance of informal and ad hoc opportunities for interactions between hospitalists and other care providers that result from the enhanced presence of hospitalists on care units.⁸ Outside of formal rounds, hospitalists have the ability to interact with other care providers throughout their shifts. Prior studies have shown that hospitalists spend a significant portion of their time communicating with other care team members throughout their workdays.¹⁶ At the same time, the amount of time spent on communication should be balanced against the need for provision of direct care at the bedside. Future research should aim to identify the right balance between these competing priorities, and to understand the nature and quality of the communication between various care providers.

We also aimed to understand the perceptions of study participants about the impact of the HM service on quality of care. Survey participants not only expressed reasonable satisfaction with various aspects of hospitalists’ performance, but also described a positive impact on care quality after the implementation of their new services. This was also reflected in the interviews:

• "The clinical knowledge of the new hospitalists is far better. Some are internal medicine trained, so they bring better knowledge and skills. I feel comfortable that they can take patients and manage them. I wasn’t always comfortable with doing that in the past." (Emergency Physician, Site C)
• "Hospitalists are really familiar with acute care and how it works. They’ve become more familiar with the discharge planning system and thus know more about the resources available. And even something as simple as knowing which forms to use." (Dietician, Site A)

It must be noted that these observations should ideally be corroborated through a robust before-after analysis of various quality measures. While such an analysis was beyond the scope of our current project, we have previously demonstrated that across our network (including the 3 sites included in our evaluation) hospitalist care is associated with lower mortality and readmission rates.⁴ Our findings appear to confirm previous suggestions that hospitalists’ dedicated focus on inpatient care may allow them to develop enhanced skills in the management of common conditions in the acute care setting¹⁷ which can be perceived to be of value to other hospital-based care providers.

The issue of frequent handover among hospitalists was the most commonly identified challenge by both survey respondents and interviewees:

• "They’re very reluctant to discharge patients if it’s their first day with the patient. Even if the previous hospitalist said they were ready for discharge, the new doc wants to run all of their own tests before they feel comfortable. Maybe it’s a trust issue between hospitalists when they hand patients over. It’s also being personally liable for patients if you discharge them." (Patient Care Coordinator, Site A)
• "Communication is an issue. There’s lots of turnover in hospitalists. Relationships were closer with GPs because we had so much more interaction with particular individuals." (Hospitalist Physician Leader, Site A)

It must be noted that we conducted our evaluation in a relatively short time span (within 2 years) after the 3 services were implemented. Developing trust among a large number of hospitalists newly recruited to these programs can take time and may be a factor that can explain the reluctance of some to discharge patients after handoffs. However, concerns about discontinuity of care inherent in the hospitalist model are not new.^18,19 Better continuity has been associated with higher probability of patient discharges²⁰ and improved outcomes.²¹ To address this challenge, the hospitalist community has focused on defining the core competencies associated with high quality handovers,²² and deliberate efforts to improve the quality of handoffs through quality improvement methodologies.²³ Our study participants similarly identified these measures as potential solutions. Despite this, addressing hospitalist continuity of care remains a pressing challenge for the broader hospitalist community.²⁴

Our evaluation has a number of methodological limitations. First, the survey response rate was only 14%, which raises questions about nonresponse bias and the representativeness of the findings to the larger population of interest. While the distribution of respondents was largely similar to the overall sampled population, a number of factors may have impacted our response rate. For example, we were only able to distribute our survey to health care providers’ institutional email addresses. Moreover, while we provided incentives for participation and sent out a number of reminders, we solely relied on one communication modality (ie, electronic communication) and did not utilize other methods (such as posters, reminder at meetings, in-person invitations). Second, while the survey included a number of open-ended questions, many of these responses were at times brief and difficult to interpret and were not included in the analysis. Third, all data collected were self-reported. For example, we could not corroborate comments about participation in interdisciplinary rounds by objective measures such as attendance records or direct observation. Self-report data is subjective in nature and is vulnerable to a range of biases, such as social desirability bias.²⁵ Finally, patient satisfaction and experience with hospitalist care were not assessed by patients themselves. Ideally, standardized cross-site indicators should validate our patient-related results.

As mentioned above, hospitalist performance ratings varied substantially from site-to-site and were consistently higher at Site B (a small community hospital in a semi-rural area), followed by Site C (a medium-sized community hospital) and Site A (a tertiary referral center). The variability in program ratings and perceived hospitalist impacts between sites could be due to a variety of factors, such as the degree of change between the past and current models at each site, differences in hospitalist hiring processes, hospital size and culture, and differences in service design and operations. It may also be related to the timing of the introduction of the HM service, as Site B was the most recent site where the service was established. As such, there may be an element of recall bias behind the observed discrepancies. This highlights the importance of local context on respondent perceptions and suggests that our results may not be generalizable to other institutions with different attributes and characteristics.

Conclusion

Findings from this study have demonstrated that the recent hospitalist services in our health system have improved overall levels of interprofessional communication and teamwork, as well as perceptions of care quality among the majority of participants who reported high levels of satisfaction with their programs. Our findings further highlight the issue of frequent handovers among hospitalists as a pressing and ongoing challenge.

Corresponding Author: Vandad Yousefi, MD, CCFP, Past Regional Department Head – Hospital Medicine, Fraser Health Authority, Central City Tower, Suite 400, 13450 – 102nd Ave, Surrey, BC V3T 0H1; [email protected].

Financial disclosures: This project was funded by the Fraser Health Authority, which provided the funding for hiring of the external consultant to design, implement, and analyze the results of the evaluation program in collaboration with the Regional Hospitalist Program at Fraser Health.

From the Fraser Health Authority, Surrey, BC, Canada (Drs. Yousefi and Paletta), and Catalyst Consulting Inc., Vancouver, BC, Canada (Elayne McIvor).

Objective: Despite the ongoing growth in the number of hospitalist programs in Canada, their impact on the quality of interprofessional communication, teamwork, and staff satisfaction is not well known. This study aimed to evaluate perceptions of frontline care providers and hospital managers about the impact of the implementation of 3 new hospitalist services on care quality, teamwork, and interprofessional communication.

Design: We used an online survey and semistructured interviews to evaluate respondents’ views on quality of interprofessional communication and collaboration, impact of the new services on quality of care, and overall staff satisfaction with the new inpatient care model.

Setting: Integrated Regional Health Authority in British Columbia, Canada.

Participants: Participants included hospital administrators, frontline care providers (across a range of professions), and hospital and community-based physicians.

Results: The majority of respondents reported high levels of satisfaction with their new hospital medicine services. They identified improvements in interprofessional collaboration and communication between hospitalists and other professionals, which were attributed to enhanced onsite presence of physicians. They also perceived improvements in quality of care and efficiency. On the other hand, they identified a number of challenges with the change process, and raised concerns about the impact of patient handoffs on care quality and efficiency.

Conclusion: Across 3 very different acute care settings, the implementation of a hospitalist service was widely perceived to have resulted in improved teamwork, quality of care, and interprofessional communication.

Keywords: hospital medicine; hospitalist; teamwork; interprofessional collaboration.

Fraser Health Authority (FH) is an integrated regional health system with one of the largest regional Hospital Medicine (HM) networks in Canada.⁹ Over the past 2 decades, FH has implemented a number of HM services in its acute care facilities across a range of small and large community and academic hospitals. More recently, 3 hospitalist services were implemented over a 2-year period: new HM services in a tertiary referral center (Site A, July 2016) and a small community hospital (Site B, December 2016), and reintroduction of a hospitalist service in a medium-sized community hospital (Site C, January 2017). This provided a unique opportunity to assess the impact of the implementation of the hospitalist model across a range of facilities. The main objectives of this evaluation were to understand the level of physician, nursing, allied staff, and hospital administration satisfaction with the new hospitalist model, as well as the perceived impact of the service on efficiency and quality of care. As such, FH engaged an external consultant (EM) to conduct a comprehensive evaluation of the introduction of its latest HM services.

Methods

Setting

Hospital medicine services are currently available in 10 of 12 acute care facilities within the FH system. The 3 sites described in this evaluation constitute the most recent sites where a hospitalist service was implemented.

Site A is a 272-bed tertiary referral center situated in a rapidly growing community. At the time of our evaluation, 21 Full Time Equivalent (FTE) hospitalists cared for an average of 126 patients, which constituted the majority of adult medical patients. Each day, 8 individuals rounded on admitted patients (average individual census: 16) with another person providing in-house, evening, and overnight coverage. An additional flexible shift during the early afternoon helped with Emergency Department (ED) admissions.

Site B is small, 45-bed community hospital in a semi-rural community. The hospitalist service began in December 2016, with 4 FTE hospitalists caring for an average of 28 patients daily. This constituted 2 hospitalists rounding daily on admitted patients, with on-call coverage provided from home.

Site C is a 188-bed community hospital with a hospitalist service initially introduced in 2005. In 2016, the program was disbanded and the site moved back to a primarily community-based model, in which family physicians in the community were invited to assume the care of hospitalized patients. However, the hospitalist program had to be reintroduced in January 2017 due to poor uptake among PCPs in the community. At the time of evaluation, 19 FTE hospitalists (with 7 hospitalists working daily) provided most responsible physician care to a daily census of 116 patients (average individual census: 16). The program also covered ED admissions in-house until midnight, with overnight call provided from home.

Approach

We adopted a utilization-focused evaluation approach to guide our investigation. In this approach, the assessment is deliberately planned and conducted in a way that it maximizes the likelihood that findings would be used by the organization to inform learning, adaptations, and decision-making.¹¹ To enable this, the evaluator identified the primary intended recipients and engaged them at the start of the evaluation process to understand the main intended uses of the project. Moreover, the evaluator ensured that these intended uses of the evaluation guided all other decisions made throughout the process.

We collected data using an online survey of the staff at the 3 facilities, complemented by a series of semistructured qualitative interviews with FH administrators and frontline providers.

Online survey

We conducted an open online survey of a broad range of stakeholders who worked in the 3 facilities. To develop the questionnaire, we searched our department’s archives for previous surveys conducted from 2001 to 2005. We also interviewed the regional HM program management team to identify priority areas and reached out to the local leadership of the 3 acute care facilities for their input and support of the project. We refined the survey through several iterations, seeking input from experts in the FH Department of Evaluation and Research. The final questionnaire contained 10 items, including a mix of closed- and open-ended questions (Appendix A).

To reach the target audience, we collaborated with each hospital’s local leadership as well as the Divisions of Family Practice (DFP) that support local community PCPs in each hospital community.¹⁰ Existing email lists were compiled to create a master electronic survey distribution list. The initial invitation and 3 subsequent reminders were disseminated to the following target groups: hospital physicians (both hospitalists and nonhospitalists), PCPs, nursing and other allied professionals, administrators, and DFP leadership.

The survey consent form, background information, questions, and online platform (SimpleSurvey, Montreal, QC) were approved by FH’s Privacy Department. All respondents were required to provide their consent and able to withdraw at any time. Survey responses were kept anonymous and confidential, with results captured automatically into a spreadsheet by the survey platform. As an incentive for participation, respondents had the opportunity to win 1 of 3 $100 Visa gift cards. Personal contact information provided for the prize draw was collected in a separate survey that could not link back to respondents’ answers. The survey was trialed several times by the evaluation team to address any technical challenges before dissemination to the targeted participants.

Qualitative interviews

We conducted semistructured interviews with a purposive sample of FH administrators and frontline providers (Appendix B). The interview questions broadly mirrored the survey but allowed for more in-depth exploration of constructs. Interviewees were recruited through email invitations to selected senior and mid-level local and regional administrators, asking interviewees to refer our team to other contacts, and inviting survey respondents to voluntarily participate in a follow-up interview. One of the authors (EM), a Credentialed Evaluator, conducted all the one-time interviews either in-person at the individual participant’s workplace or by telephone. She did not have pre-existing relationships with any of the interviewees. Interviews were recorded and transcribed for analysis. Interviewees were required to consent to participate and understood that they could withdraw at any point. They were not offered incentives to participate. Interviews were carried out until thematic saturation was reached.

Analysis

A content analysis approach was employed for all qualitative data, which included open-ended responses from the online survey and interview transcripts. One of the authors (EM) conducted the analysis. The following steps were followed in the inductive content analysis process: repeated reading of the raw data, generation of initial thematic codes, organizing and sorting codes into categories (ie, main vs subcategories), coding of all data, quantifying codes, and interpreting themes. When responding to open-ended questions, respondents often provided multiple answers per question. Each of the respondents’ answers were coded. In alignment with the inductive nature of the analysis process, themes emerged organically from the data rather than the researchers using preconceived theories and categories to code the text. This was achieved by postponing the review of relevant literature on the topic until after the analysis was complete and using an external evaluation consultant (with no prior relationship to FH and limited theoretical knowledge of the topic matter) to analyze the data. Descriptive statistics were run on quantitative data in SPSS (v.24, IBM, Armonk, NY). For survey responses to be included in the analysis, the respondents needed to indicate which site they worked at and were required to answer at least 1 other survey question. One interviewee was excluded from the analysis since they were not familiar with the hospitalist model at their site.

Ethics approval

The evaluation protocol was reviewed by FH Department of Evaluation and Research and was deemed exempt from formal research ethics review.

A total of 377 individuals responded to the online survey between January 8 and February 28, 2018 (response rate 14%). The distribution of respondents generally reflected the size of the respective acute care facilities. Compared to the overall sampled population, fewer nurses participated in the survey (45% vs 64%) while the rate of participation for Unit Clerks (14% vs 16%) and allied professionals (12% vs 16%) were similar.

Out of the 45 people approached for an interview, a total of 38 were conducted from January 3 to March 5, 2018 (response rate 84%). The interviews lasted an average of 42 minutes. Interviewees represented a range of administrative and health professional roles (Figure 1). Some interviewees held multiple positions.

Satisfaction with HM service

Across all sites, survey respondents reported high levels of satisfaction with their respective HM services and identified positive impacts on their job satisfaction (Figure 2). Almost all interviewees similarly expressed high satisfaction levels with their HM services (95%; n = 36).

Perceptions of HM service performance

Survey respondents rated the strength of hospitalists’ interprofessional communication and collaboration with other physicians and with care teams. Roughly two-thirds reported that overall hospitalist communication was “good” or “very good.” We also asked participants to rate the frequency at which hospitalists met best practice expectations related to interprofessional teamwork. Across all sites, similar proportions of respondents (23% to 39%) reported that these best practices were met “most of the time” or “always” (Figure 3). Survey questions also assessed perceptions of respondents about the quality and safety of care provided by hospitalists (Figure 4).

Perceptions of the impact of the HM service postimplementation

The majority of survey respondents reported improvements in the quality of communication, professional relationships, and coordination of inpatient care at transition points after the implementation of the HM service (Figure 5). This was also reflected in interviews, where some indicated that it was easier to communicate with hospitalists due to their on-site presence, accessibility, and 24/7 availability (n = 21). They also described improved collaboration within the care teams (n = 7), and easier communication with hospitalists because they were approachable, willing, and receptive (n = 4).

We also asked the survey respondents to assess the impact of the new hospitalist model on different dimensions of care quality, including patient satisfaction, patient experience, efficiency, and overall quality of care (Figure 6). Findings were comparable across these dimensions, with roughly 50-60% of respondents noting positive changes compared to before the implementation of the programs. However, most interviewees identified both positive and negative effects in these areas. Positive impacts included hospitalist on-site presence leading to better accessibility and timeliness of care (n = 5), hospitalists providing continuity to patients/families by working for weeklong rotations (n = 6), hospitalists being particularly skilled at managing complex clinical presentations (n = 2), and hospitalists being able to spend more time with patients (n = 2). On the other hand, some interviewees noted that patients and families did not like seeing multiple doctors due to frequent handoffs between hospitalists (n = 12). They also raised concerns that hospitalists did not know patients’ histories or had relationships with them, potentially leading to longer length of stay and unnecessary investigations (n = 8).

Site-to-site ratings of satisfaction and performance

Survey respondents’ satisfaction and performance ratings varied substantially site-to-site. Across all areas assessed, ratings were consistently highest at Site B (the smallest institution in our evaluation and the most recent addition to the HM network in the health authority). These differences were statistically significant across all survey questions asked.

Discussion

Findings from this study provide insight into the experiences of frontline health care professionals and administrators with the implementation of new HM services across a range of small to large acute care facilities. They indicate that the majority of respondents reported high levels of satisfaction with their hospitalist services. Most also indicated that the service had resulted in improvements compared to prior inpatient care models.

Over half of the survey respondents, and the majority of interviewees, reported a positive impact on interprofessional communication and collaboration. This was largely attributed to enhanced accessibility and availability of hospitalists:

• "Being on-site lends itself to better communication because they’re accessible. Hospitalists always answer the phone, but the general practitioners (GP) don’t always since they may be with other patients." (Dietician, Site A)
• "A big strength is that we have physician presence on the unit all day during scheduled hours, which makes us more accessible to nurses and more able to follow up on patients that we have concerns about." (Physician Leader, Site B)

However, the ratings dropped substantially when they were asked to assess adherence to specific best practices of such communication and collaboration, such as participation in daily check-ins or attendance at team care rounds (Figure 3). Interdisciplinary clinical rounds have been identified as a tool to improve the effectiveness of care teams.¹² A number of elements have been identified as key components of effective rounds.¹³ Bedside rounds have also been found to enhance communication and teamwork.^14,15 In our study, the discrepancy between overall high levels of satisfaction with hospitalists’ communication/collaboration despite low scores on participation in more concrete activities may illustrate the importance of informal and ad hoc opportunities for interactions between hospitalists and other care providers that result from the enhanced presence of hospitalists on care units.⁸ Outside of formal rounds, hospitalists have the ability to interact with other care providers throughout their shifts. Prior studies have shown that hospitalists spend a significant portion of their time communicating with other care team members throughout their workdays.¹⁶ At the same time, the amount of time spent on communication should be balanced against the need for provision of direct care at the bedside. Future research should aim to identify the right balance between these competing priorities, and to understand the nature and quality of the communication between various care providers.

We also aimed to understand the perceptions of study participants about the impact of the HM service on quality of care. Survey participants not only expressed reasonable satisfaction with various aspects of hospitalists’ performance, but also described a positive impact on care quality after the implementation of their new services. This was also reflected in the interviews:

• "The clinical knowledge of the new hospitalists is far better. Some are internal medicine trained, so they bring better knowledge and skills. I feel comfortable that they can take patients and manage them. I wasn’t always comfortable with doing that in the past." (Emergency Physician, Site C)
• "Hospitalists are really familiar with acute care and how it works. They’ve become more familiar with the discharge planning system and thus know more about the resources available. And even something as simple as knowing which forms to use." (Dietician, Site A)

It must be noted that these observations should ideally be corroborated through a robust before-after analysis of various quality measures. While such an analysis was beyond the scope of our current project, we have previously demonstrated that across our network (including the 3 sites included in our evaluation) hospitalist care is associated with lower mortality and readmission rates.⁴ Our findings appear to confirm previous suggestions that hospitalists’ dedicated focus on inpatient care may allow them to develop enhanced skills in the management of common conditions in the acute care setting¹⁷ which can be perceived to be of value to other hospital-based care providers.

The issue of frequent handover among hospitalists was the most commonly identified challenge by both survey respondents and interviewees:

• "They’re very reluctant to discharge patients if it’s their first day with the patient. Even if the previous hospitalist said they were ready for discharge, the new doc wants to run all of their own tests before they feel comfortable. Maybe it’s a trust issue between hospitalists when they hand patients over. It’s also being personally liable for patients if you discharge them." (Patient Care Coordinator, Site A)
• "Communication is an issue. There’s lots of turnover in hospitalists. Relationships were closer with GPs because we had so much more interaction with particular individuals." (Hospitalist Physician Leader, Site A)

It must be noted that we conducted our evaluation in a relatively short time span (within 2 years) after the 3 services were implemented. Developing trust among a large number of hospitalists newly recruited to these programs can take time and may be a factor that can explain the reluctance of some to discharge patients after handoffs. However, concerns about discontinuity of care inherent in the hospitalist model are not new.^18,19 Better continuity has been associated with higher probability of patient discharges²⁰ and improved outcomes.²¹ To address this challenge, the hospitalist community has focused on defining the core competencies associated with high quality handovers,²² and deliberate efforts to improve the quality of handoffs through quality improvement methodologies.²³ Our study participants similarly identified these measures as potential solutions. Despite this, addressing hospitalist continuity of care remains a pressing challenge for the broader hospitalist community.²⁴

Our evaluation has a number of methodological limitations. First, the survey response rate was only 14%, which raises questions about nonresponse bias and the representativeness of the findings to the larger population of interest. While the distribution of respondents was largely similar to the overall sampled population, a number of factors may have impacted our response rate. For example, we were only able to distribute our survey to health care providers’ institutional email addresses. Moreover, while we provided incentives for participation and sent out a number of reminders, we solely relied on one communication modality (ie, electronic communication) and did not utilize other methods (such as posters, reminder at meetings, in-person invitations). Second, while the survey included a number of open-ended questions, many of these responses were at times brief and difficult to interpret and were not included in the analysis. Third, all data collected were self-reported. For example, we could not corroborate comments about participation in interdisciplinary rounds by objective measures such as attendance records or direct observation. Self-report data is subjective in nature and is vulnerable to a range of biases, such as social desirability bias.²⁵ Finally, patient satisfaction and experience with hospitalist care were not assessed by patients themselves. Ideally, standardized cross-site indicators should validate our patient-related results.

As mentioned above, hospitalist performance ratings varied substantially from site-to-site and were consistently higher at Site B (a small community hospital in a semi-rural area), followed by Site C (a medium-sized community hospital) and Site A (a tertiary referral center). The variability in program ratings and perceived hospitalist impacts between sites could be due to a variety of factors, such as the degree of change between the past and current models at each site, differences in hospitalist hiring processes, hospital size and culture, and differences in service design and operations. It may also be related to the timing of the introduction of the HM service, as Site B was the most recent site where the service was established. As such, there may be an element of recall bias behind the observed discrepancies. This highlights the importance of local context on respondent perceptions and suggests that our results may not be generalizable to other institutions with different attributes and characteristics.

Conclusion

Findings from this study have demonstrated that the recent hospitalist services in our health system have improved overall levels of interprofessional communication and teamwork, as well as perceptions of care quality among the majority of participants who reported high levels of satisfaction with their programs. Our findings further highlight the issue of frequent handovers among hospitalists as a pressing and ongoing challenge.

Corresponding Author: Vandad Yousefi, MD, CCFP, Past Regional Department Head – Hospital Medicine, Fraser Health Authority, Central City Tower, Suite 400, 13450 – 102nd Ave, Surrey, BC V3T 0H1; [email protected].

Financial disclosures: This project was funded by the Fraser Health Authority, which provided the funding for hiring of the external consultant to design, implement, and analyze the results of the evaluation program in collaboration with the Regional Hospitalist Program at Fraser Health.

From the Fraser Health Authority, Surrey, BC, Canada (Drs. Yousefi and Paletta), and Catalyst Consulting Inc., Vancouver, BC, Canada (Elayne McIvor).

Objective: Despite the ongoing growth in the number of hospitalist programs in Canada, their impact on the quality of interprofessional communication, teamwork, and staff satisfaction is not well known. This study aimed to evaluate perceptions of frontline care providers and hospital managers about the impact of the implementation of 3 new hospitalist services on care quality, teamwork, and interprofessional communication.

Design: We used an online survey and semistructured interviews to evaluate respondents’ views on quality of interprofessional communication and collaboration, impact of the new services on quality of care, and overall staff satisfaction with the new inpatient care model.

Setting: Integrated Regional Health Authority in British Columbia, Canada.

Participants: Participants included hospital administrators, frontline care providers (across a range of professions), and hospital and community-based physicians.

Results: The majority of respondents reported high levels of satisfaction with their new hospital medicine services. They identified improvements in interprofessional collaboration and communication between hospitalists and other professionals, which were attributed to enhanced onsite presence of physicians. They also perceived improvements in quality of care and efficiency. On the other hand, they identified a number of challenges with the change process, and raised concerns about the impact of patient handoffs on care quality and efficiency.

Conclusion: Across 3 very different acute care settings, the implementation of a hospitalist service was widely perceived to have resulted in improved teamwork, quality of care, and interprofessional communication.

Keywords: hospital medicine; hospitalist; teamwork; interprofessional collaboration.

Fraser Health Authority (FH) is an integrated regional health system with one of the largest regional Hospital Medicine (HM) networks in Canada.⁹ Over the past 2 decades, FH has implemented a number of HM services in its acute care facilities across a range of small and large community and academic hospitals. More recently, 3 hospitalist services were implemented over a 2-year period: new HM services in a tertiary referral center (Site A, July 2016) and a small community hospital (Site B, December 2016), and reintroduction of a hospitalist service in a medium-sized community hospital (Site C, January 2017). This provided a unique opportunity to assess the impact of the implementation of the hospitalist model across a range of facilities. The main objectives of this evaluation were to understand the level of physician, nursing, allied staff, and hospital administration satisfaction with the new hospitalist model, as well as the perceived impact of the service on efficiency and quality of care. As such, FH engaged an external consultant (EM) to conduct a comprehensive evaluation of the introduction of its latest HM services.

Methods

Setting

Hospital medicine services are currently available in 10 of 12 acute care facilities within the FH system. The 3 sites described in this evaluation constitute the most recent sites where a hospitalist service was implemented.

Site A is a 272-bed tertiary referral center situated in a rapidly growing community. At the time of our evaluation, 21 Full Time Equivalent (FTE) hospitalists cared for an average of 126 patients, which constituted the majority of adult medical patients. Each day, 8 individuals rounded on admitted patients (average individual census: 16) with another person providing in-house, evening, and overnight coverage. An additional flexible shift during the early afternoon helped with Emergency Department (ED) admissions.

Site B is small, 45-bed community hospital in a semi-rural community. The hospitalist service began in December 2016, with 4 FTE hospitalists caring for an average of 28 patients daily. This constituted 2 hospitalists rounding daily on admitted patients, with on-call coverage provided from home.

Site C is a 188-bed community hospital with a hospitalist service initially introduced in 2005. In 2016, the program was disbanded and the site moved back to a primarily community-based model, in which family physicians in the community were invited to assume the care of hospitalized patients. However, the hospitalist program had to be reintroduced in January 2017 due to poor uptake among PCPs in the community. At the time of evaluation, 19 FTE hospitalists (with 7 hospitalists working daily) provided most responsible physician care to a daily census of 116 patients (average individual census: 16). The program also covered ED admissions in-house until midnight, with overnight call provided from home.

Approach

We adopted a utilization-focused evaluation approach to guide our investigation. In this approach, the assessment is deliberately planned and conducted in a way that it maximizes the likelihood that findings would be used by the organization to inform learning, adaptations, and decision-making.¹¹ To enable this, the evaluator identified the primary intended recipients and engaged them at the start of the evaluation process to understand the main intended uses of the project. Moreover, the evaluator ensured that these intended uses of the evaluation guided all other decisions made throughout the process.

We collected data using an online survey of the staff at the 3 facilities, complemented by a series of semistructured qualitative interviews with FH administrators and frontline providers.

Online survey

We conducted an open online survey of a broad range of stakeholders who worked in the 3 facilities. To develop the questionnaire, we searched our department’s archives for previous surveys conducted from 2001 to 2005. We also interviewed the regional HM program management team to identify priority areas and reached out to the local leadership of the 3 acute care facilities for their input and support of the project. We refined the survey through several iterations, seeking input from experts in the FH Department of Evaluation and Research. The final questionnaire contained 10 items, including a mix of closed- and open-ended questions (Appendix A).

To reach the target audience, we collaborated with each hospital’s local leadership as well as the Divisions of Family Practice (DFP) that support local community PCPs in each hospital community.¹⁰ Existing email lists were compiled to create a master electronic survey distribution list. The initial invitation and 3 subsequent reminders were disseminated to the following target groups: hospital physicians (both hospitalists and nonhospitalists), PCPs, nursing and other allied professionals, administrators, and DFP leadership.

The survey consent form, background information, questions, and online platform (SimpleSurvey, Montreal, QC) were approved by FH’s Privacy Department. All respondents were required to provide their consent and able to withdraw at any time. Survey responses were kept anonymous and confidential, with results captured automatically into a spreadsheet by the survey platform. As an incentive for participation, respondents had the opportunity to win 1 of 3 $100 Visa gift cards. Personal contact information provided for the prize draw was collected in a separate survey that could not link back to respondents’ answers. The survey was trialed several times by the evaluation team to address any technical challenges before dissemination to the targeted participants.

Qualitative interviews

We conducted semistructured interviews with a purposive sample of FH administrators and frontline providers (Appendix B). The interview questions broadly mirrored the survey but allowed for more in-depth exploration of constructs. Interviewees were recruited through email invitations to selected senior and mid-level local and regional administrators, asking interviewees to refer our team to other contacts, and inviting survey respondents to voluntarily participate in a follow-up interview. One of the authors (EM), a Credentialed Evaluator, conducted all the one-time interviews either in-person at the individual participant’s workplace or by telephone. She did not have pre-existing relationships with any of the interviewees. Interviews were recorded and transcribed for analysis. Interviewees were required to consent to participate and understood that they could withdraw at any point. They were not offered incentives to participate. Interviews were carried out until thematic saturation was reached.

Analysis

A content analysis approach was employed for all qualitative data, which included open-ended responses from the online survey and interview transcripts. One of the authors (EM) conducted the analysis. The following steps were followed in the inductive content analysis process: repeated reading of the raw data, generation of initial thematic codes, organizing and sorting codes into categories (ie, main vs subcategories), coding of all data, quantifying codes, and interpreting themes. When responding to open-ended questions, respondents often provided multiple answers per question. Each of the respondents’ answers were coded. In alignment with the inductive nature of the analysis process, themes emerged organically from the data rather than the researchers using preconceived theories and categories to code the text. This was achieved by postponing the review of relevant literature on the topic until after the analysis was complete and using an external evaluation consultant (with no prior relationship to FH and limited theoretical knowledge of the topic matter) to analyze the data. Descriptive statistics were run on quantitative data in SPSS (v.24, IBM, Armonk, NY). For survey responses to be included in the analysis, the respondents needed to indicate which site they worked at and were required to answer at least 1 other survey question. One interviewee was excluded from the analysis since they were not familiar with the hospitalist model at their site.

Ethics approval

The evaluation protocol was reviewed by FH Department of Evaluation and Research and was deemed exempt from formal research ethics review.

A total of 377 individuals responded to the online survey between January 8 and February 28, 2018 (response rate 14%). The distribution of respondents generally reflected the size of the respective acute care facilities. Compared to the overall sampled population, fewer nurses participated in the survey (45% vs 64%) while the rate of participation for Unit Clerks (14% vs 16%) and allied professionals (12% vs 16%) were similar.

Out of the 45 people approached for an interview, a total of 38 were conducted from January 3 to March 5, 2018 (response rate 84%). The interviews lasted an average of 42 minutes. Interviewees represented a range of administrative and health professional roles (Figure 1). Some interviewees held multiple positions.

Satisfaction with HM service

Across all sites, survey respondents reported high levels of satisfaction with their respective HM services and identified positive impacts on their job satisfaction (Figure 2). Almost all interviewees similarly expressed high satisfaction levels with their HM services (95%; n = 36).

Perceptions of HM service performance

Survey respondents rated the strength of hospitalists’ interprofessional communication and collaboration with other physicians and with care teams. Roughly two-thirds reported that overall hospitalist communication was “good” or “very good.” We also asked participants to rate the frequency at which hospitalists met best practice expectations related to interprofessional teamwork. Across all sites, similar proportions of respondents (23% to 39%) reported that these best practices were met “most of the time” or “always” (Figure 3). Survey questions also assessed perceptions of respondents about the quality and safety of care provided by hospitalists (Figure 4).

Perceptions of the impact of the HM service postimplementation

The majority of survey respondents reported improvements in the quality of communication, professional relationships, and coordination of inpatient care at transition points after the implementation of the HM service (Figure 5). This was also reflected in interviews, where some indicated that it was easier to communicate with hospitalists due to their on-site presence, accessibility, and 24/7 availability (n = 21). They also described improved collaboration within the care teams (n = 7), and easier communication with hospitalists because they were approachable, willing, and receptive (n = 4).

We also asked the survey respondents to assess the impact of the new hospitalist model on different dimensions of care quality, including patient satisfaction, patient experience, efficiency, and overall quality of care (Figure 6). Findings were comparable across these dimensions, with roughly 50-60% of respondents noting positive changes compared to before the implementation of the programs. However, most interviewees identified both positive and negative effects in these areas. Positive impacts included hospitalist on-site presence leading to better accessibility and timeliness of care (n = 5), hospitalists providing continuity to patients/families by working for weeklong rotations (n = 6), hospitalists being particularly skilled at managing complex clinical presentations (n = 2), and hospitalists being able to spend more time with patients (n = 2). On the other hand, some interviewees noted that patients and families did not like seeing multiple doctors due to frequent handoffs between hospitalists (n = 12). They also raised concerns that hospitalists did not know patients’ histories or had relationships with them, potentially leading to longer length of stay and unnecessary investigations (n = 8).

Site-to-site ratings of satisfaction and performance

Survey respondents’ satisfaction and performance ratings varied substantially site-to-site. Across all areas assessed, ratings were consistently highest at Site B (the smallest institution in our evaluation and the most recent addition to the HM network in the health authority). These differences were statistically significant across all survey questions asked.

Discussion

Findings from this study provide insight into the experiences of frontline health care professionals and administrators with the implementation of new HM services across a range of small to large acute care facilities. They indicate that the majority of respondents reported high levels of satisfaction with their hospitalist services. Most also indicated that the service had resulted in improvements compared to prior inpatient care models.

Over half of the survey respondents, and the majority of interviewees, reported a positive impact on interprofessional communication and collaboration. This was largely attributed to enhanced accessibility and availability of hospitalists:

• "Being on-site lends itself to better communication because they’re accessible. Hospitalists always answer the phone, but the general practitioners (GP) don’t always since they may be with other patients." (Dietician, Site A)
• "A big strength is that we have physician presence on the unit all day during scheduled hours, which makes us more accessible to nurses and more able to follow up on patients that we have concerns about." (Physician Leader, Site B)

However, the ratings dropped substantially when they were asked to assess adherence to specific best practices of such communication and collaboration, such as participation in daily check-ins or attendance at team care rounds (Figure 3). Interdisciplinary clinical rounds have been identified as a tool to improve the effectiveness of care teams.¹² A number of elements have been identified as key components of effective rounds.¹³ Bedside rounds have also been found to enhance communication and teamwork.^14,15 In our study, the discrepancy between overall high levels of satisfaction with hospitalists’ communication/collaboration despite low scores on participation in more concrete activities may illustrate the importance of informal and ad hoc opportunities for interactions between hospitalists and other care providers that result from the enhanced presence of hospitalists on care units.⁸ Outside of formal rounds, hospitalists have the ability to interact with other care providers throughout their shifts. Prior studies have shown that hospitalists spend a significant portion of their time communicating with other care team members throughout their workdays.¹⁶ At the same time, the amount of time spent on communication should be balanced against the need for provision of direct care at the bedside. Future research should aim to identify the right balance between these competing priorities, and to understand the nature and quality of the communication between various care providers.

We also aimed to understand the perceptions of study participants about the impact of the HM service on quality of care. Survey participants not only expressed reasonable satisfaction with various aspects of hospitalists’ performance, but also described a positive impact on care quality after the implementation of their new services. This was also reflected in the interviews:

• "The clinical knowledge of the new hospitalists is far better. Some are internal medicine trained, so they bring better knowledge and skills. I feel comfortable that they can take patients and manage them. I wasn’t always comfortable with doing that in the past." (Emergency Physician, Site C)
• "Hospitalists are really familiar with acute care and how it works. They’ve become more familiar with the discharge planning system and thus know more about the resources available. And even something as simple as knowing which forms to use." (Dietician, Site A)

It must be noted that these observations should ideally be corroborated through a robust before-after analysis of various quality measures. While such an analysis was beyond the scope of our current project, we have previously demonstrated that across our network (including the 3 sites included in our evaluation) hospitalist care is associated with lower mortality and readmission rates.⁴ Our findings appear to confirm previous suggestions that hospitalists’ dedicated focus on inpatient care may allow them to develop enhanced skills in the management of common conditions in the acute care setting¹⁷ which can be perceived to be of value to other hospital-based care providers.

The issue of frequent handover among hospitalists was the most commonly identified challenge by both survey respondents and interviewees:

• "They’re very reluctant to discharge patients if it’s their first day with the patient. Even if the previous hospitalist said they were ready for discharge, the new doc wants to run all of their own tests before they feel comfortable. Maybe it’s a trust issue between hospitalists when they hand patients over. It’s also being personally liable for patients if you discharge them." (Patient Care Coordinator, Site A)
• "Communication is an issue. There’s lots of turnover in hospitalists. Relationships were closer with GPs because we had so much more interaction with particular individuals." (Hospitalist Physician Leader, Site A)

It must be noted that we conducted our evaluation in a relatively short time span (within 2 years) after the 3 services were implemented. Developing trust among a large number of hospitalists newly recruited to these programs can take time and may be a factor that can explain the reluctance of some to discharge patients after handoffs. However, concerns about discontinuity of care inherent in the hospitalist model are not new.^18,19 Better continuity has been associated with higher probability of patient discharges²⁰ and improved outcomes.²¹ To address this challenge, the hospitalist community has focused on defining the core competencies associated with high quality handovers,²² and deliberate efforts to improve the quality of handoffs through quality improvement methodologies.²³ Our study participants similarly identified these measures as potential solutions. Despite this, addressing hospitalist continuity of care remains a pressing challenge for the broader hospitalist community.²⁴

Our evaluation has a number of methodological limitations. First, the survey response rate was only 14%, which raises questions about nonresponse bias and the representativeness of the findings to the larger population of interest. While the distribution of respondents was largely similar to the overall sampled population, a number of factors may have impacted our response rate. For example, we were only able to distribute our survey to health care providers’ institutional email addresses. Moreover, while we provided incentives for participation and sent out a number of reminders, we solely relied on one communication modality (ie, electronic communication) and did not utilize other methods (such as posters, reminder at meetings, in-person invitations). Second, while the survey included a number of open-ended questions, many of these responses were at times brief and difficult to interpret and were not included in the analysis. Third, all data collected were self-reported. For example, we could not corroborate comments about participation in interdisciplinary rounds by objective measures such as attendance records or direct observation. Self-report data is subjective in nature and is vulnerable to a range of biases, such as social desirability bias.²⁵ Finally, patient satisfaction and experience with hospitalist care were not assessed by patients themselves. Ideally, standardized cross-site indicators should validate our patient-related results.

As mentioned above, hospitalist performance ratings varied substantially from site-to-site and were consistently higher at Site B (a small community hospital in a semi-rural area), followed by Site C (a medium-sized community hospital) and Site A (a tertiary referral center). The variability in program ratings and perceived hospitalist impacts between sites could be due to a variety of factors, such as the degree of change between the past and current models at each site, differences in hospitalist hiring processes, hospital size and culture, and differences in service design and operations. It may also be related to the timing of the introduction of the HM service, as Site B was the most recent site where the service was established. As such, there may be an element of recall bias behind the observed discrepancies. This highlights the importance of local context on respondent perceptions and suggests that our results may not be generalizable to other institutions with different attributes and characteristics.

Conclusion

Findings from this study have demonstrated that the recent hospitalist services in our health system have improved overall levels of interprofessional communication and teamwork, as well as perceptions of care quality among the majority of participants who reported high levels of satisfaction with their programs. Our findings further highlight the issue of frequent handovers among hospitalists as a pressing and ongoing challenge.

Corresponding Author: Vandad Yousefi, MD, CCFP, Past Regional Department Head – Hospital Medicine, Fraser Health Authority, Central City Tower, Suite 400, 13450 – 102nd Ave, Surrey, BC V3T 0H1; [email protected].

Financial disclosures: This project was funded by the Fraser Health Authority, which provided the funding for hiring of the external consultant to design, implement, and analyze the results of the evaluation program in collaboration with the Regional Hospitalist Program at Fraser Health.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.

From Stamford Hospital, Stamford, CT.

Objective: This single-center, quasi-experimental study of adult patients admitted or transferred to a medical step-down unit with alcohol withdrawal diagnoses sought to determine if symptom–triggered therapy (STT) is more effective than combined fixed-scheduled (FS) and STT in severe alcohol withdrawal.

Methods: In the preintervention group (72 episodes), patients were treated with FS and STT based on physician preference. In the postintervention group (69 episodes), providers were required to utilize only the STT protocol.

Results: Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001) and a decrease in average length of stay from 8.0 days to 5.1 days (P < .001). Secondary safety measures included a reduction in the proportion of patients who experienced delirium tremens from 47.5% to 22.5% (P < .001), and a reduction in intubation rates from 13.8% to 1.3% (P = .003).

Conclusion: The STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients requires frequent monitoring to assess withdrawal severity combined with appropriate and timely dosing of benzodiazepines.

Keywords: alcohol withdrawal delirium; alcohol withdrawal syndrome; treatment protocol; benzodiazepine; lorazepam.

Management of severe alcohol withdrawal and delirium tremens (DT) is challenging and requires significant resources, including close monitoring and intensive treatment, frequently in an intensive care unit (ICU).¹ Early diagnosis and therapeutic intervention are important to limit potential complications associated with DT.² Benzodiazepines are first-line therapeutic agents, but the definition of optimal use and dosing regimens has been limited, due to a lack of randomized controlled trials. In lower acuity patients admitted to a detoxification unit, systematic symptom–triggered benzodiazepine therapy (STT) has been established to be more effective than fixed-schedule (FS) dosing.^3-5 Patients treated using STT require lower total benzodiazepine dosing and achieve shorter treatment durations. However, in higher-acuity patients admitted to general medical services, analyses have not shown an advantage of STT over combined FS and STT.⁶

The purpose of this study was to determine whether implementation of STT is more effective than FS dosing combined with episodic STT in the management of hospitalized high-acuity alcohol withdrawal patients. We conducted a preintervention and postintervention quasi-experimental study in the step-down unit (SDU) of a 305-bed community teaching hospital. The study population consisted of adult inpatients 18 years or older admitted or transferred to the 12-bed SDU with alcohol withdrawal, as defined by primary or secondary International Classification of Diseases, Tenth Revision diagnoses. SDU admission criteria included patients with prior DT or those who had received multiple doses of benzodiazepines in the emergency department. In-hospital transfer to the SDU was at the physician’s discretion, if the patient required escalating doses of benzodiazepines or the use of increasing resources, such as those for behavioral emergencies. The majority of patients admitted or transferred to the SDU were assigned to medical house staff teams under hospitalist supervision, and, on occasion, under community physicians. The nurse-to-patient ratio in the SDU was 1:3.

Study groups

The preintervention group consisted of 80 successive treatment episodes involving patients admitted or transferred to the SDU from December 2, 2015, to July 1, 2017. Patients were treated based upon physician preference, consisting of a scheduled dosing regimen with additional doses as needed. The postintervention group included 80 successive treatment episodes involving patients admitted or transferred to the SDU from October 1, 2017, to March 23, 2019. The STT protocol was used in all patients in the postintervention group.

In the preintervention group, fixed, scheduled doses of lorazepam or chlordiazepoxide and as-needed lorazepam were prescribed and adjusted based upon physician judgment. Monitoring of symptom severity was scored using the revised Clinical Institute Withdrawal Assessment for Alcohol scale (CIWA-Ar). Benzodiazepine dosing occurred if the CIWA-Ar score had increased 2 or more points from the last score.

In the postintervention group, the STT protocol included the creation of a standardized physician order set for benzodiazepine “sliding scale” administration. The STT protocol allowed for escalating doses for higher withdrawal scores. Symptom severity was scored using MINDS (Minnesota Detoxification Scale) criteria.¹ Lorazepam as-needed dosing was based upon MINDS scores. A MINDS score less than 10 resulted in no medication, MINDS 10-12 required 2 mg, MINDS 13-16 required 4 mg, MINDS 17-19 required 6 mg, and MINDS 20 required 8 mg and a call to the physician. Transfer to the ICU was recommended if the MINDS score was ≥ 20 for 3 consecutive hours. Monitoring intervals occurred more frequently at 30 minutes unless the MINDS score was less than 10. After 7 days, the MINDS protocol was recommended to be discontinued, as the patient might have had iatrogenic delirium.

The STT protocol was introduced during a didactic session for the hospitalists and a separate session for internal medicine and family residents. Each registered nurse working in the SDU was trained in the use of the STT protocol and MINDS during nursing huddles.

Patients were excluded from evaluation if they were transferred to the SDU after 7 or more days in the hospital, if they had stayed in the hospital more than 30 days, were chronically on benzodiazepine therapy (to avoid confounding withdrawal symptoms), or if they left the hospital against medical advice (AMA). To avoid bias in the results, the patients with early discontinuation of treatment were included in analyses of secondary outcomes, thus resulting in all 80 episodes analyzed.

Measures and data

The primary outcome measure was benzodiazepine dose intensity, expressed in total lorazepam-equivalents. Secondary measures included average length of stay (including general medical, surgical, and ICU days), seizure incidence, DT incidence, sitter use, behavioral emergency responses, rates of leaving AMA, intubation, transfer to the ICU, and death.

Benzodiazepine dosing and length of stay were obtained from the data warehouse of the hospital’s electronic health record (EHR; Meditech). Benzodiazepine dosing was expressed in total lorazepam-equivalents, with conversion as follows: lorazepam orally and intravenously 1 mg = chlordiazepoxide 25 mg = diazepam 5 mg. All other measures were obtained from chart review of the patients’ EMR entries. The Stamford Hospital Institutional Review Board approved this study.

Analysis

Data analyses for this study were performed using SPSS version 25.0 (IBM). Categorical data were reported as frequency (count) and percent within category. Continuous data were reported as mean (SD). Categorical data were analyzed using χ² analysis; continuous data were analyzed using t-tests. A P value of .05 was considered significant for each analysis.

Results

During the preintervention period, 72 episodes (58 patients) met inclusion criteria, and 69 episodes (55 patients) met inclusion criteria during the postintervention period. Ten patients were represented in both groups. Eight preintervention episodes were excluded from the primary analysis because the patient left AMA. Eleven postintervention episodes were excluded: 9 due to patients leaving AMA, 1 due to chronic benzodiazepine usage, and 1 due to transfer to the SDU unit after 7 days. Baseline characteristics and medication use profiles of the preintervention and postintervention groups are summarized in Table 1.

Implementation of the intervention was associated with a significant reduction in average (per patient) cumulative benzodiazepine dose, from 250 mg to 96 mg (P < .001), as shown in Table 2. Average length of stay decreased from 8.0 days to 5.1 days (P < .001). Secondary safety measures were notable for a reduction in DT incidence, from 47.5% to 22.5% (P < .001), and lower rates of intubation, from 13.8% to 1.3% (P = .003). Seven-day readmission rates were 0% preintervention and 1.4% postintervention.

Discussion

We found that hospitalized patients with severe alcohol withdrawal treated with STT required fewer benzodiazepines and had a lower length of stay than patients treated with a conventional combined STT and FS regimen. Implementation of the change from the STT and FS approach to the STT approach in the SDU resulted in concerns that waiting for symptoms to appear could result in more severe withdrawal and prolonged treatment.³ To address this, the intervention included monitoring and dosing every 30 minutes, as compared to monitoring and dosing every 1 hour preintervention. In addition, a sliding-scale approach to match alcohol withdrawal score with dosage was employed in postintervention patients.

Employment of the STT protocol also resulted in decreased complications, including lower rates of DT and transfer to the ICU. This new intervention resulted in significantly decreased time required to control severe symptoms. In the preintervention phase, if a patient’s symptoms escalated despite administration of the as-needed dose of benzodiazepine, there was often a delay in administration of additional doses due to the time needed for nurses to reach a physician and subsequent placement of a new order. In the postintervention phase, the STT protocol allowed nursing staff to give benzodiazepines without delay when needed. We believe this reduced the number of calls by nursing staff to physicians requesting additional medications, and that this improved teamwork when managing these patients.

As part of the intervention, a decision was made to use the MINDS scale rather than the CIWA-Ar scale to assess withdrawal severity. This was because the CIWA-Ar has only been validated in patients with uncomplicated alcohol withdrawal syndrome and has not been researched extensively in patients requiring ICU-level care.¹ MINDS assessment has proven to be reliable and reflects severity of withdrawal. Furthermore, MINDS requires less time to administer—3 to 5 minutes vs 5 to 15 minutes for the CIWA-Ar scale. CIWA-Ar, unlike MINDS, requires subjective input from the patient, which is less reliable for higher acuity patients. Our study is unique in that it focused on high-acuity patients and it showed both a significant reduction in quantity of benzodiazepines prescribed and length of stay. Previous studies on lower acuity patients in detoxification units have confirmed that STT is more effective than a FS approach.^3-5 In patients of higher acuity, STT has not proven to be superior.

A key lesson learned was the need for proper education of nursing staff. Concurrent nursing audits were necessary to ensure that scoring was performed in an accurate and timely manner. In addition, it was challenging to predict which patients might develop DTs versus those requiring a brief inpatient stay. While there was initial concern that an STT protocol could result in underdosing, we found that patients had fewer DT episodes and fewer ICU transfers.

This study had several limitations. These include a relatively small sample size and the data being less recent. As there has been no intervening change to the therapeutic paradigm of DT treatment, the findings remain pertinent to the present time. The study employed a simple pre/post design and was conducted in a single setting. We are not aware of any temporal or local trends likely to influence these results. Admissions and transfers to the SDU for severe alcohol withdrawal were based on physician discretion. However, patient characteristics in both groups were similar (Table 1). We note that the postintervention STT protocol allowed for more frequent benzodiazepine dosing, though benzodiazepine use did decrease. Different alcohol withdrawal scores (MINDS vs. CIWA-Ar) were used for postintervention and preintervention, although previous research has shown that MINDS and CIWA-Ar scores correlate well.⁷ Finally, some patients of higher acuity and complexity were excluded, potentially limiting the generalizability of our results.

Conclusion

Our STT protocol proved to be more effective and safer in treating severe alcohol withdrawal patients than usual care employing STT with FS. We believe the successful implementation of a STT protocol in high-acuity patients also requires frequent monitoring using the MINDS scale, integrated with benzodiazepine sliding-scale dosing to match symptom severity. This bundled approach resulted in a significant reduction of benzodiazepine usage and reduced length of stay. Timely treatment of these patients also reduced the percent of patients developing DTs, and reduced intubation rates and transfers to the ICU. Further studies may be warranted at other sites to confirm the effectiveness of this STT protocol.

Corresponding author: Paul W. Huang, MD, Stamford Hospital, One Hospital Plaza, PO Box 9317, Stamford, CT 06904; [email protected].

Financial disclosures: None.

From Western Sussex Hospitals NHS Foundation Trust, Physiotherapy Department, Chichester, UK (Richard J. Holmes), and Western Sussex Hospitals NHS Foundation Trust, Department of Occupational Therapy, Chichester, UK (Sophie Stratford).

Objective: Despite the benefits of early and frequent input from a neurologist, there is wide variation in the availability of this service, especially in district general hospitals, with many patients managed on clinically inappropriate wards. The purpose of this service evaluation was to explore the impact this had on patient care.

Methods: A retrospective service evaluation was undertaken at a National Health Service hospital by reviewing patient records over a 6-month period. Data related to demographics, processes within the patient’s care, and secondary complications were recorded. Findings were compared with those of stroke patients managed on a specialist stroke ward.

Results: A total of 63 patients were identified, with a mean age of 72 years. The mean length of stay was 25.9 days, with a readmission rate of 16.7%. Only 15.9% of patients were reviewed by a neurologist. There was a high rate of secondary complications, with a number of patients experiencing falls (11.1%), pressure ulcers (14.3%), and health care–acquired infections (33.3%) during their admission.

Conclusions: The lack of specialist input from a neurologist and the management of patients on clinically inappropriate wards may have negatively impacted length of stay, readmission rates, and the frequency of secondary complications.

Keywords: evaluation; clinical safety; neurology; patient-centered care; clinical outcomes; length of stay.

It is estimated that 10% of acute admissions to district general hospitals (DGHs) of the National Health Service (NHS) in the United Kingdom are due to a neurological problem other than stroke.¹ In 2011, a joint report from the Royal College of Physicians and the Association of British Neurologists (ABN) recommended that all of these patients should be admitted under the care of a neurologist and be regularly reviewed by a neurologist during their admission.² The rationale for this recommendation is clear. The involvement of a neurologist has been shown to improve accuracy of the diagnosis³ and significantly reduce length of stay.^4,5 Studies have also shown that the involvement of a neurologist has led to a change in the management plan in as high as 79%⁶ to 89%³ of cases, suggesting that a high proportion of neurological patients not seen by a neurologist are being managed suboptimally.

Despite this, a recent ABN survey of acute neurology services found ongoing wide variations in the availability of this specialist care, with a large proportion of DGHs having limited or no access to a neurologist and very few having dedicated neurology beds.⁷ While it is recognized that services have been structured in response to the reduced numbers of neurologists within the United Kingdom,⁸ it is prudent to assess the impact that such services have on patient care.

With this in mind, we planned to evaluate the current provision of care provided to neurological patients in a real-world setting. This was conducted in the context of a neurology liaison service at a DGH with no dedicated neurology beds.

Methods

A retrospective service evaluation was undertaken at a DGH in the southeast of England. The NHS hospital has neurologists on site who provide diagnostic and therapeutic consultations on the wards, but there are no dedicated beds for patients with neurological conditions. Patients requiring neurosurgical input are referred to a tertiary neurosciences center.

Patients were selected from the neurotherapy database if they were referred into the service between August 1, 2019, and January 31, 2020. The neurotherapy database was used as this was the only source that held thorough data on this patient group and allowed for the identification of patients who were not referred into the neurologist’s service. Patients were included if they had a new neurological condition as their primary diagnosis or if they had an exacerbation of an already established neurological condition. If a patient was admitted with more than 1 neurological diagnosis then the primary diagnosis for the admission was to be used in the analysis, though this did not occur during this evaluation. Patients with a primary diagnosis of a stroke were included if they were not managed on the acute stroke ward. Those managed on the stroke ward were excluded so that an analysis of patients managed on wards that were deemed clinically inappropriate could be undertaken. Patients were not included if they had a pre-existing neurological condition (ie, dementia, multiple sclerosis) but were admitted due to a non-neurological cause such as a fall or infection. All patients who met the criteria were included.

A team member independently reviewed each set of patient notes. Demographic data extracted from the medical notes included the patient’s age (on admission), gender, and diagnosis. Medical, nursing, and therapy notes were reviewed to identify secondary complications that arose during the patient’s admission. The secondary complications reviewed were falls (defined as the patient unexpectedly coming to the ground or other lower level), health care–acquired infections (HAIs) (defined as any infection acquired during the hospital admission), and pressure ulcers (defined as injuries to the skin or underlying tissue during the hospital admission). Other details, obtained from the patient administration system, included the length of stay (days), the number of ward moves the patient experienced, the speciality of the consultant responsible for the patient’s care, the discharge destination, and whether the patient was readmitted for any cause within 30 days. All data collected were stored on a password-protected computer and no patient-identifiable data were included.

The results were collated using descriptive statistics. The χ² test was used to compare categorical data between those patients who were and were not reviewed by a neurologist, and the Mann-Whitney U test was used to compare differences in the length of stay between these 2 groups.

No national data relating to this specific patient group were available within the literature. Therefore, to provide a comparator of neurological patients within the same hospital, data were collected on stroke patients managed on the stroke ward. This group was deemed most appropriate for comparison as they present with similar neurological symptoms but are cared for on a specialist ward. During the evaluation period, 284 stroke patients were admitted to the stroke ward. A sample of 75 patients was randomly selected using a random number generator, and the procedure for data collection was repeated. It was not appropriate to make direct comparative analysis on these 2 groups due to the inherent differences, but it was felt important to provide context with regards to what usual care was like on a specialist ward within the same hospital.

Ethical approval was not required as this was a service evaluation of routinely collected data within a single hospital site.

Results

In total, 63 patients were identified: 26 females and 37 males. The median age of patients was 74 years (range, 39-92 years). These demographic details and comparisons to stroke patients managed on a specialist ward can be seen in Table 1. To quantify the range of diagnoses, the condition groups defined by GIRFT Neurology Methodology⁹ were used. The most common diagnoses were tumors of the nervous system (25.4%) and traumatic brain and spine injury (23.8%). The other conditions included in the analysis can be seen in Table 2.

Despite having a neurological condition as their primary diagnosis, only 15.9% of patients were reviewed by a neurologist during their hospital admission. Patients were most commonly under the care of a geriatrician (60.3%), but they were also managed by orthopedics (12.6%), acute medicine (7.9%), respiratory (6.3%), cardiology (4.8%), gastroenterology (3.2%), and surgery (3.2%). One patient (1.6%) was managed by intensivists.

The average length of stay was 25.9 days (range, 2-78 days). This was more than double the average length of stay on the stroke ward (11.4 days) (Table 1) and the national average for patients with neurological conditions (9.78 days).¹⁰ During their stay, 33% had 2 or more ward moves, with 1 patient moving wards a total of 6 times. Just over half (52.4%) of the patients returned to their usual residence on discharge. The remainder were discharged to rehabilitation units (15.9%), nursing homes (14.3%), residential homes (6.3%), tertiary centers (4.8%), and hospice (1.6%). Unfortunately, 3 patients (4.8%) passed away. Of those still alive (n = 60), 16.7% were readmitted to the hospital within 30 days, compared to a readmission rate of 11% on the stroke ward. None of the patients who were readmitted were seen by a neurologist during their initial admission.

The frequency of secondary complications was reviewed as a measure of the multidisciplinary management of this patient group. It was noted that 11.1% had a fall on the ward, which was similar to a rate of 10.7% on the stroke ward. More striking was the fact that 14.3% of patients developed a pressure ulcer and 33.3% developed an HAI during their admission, compared with rates of 1.3% and 10.7%, respectively, on the stroke ward (Table 1).

There were no significant differences found in length of stay between those who were and were not reviewed by a neurologist (P = .73). This was also true for categorical data, whereby readmission rate (P = .13), frequency of falls (P = .22), frequency of pressure ulcers (P = .67), and HAIs (P = .81) all failed to show a significant difference between groups.

Discussion

The findings of this service evaluation show markedly poorer outcomes for neurological patients compared to stroke patients managed on a specialist stroke ward. It is suggested that these results are in part due to the lack of specialist input from a neurologist in the majority of cases and the fact that all were managed on clinically inappropriate wards. Only 15.9% of neurological patients were seen by a neurologist. This is a slight improvement compared to previous studies in DGHs that showed rates of 10%¹ and 11%,¹¹ but it is still a far cry from the goal of 100% set out in recommendations.² In addition, the increased readmission rate may be suggestive of suboptimal management, especially given that none of those readmitted had been reviewed by a neurologist. There are undoubtedly other factors that may influence readmissions, such as comorbidities, the severity/complexity of the condition, and the strength of community services. However, the impact of a lack of input from a specialist should not be underestimated, and further evaluation of this factor (with confounding factors controlled) would be beneficial.

The result of an extended length of stay was also a predictable outcome based on previous evidence.^4,5 With the potential for suboptimal management plans and inaccurate diagnoses, it is inevitable that the patient’s movement through the hospital system will be impeded. In our example, it is possible that the extended length of stay was influenced by the fact that patients included in the evaluation were managed on nonspecialist wards and a large proportion had multiple ward changes.

Given that the evidence clearly shows that stroke patients are most effectively managed by a multidisciplinary team (MDT) with specialist skills,¹² it is likely that other neurological patients, who have similar multifactorial needs, would also benefit. The patients in our evaluation were cared for by nursing staff who lacked specific skills and experience in neurology. The allied health professionals involved were specialists in neurotherapy but were not based on the ward and not directly linked to the ward MDT. A review by Epstein found that the benefits of having a MDT, in any speciality, working together on a ward included improved communication, reduced adverse events, and a reduced length of stay.¹³ This lack of an effective MDT approach may provide some explanation as to why the average length of stay and the rates of some secondary complications were at such elevated levels.

A systematic review exploring the impact of patients admitted to clinically inappropriate wards in a range of specialities found that these patients were associated with worse outcomes.¹⁴ This is supported by our findings, in which a higher rate of pressure ulcers and HAIs were observed when compared to rates in the specialist stroke ward. Again, a potential explanation for this is the impact of patients being managed by clinicians who lack the specialist knowledge of the patient group and the risks they face. Another explanation could be due to the high number of ward moves the patients experienced. Blay et al found that ward moves increased length of stay and carried an associated clinical risk, with the odds of falls and HAIs increasing with each move.¹⁵ A case example of this is apparent within our analysis in that the patient who experienced 6 ward moves not only had the longest length of stay (78 days), but also developed a pressure ulcer and 2 HAIs during their admission.

This service evaluation had a number of limitations that should be considered when interpreting the results. First, despite including all patients who met the criteria within the stipulated time frame, the sample size was relatively small, making it difficult to identify consistent patterns of behavior within the data.

Furthermore, caution should be applied when interpreting the comparators used, as the patient groups are not equivalent. The use of comparison against a standard is not a prerequisite in a service evaluation of this nature, but comparators were included to help frame the context for the reader. As such, they should only be used in this way rather than to make any firm conclusions.

Finally, as the evaluation was limited to the use of routinely collected data, there are several variables, other than those reported, which may have influenced the results. For example, it was not possible to ascertain certain demographic details, such as body mass index and socioeconomic factors, nor lifestyle factors such as smoking status, alcohol consumption, and exercise levels, all of which could impact negatively on the outcomes of interest. Furthermore, data were not collected on follow-up services after discharge to evaluate whether these had any impact on readmission rates.

Conclusion

This service evaluation highlights the potential impact of managing neurological patients on clinically inappropriate wards with limited input from a neurologist. There is the potential to ameliorate these impacts by cohorting these patients in neurologist-led beds with a specialist MDT. While there are limitations in the design of our study, including the lack of a controlled comparison, the small sample size, and the fact that this is an evaluation of a single service, the negative impacts to patients are concerning and warrant further investigation.

Corresponding author: Richard J. Holmes, MSc, Physiotherapy Department, St. Richard’s Hospital, Chichester, West Sussex, PO19 6SE; [email protected].

Financial disclosures: None.

From Western Sussex Hospitals NHS Foundation Trust, Physiotherapy Department, Chichester, UK (Richard J. Holmes), and Western Sussex Hospitals NHS Foundation Trust, Department of Occupational Therapy, Chichester, UK (Sophie Stratford).

Objective: Despite the benefits of early and frequent input from a neurologist, there is wide variation in the availability of this service, especially in district general hospitals, with many patients managed on clinically inappropriate wards. The purpose of this service evaluation was to explore the impact this had on patient care.

Methods: A retrospective service evaluation was undertaken at a National Health Service hospital by reviewing patient records over a 6-month period. Data related to demographics, processes within the patient’s care, and secondary complications were recorded. Findings were compared with those of stroke patients managed on a specialist stroke ward.

Results: A total of 63 patients were identified, with a mean age of 72 years. The mean length of stay was 25.9 days, with a readmission rate of 16.7%. Only 15.9% of patients were reviewed by a neurologist. There was a high rate of secondary complications, with a number of patients experiencing falls (11.1%), pressure ulcers (14.3%), and health care–acquired infections (33.3%) during their admission.

Conclusions: The lack of specialist input from a neurologist and the management of patients on clinically inappropriate wards may have negatively impacted length of stay, readmission rates, and the frequency of secondary complications.

Keywords: evaluation; clinical safety; neurology; patient-centered care; clinical outcomes; length of stay.

It is estimated that 10% of acute admissions to district general hospitals (DGHs) of the National Health Service (NHS) in the United Kingdom are due to a neurological problem other than stroke.¹ In 2011, a joint report from the Royal College of Physicians and the Association of British Neurologists (ABN) recommended that all of these patients should be admitted under the care of a neurologist and be regularly reviewed by a neurologist during their admission.² The rationale for this recommendation is clear. The involvement of a neurologist has been shown to improve accuracy of the diagnosis³ and significantly reduce length of stay.^4,5 Studies have also shown that the involvement of a neurologist has led to a change in the management plan in as high as 79%⁶ to 89%³ of cases, suggesting that a high proportion of neurological patients not seen by a neurologist are being managed suboptimally.

Despite this, a recent ABN survey of acute neurology services found ongoing wide variations in the availability of this specialist care, with a large proportion of DGHs having limited or no access to a neurologist and very few having dedicated neurology beds.⁷ While it is recognized that services have been structured in response to the reduced numbers of neurologists within the United Kingdom,⁸ it is prudent to assess the impact that such services have on patient care.

With this in mind, we planned to evaluate the current provision of care provided to neurological patients in a real-world setting. This was conducted in the context of a neurology liaison service at a DGH with no dedicated neurology beds.

Methods

A retrospective service evaluation was undertaken at a DGH in the southeast of England. The NHS hospital has neurologists on site who provide diagnostic and therapeutic consultations on the wards, but there are no dedicated beds for patients with neurological conditions. Patients requiring neurosurgical input are referred to a tertiary neurosciences center.

Patients were selected from the neurotherapy database if they were referred into the service between August 1, 2019, and January 31, 2020. The neurotherapy database was used as this was the only source that held thorough data on this patient group and allowed for the identification of patients who were not referred into the neurologist’s service. Patients were included if they had a new neurological condition as their primary diagnosis or if they had an exacerbation of an already established neurological condition. If a patient was admitted with more than 1 neurological diagnosis then the primary diagnosis for the admission was to be used in the analysis, though this did not occur during this evaluation. Patients with a primary diagnosis of a stroke were included if they were not managed on the acute stroke ward. Those managed on the stroke ward were excluded so that an analysis of patients managed on wards that were deemed clinically inappropriate could be undertaken. Patients were not included if they had a pre-existing neurological condition (ie, dementia, multiple sclerosis) but were admitted due to a non-neurological cause such as a fall or infection. All patients who met the criteria were included.

A team member independently reviewed each set of patient notes. Demographic data extracted from the medical notes included the patient’s age (on admission), gender, and diagnosis. Medical, nursing, and therapy notes were reviewed to identify secondary complications that arose during the patient’s admission. The secondary complications reviewed were falls (defined as the patient unexpectedly coming to the ground or other lower level), health care–acquired infections (HAIs) (defined as any infection acquired during the hospital admission), and pressure ulcers (defined as injuries to the skin or underlying tissue during the hospital admission). Other details, obtained from the patient administration system, included the length of stay (days), the number of ward moves the patient experienced, the speciality of the consultant responsible for the patient’s care, the discharge destination, and whether the patient was readmitted for any cause within 30 days. All data collected were stored on a password-protected computer and no patient-identifiable data were included.

The results were collated using descriptive statistics. The χ² test was used to compare categorical data between those patients who were and were not reviewed by a neurologist, and the Mann-Whitney U test was used to compare differences in the length of stay between these 2 groups.

No national data relating to this specific patient group were available within the literature. Therefore, to provide a comparator of neurological patients within the same hospital, data were collected on stroke patients managed on the stroke ward. This group was deemed most appropriate for comparison as they present with similar neurological symptoms but are cared for on a specialist ward. During the evaluation period, 284 stroke patients were admitted to the stroke ward. A sample of 75 patients was randomly selected using a random number generator, and the procedure for data collection was repeated. It was not appropriate to make direct comparative analysis on these 2 groups due to the inherent differences, but it was felt important to provide context with regards to what usual care was like on a specialist ward within the same hospital.

Ethical approval was not required as this was a service evaluation of routinely collected data within a single hospital site.

Results

In total, 63 patients were identified: 26 females and 37 males. The median age of patients was 74 years (range, 39-92 years). These demographic details and comparisons to stroke patients managed on a specialist ward can be seen in Table 1. To quantify the range of diagnoses, the condition groups defined by GIRFT Neurology Methodology⁹ were used. The most common diagnoses were tumors of the nervous system (25.4%) and traumatic brain and spine injury (23.8%). The other conditions included in the analysis can be seen in Table 2.

Despite having a neurological condition as their primary diagnosis, only 15.9% of patients were reviewed by a neurologist during their hospital admission. Patients were most commonly under the care of a geriatrician (60.3%), but they were also managed by orthopedics (12.6%), acute medicine (7.9%), respiratory (6.3%), cardiology (4.8%), gastroenterology (3.2%), and surgery (3.2%). One patient (1.6%) was managed by intensivists.

The average length of stay was 25.9 days (range, 2-78 days). This was more than double the average length of stay on the stroke ward (11.4 days) (Table 1) and the national average for patients with neurological conditions (9.78 days).¹⁰ During their stay, 33% had 2 or more ward moves, with 1 patient moving wards a total of 6 times. Just over half (52.4%) of the patients returned to their usual residence on discharge. The remainder were discharged to rehabilitation units (15.9%), nursing homes (14.3%), residential homes (6.3%), tertiary centers (4.8%), and hospice (1.6%). Unfortunately, 3 patients (4.8%) passed away. Of those still alive (n = 60), 16.7% were readmitted to the hospital within 30 days, compared to a readmission rate of 11% on the stroke ward. None of the patients who were readmitted were seen by a neurologist during their initial admission.

The frequency of secondary complications was reviewed as a measure of the multidisciplinary management of this patient group. It was noted that 11.1% had a fall on the ward, which was similar to a rate of 10.7% on the stroke ward. More striking was the fact that 14.3% of patients developed a pressure ulcer and 33.3% developed an HAI during their admission, compared with rates of 1.3% and 10.7%, respectively, on the stroke ward (Table 1).

There were no significant differences found in length of stay between those who were and were not reviewed by a neurologist (P = .73). This was also true for categorical data, whereby readmission rate (P = .13), frequency of falls (P = .22), frequency of pressure ulcers (P = .67), and HAIs (P = .81) all failed to show a significant difference between groups.

Discussion

The findings of this service evaluation show markedly poorer outcomes for neurological patients compared to stroke patients managed on a specialist stroke ward. It is suggested that these results are in part due to the lack of specialist input from a neurologist in the majority of cases and the fact that all were managed on clinically inappropriate wards. Only 15.9% of neurological patients were seen by a neurologist. This is a slight improvement compared to previous studies in DGHs that showed rates of 10%¹ and 11%,¹¹ but it is still a far cry from the goal of 100% set out in recommendations.² In addition, the increased readmission rate may be suggestive of suboptimal management, especially given that none of those readmitted had been reviewed by a neurologist. There are undoubtedly other factors that may influence readmissions, such as comorbidities, the severity/complexity of the condition, and the strength of community services. However, the impact of a lack of input from a specialist should not be underestimated, and further evaluation of this factor (with confounding factors controlled) would be beneficial.

The result of an extended length of stay was also a predictable outcome based on previous evidence.^4,5 With the potential for suboptimal management plans and inaccurate diagnoses, it is inevitable that the patient’s movement through the hospital system will be impeded. In our example, it is possible that the extended length of stay was influenced by the fact that patients included in the evaluation were managed on nonspecialist wards and a large proportion had multiple ward changes.

Given that the evidence clearly shows that stroke patients are most effectively managed by a multidisciplinary team (MDT) with specialist skills,¹² it is likely that other neurological patients, who have similar multifactorial needs, would also benefit. The patients in our evaluation were cared for by nursing staff who lacked specific skills and experience in neurology. The allied health professionals involved were specialists in neurotherapy but were not based on the ward and not directly linked to the ward MDT. A review by Epstein found that the benefits of having a MDT, in any speciality, working together on a ward included improved communication, reduced adverse events, and a reduced length of stay.¹³ This lack of an effective MDT approach may provide some explanation as to why the average length of stay and the rates of some secondary complications were at such elevated levels.

A systematic review exploring the impact of patients admitted to clinically inappropriate wards in a range of specialities found that these patients were associated with worse outcomes.¹⁴ This is supported by our findings, in which a higher rate of pressure ulcers and HAIs were observed when compared to rates in the specialist stroke ward. Again, a potential explanation for this is the impact of patients being managed by clinicians who lack the specialist knowledge of the patient group and the risks they face. Another explanation could be due to the high number of ward moves the patients experienced. Blay et al found that ward moves increased length of stay and carried an associated clinical risk, with the odds of falls and HAIs increasing with each move.¹⁵ A case example of this is apparent within our analysis in that the patient who experienced 6 ward moves not only had the longest length of stay (78 days), but also developed a pressure ulcer and 2 HAIs during their admission.

This service evaluation had a number of limitations that should be considered when interpreting the results. First, despite including all patients who met the criteria within the stipulated time frame, the sample size was relatively small, making it difficult to identify consistent patterns of behavior within the data.

Furthermore, caution should be applied when interpreting the comparators used, as the patient groups are not equivalent. The use of comparison against a standard is not a prerequisite in a service evaluation of this nature, but comparators were included to help frame the context for the reader. As such, they should only be used in this way rather than to make any firm conclusions.

Finally, as the evaluation was limited to the use of routinely collected data, there are several variables, other than those reported, which may have influenced the results. For example, it was not possible to ascertain certain demographic details, such as body mass index and socioeconomic factors, nor lifestyle factors such as smoking status, alcohol consumption, and exercise levels, all of which could impact negatively on the outcomes of interest. Furthermore, data were not collected on follow-up services after discharge to evaluate whether these had any impact on readmission rates.

Conclusion

This service evaluation highlights the potential impact of managing neurological patients on clinically inappropriate wards with limited input from a neurologist. There is the potential to ameliorate these impacts by cohorting these patients in neurologist-led beds with a specialist MDT. While there are limitations in the design of our study, including the lack of a controlled comparison, the small sample size, and the fact that this is an evaluation of a single service, the negative impacts to patients are concerning and warrant further investigation.

Corresponding author: Richard J. Holmes, MSc, Physiotherapy Department, St. Richard’s Hospital, Chichester, West Sussex, PO19 6SE; [email protected].

Financial disclosures: None.

From Western Sussex Hospitals NHS Foundation Trust, Physiotherapy Department, Chichester, UK (Richard J. Holmes), and Western Sussex Hospitals NHS Foundation Trust, Department of Occupational Therapy, Chichester, UK (Sophie Stratford).

Objective: Despite the benefits of early and frequent input from a neurologist, there is wide variation in the availability of this service, especially in district general hospitals, with many patients managed on clinically inappropriate wards. The purpose of this service evaluation was to explore the impact this had on patient care.

Methods: A retrospective service evaluation was undertaken at a National Health Service hospital by reviewing patient records over a 6-month period. Data related to demographics, processes within the patient’s care, and secondary complications were recorded. Findings were compared with those of stroke patients managed on a specialist stroke ward.

Results: A total of 63 patients were identified, with a mean age of 72 years. The mean length of stay was 25.9 days, with a readmission rate of 16.7%. Only 15.9% of patients were reviewed by a neurologist. There was a high rate of secondary complications, with a number of patients experiencing falls (11.1%), pressure ulcers (14.3%), and health care–acquired infections (33.3%) during their admission.

Conclusions: The lack of specialist input from a neurologist and the management of patients on clinically inappropriate wards may have negatively impacted length of stay, readmission rates, and the frequency of secondary complications.

Keywords: evaluation; clinical safety; neurology; patient-centered care; clinical outcomes; length of stay.

It is estimated that 10% of acute admissions to district general hospitals (DGHs) of the National Health Service (NHS) in the United Kingdom are due to a neurological problem other than stroke.¹ In 2011, a joint report from the Royal College of Physicians and the Association of British Neurologists (ABN) recommended that all of these patients should be admitted under the care of a neurologist and be regularly reviewed by a neurologist during their admission.² The rationale for this recommendation is clear. The involvement of a neurologist has been shown to improve accuracy of the diagnosis³ and significantly reduce length of stay.^4,5 Studies have also shown that the involvement of a neurologist has led to a change in the management plan in as high as 79%⁶ to 89%³ of cases, suggesting that a high proportion of neurological patients not seen by a neurologist are being managed suboptimally.

Despite this, a recent ABN survey of acute neurology services found ongoing wide variations in the availability of this specialist care, with a large proportion of DGHs having limited or no access to a neurologist and very few having dedicated neurology beds.⁷ While it is recognized that services have been structured in response to the reduced numbers of neurologists within the United Kingdom,⁸ it is prudent to assess the impact that such services have on patient care.

With this in mind, we planned to evaluate the current provision of care provided to neurological patients in a real-world setting. This was conducted in the context of a neurology liaison service at a DGH with no dedicated neurology beds.

Methods

A retrospective service evaluation was undertaken at a DGH in the southeast of England. The NHS hospital has neurologists on site who provide diagnostic and therapeutic consultations on the wards, but there are no dedicated beds for patients with neurological conditions. Patients requiring neurosurgical input are referred to a tertiary neurosciences center.

Patients were selected from the neurotherapy database if they were referred into the service between August 1, 2019, and January 31, 2020. The neurotherapy database was used as this was the only source that held thorough data on this patient group and allowed for the identification of patients who were not referred into the neurologist’s service. Patients were included if they had a new neurological condition as their primary diagnosis or if they had an exacerbation of an already established neurological condition. If a patient was admitted with more than 1 neurological diagnosis then the primary diagnosis for the admission was to be used in the analysis, though this did not occur during this evaluation. Patients with a primary diagnosis of a stroke were included if they were not managed on the acute stroke ward. Those managed on the stroke ward were excluded so that an analysis of patients managed on wards that were deemed clinically inappropriate could be undertaken. Patients were not included if they had a pre-existing neurological condition (ie, dementia, multiple sclerosis) but were admitted due to a non-neurological cause such as a fall or infection. All patients who met the criteria were included.

A team member independently reviewed each set of patient notes. Demographic data extracted from the medical notes included the patient’s age (on admission), gender, and diagnosis. Medical, nursing, and therapy notes were reviewed to identify secondary complications that arose during the patient’s admission. The secondary complications reviewed were falls (defined as the patient unexpectedly coming to the ground or other lower level), health care–acquired infections (HAIs) (defined as any infection acquired during the hospital admission), and pressure ulcers (defined as injuries to the skin or underlying tissue during the hospital admission). Other details, obtained from the patient administration system, included the length of stay (days), the number of ward moves the patient experienced, the speciality of the consultant responsible for the patient’s care, the discharge destination, and whether the patient was readmitted for any cause within 30 days. All data collected were stored on a password-protected computer and no patient-identifiable data were included.

The results were collated using descriptive statistics. The χ² test was used to compare categorical data between those patients who were and were not reviewed by a neurologist, and the Mann-Whitney U test was used to compare differences in the length of stay between these 2 groups.

No national data relating to this specific patient group were available within the literature. Therefore, to provide a comparator of neurological patients within the same hospital, data were collected on stroke patients managed on the stroke ward. This group was deemed most appropriate for comparison as they present with similar neurological symptoms but are cared for on a specialist ward. During the evaluation period, 284 stroke patients were admitted to the stroke ward. A sample of 75 patients was randomly selected using a random number generator, and the procedure for data collection was repeated. It was not appropriate to make direct comparative analysis on these 2 groups due to the inherent differences, but it was felt important to provide context with regards to what usual care was like on a specialist ward within the same hospital.

Ethical approval was not required as this was a service evaluation of routinely collected data within a single hospital site.

Results

In total, 63 patients were identified: 26 females and 37 males. The median age of patients was 74 years (range, 39-92 years). These demographic details and comparisons to stroke patients managed on a specialist ward can be seen in Table 1. To quantify the range of diagnoses, the condition groups defined by GIRFT Neurology Methodology⁹ were used. The most common diagnoses were tumors of the nervous system (25.4%) and traumatic brain and spine injury (23.8%). The other conditions included in the analysis can be seen in Table 2.

Despite having a neurological condition as their primary diagnosis, only 15.9% of patients were reviewed by a neurologist during their hospital admission. Patients were most commonly under the care of a geriatrician (60.3%), but they were also managed by orthopedics (12.6%), acute medicine (7.9%), respiratory (6.3%), cardiology (4.8%), gastroenterology (3.2%), and surgery (3.2%). One patient (1.6%) was managed by intensivists.

The average length of stay was 25.9 days (range, 2-78 days). This was more than double the average length of stay on the stroke ward (11.4 days) (Table 1) and the national average for patients with neurological conditions (9.78 days).¹⁰ During their stay, 33% had 2 or more ward moves, with 1 patient moving wards a total of 6 times. Just over half (52.4%) of the patients returned to their usual residence on discharge. The remainder were discharged to rehabilitation units (15.9%), nursing homes (14.3%), residential homes (6.3%), tertiary centers (4.8%), and hospice (1.6%). Unfortunately, 3 patients (4.8%) passed away. Of those still alive (n = 60), 16.7% were readmitted to the hospital within 30 days, compared to a readmission rate of 11% on the stroke ward. None of the patients who were readmitted were seen by a neurologist during their initial admission.

The frequency of secondary complications was reviewed as a measure of the multidisciplinary management of this patient group. It was noted that 11.1% had a fall on the ward, which was similar to a rate of 10.7% on the stroke ward. More striking was the fact that 14.3% of patients developed a pressure ulcer and 33.3% developed an HAI during their admission, compared with rates of 1.3% and 10.7%, respectively, on the stroke ward (Table 1).

There were no significant differences found in length of stay between those who were and were not reviewed by a neurologist (P = .73). This was also true for categorical data, whereby readmission rate (P = .13), frequency of falls (P = .22), frequency of pressure ulcers (P = .67), and HAIs (P = .81) all failed to show a significant difference between groups.

Discussion

The findings of this service evaluation show markedly poorer outcomes for neurological patients compared to stroke patients managed on a specialist stroke ward. It is suggested that these results are in part due to the lack of specialist input from a neurologist in the majority of cases and the fact that all were managed on clinically inappropriate wards. Only 15.9% of neurological patients were seen by a neurologist. This is a slight improvement compared to previous studies in DGHs that showed rates of 10%¹ and 11%,¹¹ but it is still a far cry from the goal of 100% set out in recommendations.² In addition, the increased readmission rate may be suggestive of suboptimal management, especially given that none of those readmitted had been reviewed by a neurologist. There are undoubtedly other factors that may influence readmissions, such as comorbidities, the severity/complexity of the condition, and the strength of community services. However, the impact of a lack of input from a specialist should not be underestimated, and further evaluation of this factor (with confounding factors controlled) would be beneficial.

The result of an extended length of stay was also a predictable outcome based on previous evidence.^4,5 With the potential for suboptimal management plans and inaccurate diagnoses, it is inevitable that the patient’s movement through the hospital system will be impeded. In our example, it is possible that the extended length of stay was influenced by the fact that patients included in the evaluation were managed on nonspecialist wards and a large proportion had multiple ward changes.

Given that the evidence clearly shows that stroke patients are most effectively managed by a multidisciplinary team (MDT) with specialist skills,¹² it is likely that other neurological patients, who have similar multifactorial needs, would also benefit. The patients in our evaluation were cared for by nursing staff who lacked specific skills and experience in neurology. The allied health professionals involved were specialists in neurotherapy but were not based on the ward and not directly linked to the ward MDT. A review by Epstein found that the benefits of having a MDT, in any speciality, working together on a ward included improved communication, reduced adverse events, and a reduced length of stay.¹³ This lack of an effective MDT approach may provide some explanation as to why the average length of stay and the rates of some secondary complications were at such elevated levels.

A systematic review exploring the impact of patients admitted to clinically inappropriate wards in a range of specialities found that these patients were associated with worse outcomes.¹⁴ This is supported by our findings, in which a higher rate of pressure ulcers and HAIs were observed when compared to rates in the specialist stroke ward. Again, a potential explanation for this is the impact of patients being managed by clinicians who lack the specialist knowledge of the patient group and the risks they face. Another explanation could be due to the high number of ward moves the patients experienced. Blay et al found that ward moves increased length of stay and carried an associated clinical risk, with the odds of falls and HAIs increasing with each move.¹⁵ A case example of this is apparent within our analysis in that the patient who experienced 6 ward moves not only had the longest length of stay (78 days), but also developed a pressure ulcer and 2 HAIs during their admission.

This service evaluation had a number of limitations that should be considered when interpreting the results. First, despite including all patients who met the criteria within the stipulated time frame, the sample size was relatively small, making it difficult to identify consistent patterns of behavior within the data.

Furthermore, caution should be applied when interpreting the comparators used, as the patient groups are not equivalent. The use of comparison against a standard is not a prerequisite in a service evaluation of this nature, but comparators were included to help frame the context for the reader. As such, they should only be used in this way rather than to make any firm conclusions.

Finally, as the evaluation was limited to the use of routinely collected data, there are several variables, other than those reported, which may have influenced the results. For example, it was not possible to ascertain certain demographic details, such as body mass index and socioeconomic factors, nor lifestyle factors such as smoking status, alcohol consumption, and exercise levels, all of which could impact negatively on the outcomes of interest. Furthermore, data were not collected on follow-up services after discharge to evaluate whether these had any impact on readmission rates.

Conclusion

This service evaluation highlights the potential impact of managing neurological patients on clinically inappropriate wards with limited input from a neurologist. There is the potential to ameliorate these impacts by cohorting these patients in neurologist-led beds with a specialist MDT. While there are limitations in the design of our study, including the lack of a controlled comparison, the small sample size, and the fact that this is an evaluation of a single service, the negative impacts to patients are concerning and warrant further investigation.

Corresponding author: Richard J. Holmes, MSc, Physiotherapy Department, St. Richard’s Hospital, Chichester, West Sussex, PO19 6SE; [email protected].

Financial disclosures: None.

A group of bipartisan lawmakers intends to compel insurers to streamline prior authorization processes for Medicare Advantage plans, including a bid to end the use of faxes and develop systems that can allow for real-time decisions.

Rep. Suzan DelBene (D-Wash.); Rep. Mike Kelly (R-Pa.); Rep. Ami Bera, MD (D-Calif.); and Rep. Larry Bucshon, MD, (R-Ind.) on May 13 introduced a bill that would task federal officials with refining standards regarding prior authorization for Medicare Advantage. Titled the Improving Seniors’ Timely Access to Care Act of 2021, the bill would direct the Department of Health & Human Services to create rules intended to make prior authorization more transparent and speedy for the insurer-run Medicare plans. Known as Medicare Advantage, these plans cover about 24.1 million people of the 62 million enrolled in the giant federal health program, according to the nonprofit Kaiser Family Foundation.

These revamped prior authorization systems could not rely on faxes nor could they employ proprietary payer portals that did not meet HHS’ standards, says the text of the bill released by Rep. DelBene. Insurers would also have to report to the Centers for Medicare & Medicaid Services about the extent of their use of prior authorization and the rate of approvals or denials. The bill seeks to encourage plans to adopt prior authorization programs that adhere to evidence-based medical guidelines in consultation with physicians.

There were several reasons for focusing on Medicare Advantage plans, although prior authorization concerns extend more broadly in the U.S. health care system, said Susan Bailey, MD, president of the American Medical Association.

There’s an ample body of research about issues seen in the Medicare Advantage plans. Dr. Bailey also said that, in her experience, Medicare Advantage plans have had some of the most restrictive policies. And, by starting with Medicare Advantage, there’s a potential for a ripple effect in the industry, easing this issue when physicians work with other insurers as well.

“When Medicare adopts a policy whether it be a payment policy or a coverage policy, private insurers typically follow along,” she said.
 

Strong support among health care groups

There’s strong support for streamlining prior authorization both in the medical community and in Congress.

The bill has the support of about 70 health care organizations, including the AMA and the American Academy of Family Physicians, according to its sponsors. As of May 17, the bill had attracted the backing of 97 members of the House of Representatives, roughly evenly split among Democrats and Republicans.

Rep. DelBene’s previous version of this bill, the Improving Seniors’ Timely Access to Care Act of 2019, attracted 143 Democratic cosponsors and 137 Republican ones, or more than half of the members of the House. This bill was not completed during the previous session of Congress (January 2019–January 2021) because of the more urgent needs of pandemic response, said Rep. Bucshon, who practiced cardiothoracic surgery before joining Congress.

“It wasn’t quite on the radar as much as it might have been if we didn’t have COVID,” Rep. Bucshon said.

Rep. Bucshon added that he expects strong Senate support for a companion measure of the House bill, which could make the difference for efforts to pass it this year.

Insurers have become more aggressive over time in denying payments through prior authorization systems for services that physicians say their patients need, according to Rep. Bucshon. There may be some “bad actors” in medicine who would order unnecessary procedures, Rep. Bucshon allowed, but in most cases, the cumbersome prior authorization processes only put a hurdle for patients seeking needed treatments, he said.

“The premise is that it controls health care costs but actually what it does is it helps insurance company’s bottom line,” Rep. Bucshon said.

In a prepared statement, former Pennsylvania representative Allyson Y. Schwartz, now CEO of the Better Medicare Alliance, said her group had spoken with sponsors of this legislation and appreciates “their receptiveness to feedback in this process.”

“Prior authorization ensures beneficiaries receive clinically appropriate care and reduces exposures to duplicative and unnecessary services,” Ms. Schwartz said. “We share an interest in ensuring prior authorization works as smoothly and effectively as possible for beneficiaries while protecting its essential function of facilitating safe, evidenced-based care.”

The Better Medicare Alliance said its funders include UnitedHealth, Humana, and CVS Health/Aetna, which run Advantage plans. The group also lists as its partners many medical organizations.
 

“Rationing care by hassling”

Like Rep. Bucshon, Dr. Bailey sees a different motivation in insurers’ persistence in keeping the prior authorization process cumbersome.

Phone calls and faxes remain the key methods for handling prior authorization for medical services, according to the results of a survey done by the AMA in December. Phone calls were always or often required for prior authorization for medical services (59%), with faxes the second-most common approach (46%), followed by health plans’ online portals (39%), electronic health records and practice management systems (29%), and email or U.S. mail (26%), according to the AMA’s report on the survey.

“It seems like every step in the process is designed to make the patient less likely to get the therapy that the doctor thinks that the patient needs,” Dr. Bailey said. “It’s almost like rationing care by hassling the patient and the physician.”

The findings of an investigation by HHS’ internal watchdog unit appear to support Dr. Bailey’s view, showing that insurer-run Medicare plans had a pattern of often walking back their initial rejections.

In 2018, the Office of the Inspector General for HHS reported that Medicare Advantage organizations (MAOs) overturned 75% of their own denials during 2014-16. In addition, independent reviewers within the appeals process overturned additional denials in favor of patients and clinicians, OIG said.

“The high number of overturned denials raises concerns that some Medicare Advantage beneficiaries and providers were initially denied services and payments that should have been provided,” the OIG said in the report. “This is especially concerning because beneficiaries and providers rarely used the appeals process, which is designed to ensure access to care and payment.”

During 2014-2016, patients and clinicians appealed only 1% of denials to the first level of appeal, OIG said. In the report, the watchdog group noted that CMS audits had highlighted “widespread and persistent MAO performance problems related to denials of care and payment.” In 2015, for example, CMS cited 56% of audited contracts for making inappropriate denials.

Dr. Bailey also said in an interview that she routinely encounters problems with prior authorization in her own practice as an allergist and immunologist in Fort Worth, Tex.

In late May, for example, a Medicare Advantage plan made a patient whose chronic asthma had been stable for years change to a new inhaler that resulted in him developing a yeast infection in his mouth, Dr. Bailey said.

“We treated the yeast infection, made some changes in the way he uses his inhaler, so hopefully he would tolerate it better,” Dr. Bailey said. “He had a reaction to the medication to treat the yeast infection and ended up in the hospital. How is that helping anyone? It certainly hasn’t helped my patient.”

Dr. Bailey said insurers have also asked to seek prior authorization to prescribe medications that have been generic for years and have used the process to challenge her on cases of what seem to be common sense in medical practice. This included a bid to have Dr. Bailey prescribe a medication in pill form for a 6-month-old baby who had no teeth.

“Every doctor has got absurd stories like that, but unfortunately, every doctor is going to have tragic stories where prior authorization has resulted in death and harm to the patients,” Dr. Bailey said.

Some physicians leave it to the patient to try to overcome insurers’ decisions on prior authorization, seeing this task as falling outside of their duties, Dr. Bailey said.

“I don’t do that. I fight. I spend a lot of time fighting. I don’t like to lose. I don’t like my patients to lose, so I will go to the mat for them,” Dr. Bailey said. “But I’m blessed to be in a specialty where I’ve got loads more control over my schedule than many other specialties do.”

A version of this article first appeared on Medscape.com.

A group of bipartisan lawmakers intends to compel insurers to streamline prior authorization processes for Medicare Advantage plans, including a bid to end the use of faxes and develop systems that can allow for real-time decisions.

Rep. Suzan DelBene (D-Wash.); Rep. Mike Kelly (R-Pa.); Rep. Ami Bera, MD (D-Calif.); and Rep. Larry Bucshon, MD, (R-Ind.) on May 13 introduced a bill that would task federal officials with refining standards regarding prior authorization for Medicare Advantage. Titled the Improving Seniors’ Timely Access to Care Act of 2021, the bill would direct the Department of Health & Human Services to create rules intended to make prior authorization more transparent and speedy for the insurer-run Medicare plans. Known as Medicare Advantage, these plans cover about 24.1 million people of the 62 million enrolled in the giant federal health program, according to the nonprofit Kaiser Family Foundation.

These revamped prior authorization systems could not rely on faxes nor could they employ proprietary payer portals that did not meet HHS’ standards, says the text of the bill released by Rep. DelBene. Insurers would also have to report to the Centers for Medicare & Medicaid Services about the extent of their use of prior authorization and the rate of approvals or denials. The bill seeks to encourage plans to adopt prior authorization programs that adhere to evidence-based medical guidelines in consultation with physicians.

There were several reasons for focusing on Medicare Advantage plans, although prior authorization concerns extend more broadly in the U.S. health care system, said Susan Bailey, MD, president of the American Medical Association.

There’s an ample body of research about issues seen in the Medicare Advantage plans. Dr. Bailey also said that, in her experience, Medicare Advantage plans have had some of the most restrictive policies. And, by starting with Medicare Advantage, there’s a potential for a ripple effect in the industry, easing this issue when physicians work with other insurers as well.

“When Medicare adopts a policy whether it be a payment policy or a coverage policy, private insurers typically follow along,” she said.
 

Strong support among health care groups

There’s strong support for streamlining prior authorization both in the medical community and in Congress.

The bill has the support of about 70 health care organizations, including the AMA and the American Academy of Family Physicians, according to its sponsors. As of May 17, the bill had attracted the backing of 97 members of the House of Representatives, roughly evenly split among Democrats and Republicans.

Rep. DelBene’s previous version of this bill, the Improving Seniors’ Timely Access to Care Act of 2019, attracted 143 Democratic cosponsors and 137 Republican ones, or more than half of the members of the House. This bill was not completed during the previous session of Congress (January 2019–January 2021) because of the more urgent needs of pandemic response, said Rep. Bucshon, who practiced cardiothoracic surgery before joining Congress.

“It wasn’t quite on the radar as much as it might have been if we didn’t have COVID,” Rep. Bucshon said.

Rep. Bucshon added that he expects strong Senate support for a companion measure of the House bill, which could make the difference for efforts to pass it this year.

Insurers have become more aggressive over time in denying payments through prior authorization systems for services that physicians say their patients need, according to Rep. Bucshon. There may be some “bad actors” in medicine who would order unnecessary procedures, Rep. Bucshon allowed, but in most cases, the cumbersome prior authorization processes only put a hurdle for patients seeking needed treatments, he said.

“The premise is that it controls health care costs but actually what it does is it helps insurance company’s bottom line,” Rep. Bucshon said.

In a prepared statement, former Pennsylvania representative Allyson Y. Schwartz, now CEO of the Better Medicare Alliance, said her group had spoken with sponsors of this legislation and appreciates “their receptiveness to feedback in this process.”

“Prior authorization ensures beneficiaries receive clinically appropriate care and reduces exposures to duplicative and unnecessary services,” Ms. Schwartz said. “We share an interest in ensuring prior authorization works as smoothly and effectively as possible for beneficiaries while protecting its essential function of facilitating safe, evidenced-based care.”

The Better Medicare Alliance said its funders include UnitedHealth, Humana, and CVS Health/Aetna, which run Advantage plans. The group also lists as its partners many medical organizations.
 

“Rationing care by hassling”

Like Rep. Bucshon, Dr. Bailey sees a different motivation in insurers’ persistence in keeping the prior authorization process cumbersome.

Phone calls and faxes remain the key methods for handling prior authorization for medical services, according to the results of a survey done by the AMA in December. Phone calls were always or often required for prior authorization for medical services (59%), with faxes the second-most common approach (46%), followed by health plans’ online portals (39%), electronic health records and practice management systems (29%), and email or U.S. mail (26%), according to the AMA’s report on the survey.

“It seems like every step in the process is designed to make the patient less likely to get the therapy that the doctor thinks that the patient needs,” Dr. Bailey said. “It’s almost like rationing care by hassling the patient and the physician.”

The findings of an investigation by HHS’ internal watchdog unit appear to support Dr. Bailey’s view, showing that insurer-run Medicare plans had a pattern of often walking back their initial rejections.

In 2018, the Office of the Inspector General for HHS reported that Medicare Advantage organizations (MAOs) overturned 75% of their own denials during 2014-16. In addition, independent reviewers within the appeals process overturned additional denials in favor of patients and clinicians, OIG said.

“The high number of overturned denials raises concerns that some Medicare Advantage beneficiaries and providers were initially denied services and payments that should have been provided,” the OIG said in the report. “This is especially concerning because beneficiaries and providers rarely used the appeals process, which is designed to ensure access to care and payment.”

During 2014-2016, patients and clinicians appealed only 1% of denials to the first level of appeal, OIG said. In the report, the watchdog group noted that CMS audits had highlighted “widespread and persistent MAO performance problems related to denials of care and payment.” In 2015, for example, CMS cited 56% of audited contracts for making inappropriate denials.

Dr. Bailey also said in an interview that she routinely encounters problems with prior authorization in her own practice as an allergist and immunologist in Fort Worth, Tex.

In late May, for example, a Medicare Advantage plan made a patient whose chronic asthma had been stable for years change to a new inhaler that resulted in him developing a yeast infection in his mouth, Dr. Bailey said.

“We treated the yeast infection, made some changes in the way he uses his inhaler, so hopefully he would tolerate it better,” Dr. Bailey said. “He had a reaction to the medication to treat the yeast infection and ended up in the hospital. How is that helping anyone? It certainly hasn’t helped my patient.”

Dr. Bailey said insurers have also asked to seek prior authorization to prescribe medications that have been generic for years and have used the process to challenge her on cases of what seem to be common sense in medical practice. This included a bid to have Dr. Bailey prescribe a medication in pill form for a 6-month-old baby who had no teeth.

“Every doctor has got absurd stories like that, but unfortunately, every doctor is going to have tragic stories where prior authorization has resulted in death and harm to the patients,” Dr. Bailey said.

Some physicians leave it to the patient to try to overcome insurers’ decisions on prior authorization, seeing this task as falling outside of their duties, Dr. Bailey said.

“I don’t do that. I fight. I spend a lot of time fighting. I don’t like to lose. I don’t like my patients to lose, so I will go to the mat for them,” Dr. Bailey said. “But I’m blessed to be in a specialty where I’ve got loads more control over my schedule than many other specialties do.”

A version of this article first appeared on Medscape.com.

A group of bipartisan lawmakers intends to compel insurers to streamline prior authorization processes for Medicare Advantage plans, including a bid to end the use of faxes and develop systems that can allow for real-time decisions.

Rep. Suzan DelBene (D-Wash.); Rep. Mike Kelly (R-Pa.); Rep. Ami Bera, MD (D-Calif.); and Rep. Larry Bucshon, MD, (R-Ind.) on May 13 introduced a bill that would task federal officials with refining standards regarding prior authorization for Medicare Advantage. Titled the Improving Seniors’ Timely Access to Care Act of 2021, the bill would direct the Department of Health & Human Services to create rules intended to make prior authorization more transparent and speedy for the insurer-run Medicare plans. Known as Medicare Advantage, these plans cover about 24.1 million people of the 62 million enrolled in the giant federal health program, according to the nonprofit Kaiser Family Foundation.

These revamped prior authorization systems could not rely on faxes nor could they employ proprietary payer portals that did not meet HHS’ standards, says the text of the bill released by Rep. DelBene. Insurers would also have to report to the Centers for Medicare & Medicaid Services about the extent of their use of prior authorization and the rate of approvals or denials. The bill seeks to encourage plans to adopt prior authorization programs that adhere to evidence-based medical guidelines in consultation with physicians.

There were several reasons for focusing on Medicare Advantage plans, although prior authorization concerns extend more broadly in the U.S. health care system, said Susan Bailey, MD, president of the American Medical Association.

There’s an ample body of research about issues seen in the Medicare Advantage plans. Dr. Bailey also said that, in her experience, Medicare Advantage plans have had some of the most restrictive policies. And, by starting with Medicare Advantage, there’s a potential for a ripple effect in the industry, easing this issue when physicians work with other insurers as well.

“When Medicare adopts a policy whether it be a payment policy or a coverage policy, private insurers typically follow along,” she said.
 

Strong support among health care groups

There’s strong support for streamlining prior authorization both in the medical community and in Congress.

The bill has the support of about 70 health care organizations, including the AMA and the American Academy of Family Physicians, according to its sponsors. As of May 17, the bill had attracted the backing of 97 members of the House of Representatives, roughly evenly split among Democrats and Republicans.

Rep. DelBene’s previous version of this bill, the Improving Seniors’ Timely Access to Care Act of 2019, attracted 143 Democratic cosponsors and 137 Republican ones, or more than half of the members of the House. This bill was not completed during the previous session of Congress (January 2019–January 2021) because of the more urgent needs of pandemic response, said Rep. Bucshon, who practiced cardiothoracic surgery before joining Congress.

“It wasn’t quite on the radar as much as it might have been if we didn’t have COVID,” Rep. Bucshon said.

Rep. Bucshon added that he expects strong Senate support for a companion measure of the House bill, which could make the difference for efforts to pass it this year.

Insurers have become more aggressive over time in denying payments through prior authorization systems for services that physicians say their patients need, according to Rep. Bucshon. There may be some “bad actors” in medicine who would order unnecessary procedures, Rep. Bucshon allowed, but in most cases, the cumbersome prior authorization processes only put a hurdle for patients seeking needed treatments, he said.

“The premise is that it controls health care costs but actually what it does is it helps insurance company’s bottom line,” Rep. Bucshon said.

In a prepared statement, former Pennsylvania representative Allyson Y. Schwartz, now CEO of the Better Medicare Alliance, said her group had spoken with sponsors of this legislation and appreciates “their receptiveness to feedback in this process.”

“Prior authorization ensures beneficiaries receive clinically appropriate care and reduces exposures to duplicative and unnecessary services,” Ms. Schwartz said. “We share an interest in ensuring prior authorization works as smoothly and effectively as possible for beneficiaries while protecting its essential function of facilitating safe, evidenced-based care.”

The Better Medicare Alliance said its funders include UnitedHealth, Humana, and CVS Health/Aetna, which run Advantage plans. The group also lists as its partners many medical organizations.
 

“Rationing care by hassling”

Like Rep. Bucshon, Dr. Bailey sees a different motivation in insurers’ persistence in keeping the prior authorization process cumbersome.

Phone calls and faxes remain the key methods for handling prior authorization for medical services, according to the results of a survey done by the AMA in December. Phone calls were always or often required for prior authorization for medical services (59%), with faxes the second-most common approach (46%), followed by health plans’ online portals (39%), electronic health records and practice management systems (29%), and email or U.S. mail (26%), according to the AMA’s report on the survey.

“It seems like every step in the process is designed to make the patient less likely to get the therapy that the doctor thinks that the patient needs,” Dr. Bailey said. “It’s almost like rationing care by hassling the patient and the physician.”

The findings of an investigation by HHS’ internal watchdog unit appear to support Dr. Bailey’s view, showing that insurer-run Medicare plans had a pattern of often walking back their initial rejections.

In 2018, the Office of the Inspector General for HHS reported that Medicare Advantage organizations (MAOs) overturned 75% of their own denials during 2014-16. In addition, independent reviewers within the appeals process overturned additional denials in favor of patients and clinicians, OIG said.

“The high number of overturned denials raises concerns that some Medicare Advantage beneficiaries and providers were initially denied services and payments that should have been provided,” the OIG said in the report. “This is especially concerning because beneficiaries and providers rarely used the appeals process, which is designed to ensure access to care and payment.”

During 2014-2016, patients and clinicians appealed only 1% of denials to the first level of appeal, OIG said. In the report, the watchdog group noted that CMS audits had highlighted “widespread and persistent MAO performance problems related to denials of care and payment.” In 2015, for example, CMS cited 56% of audited contracts for making inappropriate denials.

Dr. Bailey also said in an interview that she routinely encounters problems with prior authorization in her own practice as an allergist and immunologist in Fort Worth, Tex.

In late May, for example, a Medicare Advantage plan made a patient whose chronic asthma had been stable for years change to a new inhaler that resulted in him developing a yeast infection in his mouth, Dr. Bailey said.

“We treated the yeast infection, made some changes in the way he uses his inhaler, so hopefully he would tolerate it better,” Dr. Bailey said. “He had a reaction to the medication to treat the yeast infection and ended up in the hospital. How is that helping anyone? It certainly hasn’t helped my patient.”

Dr. Bailey said insurers have also asked to seek prior authorization to prescribe medications that have been generic for years and have used the process to challenge her on cases of what seem to be common sense in medical practice. This included a bid to have Dr. Bailey prescribe a medication in pill form for a 6-month-old baby who had no teeth.

“Every doctor has got absurd stories like that, but unfortunately, every doctor is going to have tragic stories where prior authorization has resulted in death and harm to the patients,” Dr. Bailey said.

Some physicians leave it to the patient to try to overcome insurers’ decisions on prior authorization, seeing this task as falling outside of their duties, Dr. Bailey said.

“I don’t do that. I fight. I spend a lot of time fighting. I don’t like to lose. I don’t like my patients to lose, so I will go to the mat for them,” Dr. Bailey said. “But I’m blessed to be in a specialty where I’ve got loads more control over my schedule than many other specialties do.”

A version of this article first appeared on Medscape.com.

Despite the shutdowns and plummeting patient volumes early in the COVID-19 pandemic, gastroenterologists’ earnings were just 3.1% lower in 2020 than in 2019, according to new survey results from Medscape.

That drop, from $419,000 to $406,000, was larger, however, than the average for all specialists, which slipped just 0.6% in 2020.

“Most gastroenterologists who saw a drop in income cited COVID-19–related issues, such as job loss, fewer hours, and fewer patients,” Keith L. Martin wrote in the 2021 Medscape Gastroenterologist Compensation Report.

Specialties with larger declines than gastroenterology included dermatology (–4%), pediatrics (–5%), and otolaryngology (–9%). Conversely, plastic surgeons saw the largest increases last year, with their average compensation rising 10% over 2019. Oncologists (+7%) and cardiologists (+5%) also did well, the Medscape data show.

For the physicians who did encounter financial hardships, relief came in several forms.

Many turned to “the federal Paycheck Protection Program to help keep themselves afloat; some were able to renegotiate their lease contracts; a large percentage reduced their staff, which reduced their expenses; and those in capitated plans were still getting paid even though they weren’t seeing as many patients,” Michael Belkin, JD, divisional vice president at Merritt Hawkins and Associates in Dallas, said in an interview.

One complication on the road to recovery was the furloughs experienced by some gastroenterologists, but work hours for the specialty have largely recovered. The prepandemic average was 53 hours per week, compared with 52 hours for this year’s gastroenterologist respondents, who represented about 2% of the 17,903 Medscape member physicians who completed the survey.

Among the gastroenterologists surveyed who did experience negative financial or practice-related effects from the pandemic, about one-third estimated that it would take 2-3 years for their income to return to the pre-COVID level, and 14% believe that it will never return to those levels. It is worth noting, however, that 45% of physicians overall reported no such harms last year.

Despite the drop in their incomes last year, more gastroenterologists said that they felt fairly compensated in 2020 than indicated as such in 2019 (55% vs. 52%). This year’s higher figure, though, is on the low end of the scale: of the 29 specialties included, only 4 were lower, and 19 were higher. Five others were the same, according to Medscape’s findings.

In other matters covered by the survey, gastroenterologists found themselves closer to the top. When asked if they would choose medicine again, 81% said yes. Only 8 of the 29 specialties were higher; 93% of gastroenterologists said they would choose gastroenterology again. Only four specialties were higher.

The survey was conducted from Oct. 6, 2020, to Feb. 11, 2021, and had a sampling error of ±0.73%. The salary figures were calculated using data for full-time physicians only.

A version of this article first appeared on Medscape.com.

Despite the shutdowns and plummeting patient volumes early in the COVID-19 pandemic, gastroenterologists’ earnings were just 3.1% lower in 2020 than in 2019, according to new survey results from Medscape.

That drop, from $419,000 to $406,000, was larger, however, than the average for all specialists, which slipped just 0.6% in 2020.

“Most gastroenterologists who saw a drop in income cited COVID-19–related issues, such as job loss, fewer hours, and fewer patients,” Keith L. Martin wrote in the 2021 Medscape Gastroenterologist Compensation Report.

Specialties with larger declines than gastroenterology included dermatology (–4%), pediatrics (–5%), and otolaryngology (–9%). Conversely, plastic surgeons saw the largest increases last year, with their average compensation rising 10% over 2019. Oncologists (+7%) and cardiologists (+5%) also did well, the Medscape data show.

For the physicians who did encounter financial hardships, relief came in several forms.

Many turned to “the federal Paycheck Protection Program to help keep themselves afloat; some were able to renegotiate their lease contracts; a large percentage reduced their staff, which reduced their expenses; and those in capitated plans were still getting paid even though they weren’t seeing as many patients,” Michael Belkin, JD, divisional vice president at Merritt Hawkins and Associates in Dallas, said in an interview.

One complication on the road to recovery was the furloughs experienced by some gastroenterologists, but work hours for the specialty have largely recovered. The prepandemic average was 53 hours per week, compared with 52 hours for this year’s gastroenterologist respondents, who represented about 2% of the 17,903 Medscape member physicians who completed the survey.

Among the gastroenterologists surveyed who did experience negative financial or practice-related effects from the pandemic, about one-third estimated that it would take 2-3 years for their income to return to the pre-COVID level, and 14% believe that it will never return to those levels. It is worth noting, however, that 45% of physicians overall reported no such harms last year.

Despite the drop in their incomes last year, more gastroenterologists said that they felt fairly compensated in 2020 than indicated as such in 2019 (55% vs. 52%). This year’s higher figure, though, is on the low end of the scale: of the 29 specialties included, only 4 were lower, and 19 were higher. Five others were the same, according to Medscape’s findings.

In other matters covered by the survey, gastroenterologists found themselves closer to the top. When asked if they would choose medicine again, 81% said yes. Only 8 of the 29 specialties were higher; 93% of gastroenterologists said they would choose gastroenterology again. Only four specialties were higher.

The survey was conducted from Oct. 6, 2020, to Feb. 11, 2021, and had a sampling error of ±0.73%. The salary figures were calculated using data for full-time physicians only.

A version of this article first appeared on Medscape.com.

Despite the shutdowns and plummeting patient volumes early in the COVID-19 pandemic, gastroenterologists’ earnings were just 3.1% lower in 2020 than in 2019, according to new survey results from Medscape.

That drop, from $419,000 to $406,000, was larger, however, than the average for all specialists, which slipped just 0.6% in 2020.

“Most gastroenterologists who saw a drop in income cited COVID-19–related issues, such as job loss, fewer hours, and fewer patients,” Keith L. Martin wrote in the 2021 Medscape Gastroenterologist Compensation Report.

Specialties with larger declines than gastroenterology included dermatology (–4%), pediatrics (–5%), and otolaryngology (–9%). Conversely, plastic surgeons saw the largest increases last year, with their average compensation rising 10% over 2019. Oncologists (+7%) and cardiologists (+5%) also did well, the Medscape data show.

For the physicians who did encounter financial hardships, relief came in several forms.

Many turned to “the federal Paycheck Protection Program to help keep themselves afloat; some were able to renegotiate their lease contracts; a large percentage reduced their staff, which reduced their expenses; and those in capitated plans were still getting paid even though they weren’t seeing as many patients,” Michael Belkin, JD, divisional vice president at Merritt Hawkins and Associates in Dallas, said in an interview.

One complication on the road to recovery was the furloughs experienced by some gastroenterologists, but work hours for the specialty have largely recovered. The prepandemic average was 53 hours per week, compared with 52 hours for this year’s gastroenterologist respondents, who represented about 2% of the 17,903 Medscape member physicians who completed the survey.

Among the gastroenterologists surveyed who did experience negative financial or practice-related effects from the pandemic, about one-third estimated that it would take 2-3 years for their income to return to the pre-COVID level, and 14% believe that it will never return to those levels. It is worth noting, however, that 45% of physicians overall reported no such harms last year.

Despite the drop in their incomes last year, more gastroenterologists said that they felt fairly compensated in 2020 than indicated as such in 2019 (55% vs. 52%). This year’s higher figure, though, is on the low end of the scale: of the 29 specialties included, only 4 were lower, and 19 were higher. Five others were the same, according to Medscape’s findings.

In other matters covered by the survey, gastroenterologists found themselves closer to the top. When asked if they would choose medicine again, 81% said yes. Only 8 of the 29 specialties were higher; 93% of gastroenterologists said they would choose gastroenterology again. Only four specialties were higher.

The survey was conducted from Oct. 6, 2020, to Feb. 11, 2021, and had a sampling error of ±0.73%. The salary figures were calculated using data for full-time physicians only.

A version of this article first appeared on Medscape.com.

Patient navigation as a best practice for GI procedures

Colonoscopy is the preferred method for colorectal cancer (CRC) screening. Among scheduled outpatient colonoscopies, key metrics like no-show rates and poor bowel preparation can be as high as 25% in some facilities. These missed appointments and repeated calls with patients have been an important source of wasted resources, poor patient outcomes, and revenue loss for endoscopy facilities (estimated to be up to $1 million dollars for 10-member GI practice).

Studies have shown that patient navigation (PN), a patient-centered approach, overcomes barriers in health care delivery, thus improving adherence to CRC screening. Typically, navigators are specialized health practitioners who fill a variety of functions, including providing updates and instructions to patients, as well as assisting with test-related fears. Despite the overall cost-effectiveness, PN programs require significant resources from hospitals or medical groups. The continued focus in the United States on value-based medicine has provided an urgent need for cost-effective treatments that are also readily available to most physicians.
 

Digital navigation to automate navigation for colonoscopy and other GI procedures

Digital navigation (DN) is a new navigation technique that enables patients to receive appointment updates, resources related to a treatment or condition, stepwise bowel prep directions, and other periprocedural guidance in an automated and convenient manner (see Figure below). Given the widespread use of mobile phones, DN has the ability to change the way doctors and health care providers work. This led to Mount Sinai Health System, New York, conducting a quality improvement program to automate and evaluate the effectiveness of an automated text messaging and web-based “digital navigation” platform for decreasing colonoscopy appointment no-show rates.

Dr. Ashish Atreja/Icahn School of Medicine

If a valid phone number was available in the patient’s electronic medical record chart and they did not opt out of receiving text message communications from the Mount Sinai Health System, patients over the age of 18 years who were scheduled for a colonoscopy at either of Mount Sinai Hospital, Mount Sinai Morningside, or Mount Sinai West were automatically sent DN SMS messages. The RxUniverse software platform (Rx.Health, New York) was used to send DN content through SMS to all eligible patients. The software platform interfaces with the EMR and endoscopy system (Provation) to automatically extract patient phone number and appointment details.
 

Impact of digital navigation and patient engagement

This study at Mount Sinai Health System demonstrated that patient engagement with SMS-based navigation is strongly predictive of colonoscopy completion. Patients with high engagement with digital navigation are about four times more likely to complete colonoscopy. Of all covariates included in the model, high DN engagement level had the largest effect size (odds ratio, 3.97), compared with no engagement. For health systems with patient navigators, targeting patients who are unlikely to engage DN or are low-engagers may be a more efficient use of person-to-person navigation.

Value-based reimbursement and cost-effectiveness have emerged as core principles in American health care reform, possibly requiring the creation of affordable, cost-effective approaches. Our research at Mount Sinai Health System suggested that SMS-based navigation can be a potential cost-effective strategy for reducing no-show rates. Beyond appointment no-shows, adequate bowel preparation is another important component of the preprocedure navigation process. Insufficient bowel preparation requires a repeat procedure, as poor visualization of the colon results in reduced therapeutic benefit from screening colonoscopy. We’ve shown in previous studies that our DN platform can increase bowel preparation efficiency, which results in lower rates of aborted procedures.

Missed colonoscopies not only cause longer wait times for patients, but they also cost the average facility $725 a day in lost revenue. It has been found through studies that traditional PN is cost-effective, with additional revenue generated from increased colonoscopy completion rates exceeding the costs of program implementation. While formal cost analyses have not been conducted on DN, estimates have shown around $1 million in annual savings for an average ambulatory surgery center or 10-member GI practice.
 

Looking ahead: AGA digital transformation network

After positive results for the Rx.Health’s platform were seen at Mount Sinai Health System, the American Gastroenterological Association partnered with Rx.Health to provide the GI community with a GI endoscopy transformation network. The core purpose of this endoscopy transformation network is to take an evidence-based approach and use digital medicine to positively affect key metrics and safety around periprocedural care and support “procedure bundles.” To illustrate the specific case of colonoscopy, these included the following: enhancing colorectal cancer surveillance rates though a comprehensive screening test strategy, decreasing no-show rates through shared decision-making and better preprocedure engagement, improving rates of adequate bowel preparation, benchmarking safety of procedures nationwide, and ensuring patient satisfaction and adequate recall for repeat procedures. These metrics represent key sources of revenue loss for provider organizations and, more importantly, have negative implications on patient care.

This collaboration is now supporting the implementation and expansion of the digital navigation program to all GI procedures at more than 15 different sites across the country.

Dr. Atreja is an adjunct associate professor at the Icahn School of Medicine at Mount Sinai, New York, and chief information officer and chief digital health officer at UC Davis Medical Center, Sacramento. The Icahn School of Medicine has licensed technology to Rx.Health. Dr. Atreja has no other conflicts to disclose

Patient navigation as a best practice for GI procedures

Colonoscopy is the preferred method for colorectal cancer (CRC) screening. Among scheduled outpatient colonoscopies, key metrics like no-show rates and poor bowel preparation can be as high as 25% in some facilities. These missed appointments and repeated calls with patients have been an important source of wasted resources, poor patient outcomes, and revenue loss for endoscopy facilities (estimated to be up to $1 million dollars for 10-member GI practice).

Studies have shown that patient navigation (PN), a patient-centered approach, overcomes barriers in health care delivery, thus improving adherence to CRC screening. Typically, navigators are specialized health practitioners who fill a variety of functions, including providing updates and instructions to patients, as well as assisting with test-related fears. Despite the overall cost-effectiveness, PN programs require significant resources from hospitals or medical groups. The continued focus in the United States on value-based medicine has provided an urgent need for cost-effective treatments that are also readily available to most physicians.
 

Digital navigation to automate navigation for colonoscopy and other GI procedures

Digital navigation (DN) is a new navigation technique that enables patients to receive appointment updates, resources related to a treatment or condition, stepwise bowel prep directions, and other periprocedural guidance in an automated and convenient manner (see Figure below). Given the widespread use of mobile phones, DN has the ability to change the way doctors and health care providers work. This led to Mount Sinai Health System, New York, conducting a quality improvement program to automate and evaluate the effectiveness of an automated text messaging and web-based “digital navigation” platform for decreasing colonoscopy appointment no-show rates.

Dr. Ashish Atreja/Icahn School of Medicine

If a valid phone number was available in the patient’s electronic medical record chart and they did not opt out of receiving text message communications from the Mount Sinai Health System, patients over the age of 18 years who were scheduled for a colonoscopy at either of Mount Sinai Hospital, Mount Sinai Morningside, or Mount Sinai West were automatically sent DN SMS messages. The RxUniverse software platform (Rx.Health, New York) was used to send DN content through SMS to all eligible patients. The software platform interfaces with the EMR and endoscopy system (Provation) to automatically extract patient phone number and appointment details.
 

Impact of digital navigation and patient engagement

This study at Mount Sinai Health System demonstrated that patient engagement with SMS-based navigation is strongly predictive of colonoscopy completion. Patients with high engagement with digital navigation are about four times more likely to complete colonoscopy. Of all covariates included in the model, high DN engagement level had the largest effect size (odds ratio, 3.97), compared with no engagement. For health systems with patient navigators, targeting patients who are unlikely to engage DN or are low-engagers may be a more efficient use of person-to-person navigation.

Value-based reimbursement and cost-effectiveness have emerged as core principles in American health care reform, possibly requiring the creation of affordable, cost-effective approaches. Our research at Mount Sinai Health System suggested that SMS-based navigation can be a potential cost-effective strategy for reducing no-show rates. Beyond appointment no-shows, adequate bowel preparation is another important component of the preprocedure navigation process. Insufficient bowel preparation requires a repeat procedure, as poor visualization of the colon results in reduced therapeutic benefit from screening colonoscopy. We’ve shown in previous studies that our DN platform can increase bowel preparation efficiency, which results in lower rates of aborted procedures.

Missed colonoscopies not only cause longer wait times for patients, but they also cost the average facility $725 a day in lost revenue. It has been found through studies that traditional PN is cost-effective, with additional revenue generated from increased colonoscopy completion rates exceeding the costs of program implementation. While formal cost analyses have not been conducted on DN, estimates have shown around $1 million in annual savings for an average ambulatory surgery center or 10-member GI practice.
 

Looking ahead: AGA digital transformation network

After positive results for the Rx.Health’s platform were seen at Mount Sinai Health System, the American Gastroenterological Association partnered with Rx.Health to provide the GI community with a GI endoscopy transformation network. The core purpose of this endoscopy transformation network is to take an evidence-based approach and use digital medicine to positively affect key metrics and safety around periprocedural care and support “procedure bundles.” To illustrate the specific case of colonoscopy, these included the following: enhancing colorectal cancer surveillance rates though a comprehensive screening test strategy, decreasing no-show rates through shared decision-making and better preprocedure engagement, improving rates of adequate bowel preparation, benchmarking safety of procedures nationwide, and ensuring patient satisfaction and adequate recall for repeat procedures. These metrics represent key sources of revenue loss for provider organizations and, more importantly, have negative implications on patient care.

This collaboration is now supporting the implementation and expansion of the digital navigation program to all GI procedures at more than 15 different sites across the country.

Dr. Atreja is an adjunct associate professor at the Icahn School of Medicine at Mount Sinai, New York, and chief information officer and chief digital health officer at UC Davis Medical Center, Sacramento. The Icahn School of Medicine has licensed technology to Rx.Health. Dr. Atreja has no other conflicts to disclose

Patient navigation as a best practice for GI procedures

Colonoscopy is the preferred method for colorectal cancer (CRC) screening. Among scheduled outpatient colonoscopies, key metrics like no-show rates and poor bowel preparation can be as high as 25% in some facilities. These missed appointments and repeated calls with patients have been an important source of wasted resources, poor patient outcomes, and revenue loss for endoscopy facilities (estimated to be up to $1 million dollars for 10-member GI practice).

Studies have shown that patient navigation (PN), a patient-centered approach, overcomes barriers in health care delivery, thus improving adherence to CRC screening. Typically, navigators are specialized health practitioners who fill a variety of functions, including providing updates and instructions to patients, as well as assisting with test-related fears. Despite the overall cost-effectiveness, PN programs require significant resources from hospitals or medical groups. The continued focus in the United States on value-based medicine has provided an urgent need for cost-effective treatments that are also readily available to most physicians.
 

Digital navigation to automate navigation for colonoscopy and other GI procedures

Digital navigation (DN) is a new navigation technique that enables patients to receive appointment updates, resources related to a treatment or condition, stepwise bowel prep directions, and other periprocedural guidance in an automated and convenient manner (see Figure below). Given the widespread use of mobile phones, DN has the ability to change the way doctors and health care providers work. This led to Mount Sinai Health System, New York, conducting a quality improvement program to automate and evaluate the effectiveness of an automated text messaging and web-based “digital navigation” platform for decreasing colonoscopy appointment no-show rates.

Dr. Ashish Atreja/Icahn School of Medicine

If a valid phone number was available in the patient’s electronic medical record chart and they did not opt out of receiving text message communications from the Mount Sinai Health System, patients over the age of 18 years who were scheduled for a colonoscopy at either of Mount Sinai Hospital, Mount Sinai Morningside, or Mount Sinai West were automatically sent DN SMS messages. The RxUniverse software platform (Rx.Health, New York) was used to send DN content through SMS to all eligible patients. The software platform interfaces with the EMR and endoscopy system (Provation) to automatically extract patient phone number and appointment details.
 

Impact of digital navigation and patient engagement

This study at Mount Sinai Health System demonstrated that patient engagement with SMS-based navigation is strongly predictive of colonoscopy completion. Patients with high engagement with digital navigation are about four times more likely to complete colonoscopy. Of all covariates included in the model, high DN engagement level had the largest effect size (odds ratio, 3.97), compared with no engagement. For health systems with patient navigators, targeting patients who are unlikely to engage DN or are low-engagers may be a more efficient use of person-to-person navigation.

Value-based reimbursement and cost-effectiveness have emerged as core principles in American health care reform, possibly requiring the creation of affordable, cost-effective approaches. Our research at Mount Sinai Health System suggested that SMS-based navigation can be a potential cost-effective strategy for reducing no-show rates. Beyond appointment no-shows, adequate bowel preparation is another important component of the preprocedure navigation process. Insufficient bowel preparation requires a repeat procedure, as poor visualization of the colon results in reduced therapeutic benefit from screening colonoscopy. We’ve shown in previous studies that our DN platform can increase bowel preparation efficiency, which results in lower rates of aborted procedures.

Missed colonoscopies not only cause longer wait times for patients, but they also cost the average facility $725 a day in lost revenue. It has been found through studies that traditional PN is cost-effective, with additional revenue generated from increased colonoscopy completion rates exceeding the costs of program implementation. While formal cost analyses have not been conducted on DN, estimates have shown around $1 million in annual savings for an average ambulatory surgery center or 10-member GI practice.
 

Looking ahead: AGA digital transformation network

After positive results for the Rx.Health’s platform were seen at Mount Sinai Health System, the American Gastroenterological Association partnered with Rx.Health to provide the GI community with a GI endoscopy transformation network. The core purpose of this endoscopy transformation network is to take an evidence-based approach and use digital medicine to positively affect key metrics and safety around periprocedural care and support “procedure bundles.” To illustrate the specific case of colonoscopy, these included the following: enhancing colorectal cancer surveillance rates though a comprehensive screening test strategy, decreasing no-show rates through shared decision-making and better preprocedure engagement, improving rates of adequate bowel preparation, benchmarking safety of procedures nationwide, and ensuring patient satisfaction and adequate recall for repeat procedures. These metrics represent key sources of revenue loss for provider organizations and, more importantly, have negative implications on patient care.

This collaboration is now supporting the implementation and expansion of the digital navigation program to all GI procedures at more than 15 different sites across the country.

Dr. Atreja is an adjunct associate professor at the Icahn School of Medicine at Mount Sinai, New York, and chief information officer and chief digital health officer at UC Davis Medical Center, Sacramento. The Icahn School of Medicine has licensed technology to Rx.Health. Dr. Atreja has no other conflicts to disclose

Have you ever had a nightmare you’re running late? Recently I dreamt I was seeing patients on a ship, a little cruiser like the ones that give you tours of Boston Harbor, with low ceilings and narrow iron stairs. My nurse stood where what would have been the coffee and danish window. My first patient was a newborn (this was a nightmare, in case you forgot) who was enormous. She had a big belly and spindly legs that hung off the table. Uniform, umbilicated papules and pustules covered her body. At the sight of her, terror ripped through me – no clue. I rushed to the doctor lounge (nice the ship had one) and flipped channels on a little TV mounted on the ceiling. Suddenly, my nurse burst in, she was frantic because dozens of angry adults and crying children were crammed in the hallway. Apparently, I had been watching TV for hours and my whole clinic was now backed up.

Running-late dreams are common and usually relate to real life. For us, the clinic has been busy lately. Vaccinated patients are returning after a year with their skin cancers that have flourished and psoriasis covering them like kudzu. Staying on time has been difficult. Yet, despite the challenge, some of my colleagues manage easily. Why are they always on time? I talked to a few to get insight. In particular, they “see the floor” better than other docs and therefore make continual adjustments to stay on pace. At its essence, they are using super-powers of observation to make decisions. It reminded me of a podcast about court awareness and great passers in basketball like the Charlotte Hornets’ LaMelo Ball and NBA great, Bill Bradley.

Bradley had an extraordinary ability to know where all the players were, and where they would be, at any given moment. He spent years honing this skill, noticing details in store windows as he stared straight ahead walking down a street. It’s reported his peripheral vision extended 5%-15% wider than average and he used it to gather more information and to process it more quickly. As a result he made outstanding decisions and fast, ultimately earning a spot in the Hall of Fame in Springfield.

Hall of Fame clinicians similarly take in a wider view than others and process that information quickly. They know how much time they have spent in the room, sense the emotional needs of the patient and anticipate the complexity of the problem. They quickly get to the critical questions and examinations that will make the diagnosis. They know the experience and skill of their medical assistant. They know the level of difficulty and even the temperament of patients who lie ahead on the schedule. All this is processed and used in moment-to-moment decision making. Do I sit down or stand up now? Can I excise this today, or reschedule? Do I ask another question? Do I step out of this room and see another in parallel while this biopsy is set up? And always, do I dare ask about grandkids or do I politely move on?

By broadening out their vision, they optimize their clinic, providing the best possible service, whether the day is busy or slow. I found their economy of motion also means they are less exhausted at the end of the day. I bet if when they dream of being on a ship, they’re sipping a Mai Tai, lounging on the deck.

For more on Bill Bradley and becoming more observant about your surroundings, you might appreciate the following:

www.newyorker.com/magazine/1965/01/23/a-sense-of-where-you-are and freakonomics.com/podcast/nsq-mindfulness/

Dr. Benabio is director of Healthcare Transformation and chief of dermatology at Kaiser Permanente San Diego. The opinions expressed in this column are his own and do not represent those of Kaiser Permanente. Dr. Benabio is @Dermdoc on Twitter. Write to him at [email protected].

Have you ever had a nightmare you’re running late? Recently I dreamt I was seeing patients on a ship, a little cruiser like the ones that give you tours of Boston Harbor, with low ceilings and narrow iron stairs. My nurse stood where what would have been the coffee and danish window. My first patient was a newborn (this was a nightmare, in case you forgot) who was enormous. She had a big belly and spindly legs that hung off the table. Uniform, umbilicated papules and pustules covered her body. At the sight of her, terror ripped through me – no clue. I rushed to the doctor lounge (nice the ship had one) and flipped channels on a little TV mounted on the ceiling. Suddenly, my nurse burst in, she was frantic because dozens of angry adults and crying children were crammed in the hallway. Apparently, I had been watching TV for hours and my whole clinic was now backed up.

Running-late dreams are common and usually relate to real life. For us, the clinic has been busy lately. Vaccinated patients are returning after a year with their skin cancers that have flourished and psoriasis covering them like kudzu. Staying on time has been difficult. Yet, despite the challenge, some of my colleagues manage easily. Why are they always on time? I talked to a few to get insight. In particular, they “see the floor” better than other docs and therefore make continual adjustments to stay on pace. At its essence, they are using super-powers of observation to make decisions. It reminded me of a podcast about court awareness and great passers in basketball like the Charlotte Hornets’ LaMelo Ball and NBA great, Bill Bradley.

Bradley had an extraordinary ability to know where all the players were, and where they would be, at any given moment. He spent years honing this skill, noticing details in store windows as he stared straight ahead walking down a street. It’s reported his peripheral vision extended 5%-15% wider than average and he used it to gather more information and to process it more quickly. As a result he made outstanding decisions and fast, ultimately earning a spot in the Hall of Fame in Springfield.

Hall of Fame clinicians similarly take in a wider view than others and process that information quickly. They know how much time they have spent in the room, sense the emotional needs of the patient and anticipate the complexity of the problem. They quickly get to the critical questions and examinations that will make the diagnosis. They know the experience and skill of their medical assistant. They know the level of difficulty and even the temperament of patients who lie ahead on the schedule. All this is processed and used in moment-to-moment decision making. Do I sit down or stand up now? Can I excise this today, or reschedule? Do I ask another question? Do I step out of this room and see another in parallel while this biopsy is set up? And always, do I dare ask about grandkids or do I politely move on?

By broadening out their vision, they optimize their clinic, providing the best possible service, whether the day is busy or slow. I found their economy of motion also means they are less exhausted at the end of the day. I bet if when they dream of being on a ship, they’re sipping a Mai Tai, lounging on the deck.

For more on Bill Bradley and becoming more observant about your surroundings, you might appreciate the following:

www.newyorker.com/magazine/1965/01/23/a-sense-of-where-you-are and freakonomics.com/podcast/nsq-mindfulness/

Dr. Benabio is director of Healthcare Transformation and chief of dermatology at Kaiser Permanente San Diego. The opinions expressed in this column are his own and do not represent those of Kaiser Permanente. Dr. Benabio is @Dermdoc on Twitter. Write to him at [email protected].

Have you ever had a nightmare you’re running late? Recently I dreamt I was seeing patients on a ship, a little cruiser like the ones that give you tours of Boston Harbor, with low ceilings and narrow iron stairs. My nurse stood where what would have been the coffee and danish window. My first patient was a newborn (this was a nightmare, in case you forgot) who was enormous. She had a big belly and spindly legs that hung off the table. Uniform, umbilicated papules and pustules covered her body. At the sight of her, terror ripped through me – no clue. I rushed to the doctor lounge (nice the ship had one) and flipped channels on a little TV mounted on the ceiling. Suddenly, my nurse burst in, she was frantic because dozens of angry adults and crying children were crammed in the hallway. Apparently, I had been watching TV for hours and my whole clinic was now backed up.

Running-late dreams are common and usually relate to real life. For us, the clinic has been busy lately. Vaccinated patients are returning after a year with their skin cancers that have flourished and psoriasis covering them like kudzu. Staying on time has been difficult. Yet, despite the challenge, some of my colleagues manage easily. Why are they always on time? I talked to a few to get insight. In particular, they “see the floor” better than other docs and therefore make continual adjustments to stay on pace. At its essence, they are using super-powers of observation to make decisions. It reminded me of a podcast about court awareness and great passers in basketball like the Charlotte Hornets’ LaMelo Ball and NBA great, Bill Bradley.

Bradley had an extraordinary ability to know where all the players were, and where they would be, at any given moment. He spent years honing this skill, noticing details in store windows as he stared straight ahead walking down a street. It’s reported his peripheral vision extended 5%-15% wider than average and he used it to gather more information and to process it more quickly. As a result he made outstanding decisions and fast, ultimately earning a spot in the Hall of Fame in Springfield.

Hall of Fame clinicians similarly take in a wider view than others and process that information quickly. They know how much time they have spent in the room, sense the emotional needs of the patient and anticipate the complexity of the problem. They quickly get to the critical questions and examinations that will make the diagnosis. They know the experience and skill of their medical assistant. They know the level of difficulty and even the temperament of patients who lie ahead on the schedule. All this is processed and used in moment-to-moment decision making. Do I sit down or stand up now? Can I excise this today, or reschedule? Do I ask another question? Do I step out of this room and see another in parallel while this biopsy is set up? And always, do I dare ask about grandkids or do I politely move on?

By broadening out their vision, they optimize their clinic, providing the best possible service, whether the day is busy or slow. I found their economy of motion also means they are less exhausted at the end of the day. I bet if when they dream of being on a ship, they’re sipping a Mai Tai, lounging on the deck.

For more on Bill Bradley and becoming more observant about your surroundings, you might appreciate the following:

www.newyorker.com/magazine/1965/01/23/a-sense-of-where-you-are and freakonomics.com/podcast/nsq-mindfulness/

Dr. Benabio is director of Healthcare Transformation and chief of dermatology at Kaiser Permanente San Diego. The opinions expressed in this column are his own and do not represent those of Kaiser Permanente. Dr. Benabio is @Dermdoc on Twitter. Write to him at [email protected].