Clinical Review

According to researchers from Columbia University in New York City, McMaster University in Hamilton, Ontario, Canada, and Ontario HIV Treatment Network, in Canada, homelessness and unstable housing situations are associated with higher rates of HIV and hepatitis C infection (HCV). They reviewed 152 studies involving 139,757 participants who had HIV or were co-infected with HCV. The researchers found “strong evidence” that the lack of stable, secure, adequate housing is a significant barrier to consistent and appropriate medical care, adherence to treatment, sustained viral suppression, and reduction of risk behaviors.

Research data showed that the worse the housing status, the less the engagement and utilization of HIV medical care. Homeless patients had more emergency department (ED) admissions; homeless males had longer hospital stays; and homeless injection-drug users were more often hospitalized than were people with HIV in high socioeconomic neighborhoods.

In another study, homelessness was significantly associated with baseline HCV-positive status. Twenty-five studies reported that homelessness or unstable housing was associated with significantly poorer outcomes on 1 or more indications of physical or mental health functioning and quality of life, mental health symptoms or diagnosis, or diagnosed physical health comorbidities, such as HCV and tuberculosis. The studies also showed the impact of having a home on both treatment and adherence to treatment. One study of co-infected patients who were on antiretroviral therapy (ART) or beginning HCV treatment found that good housing conditions reduced the risk of nonadherence to ART, regardless of the treatment of HCV. Stable housing also doubled the odds of ART use.     

 Data from another study also found participants with a fixed address were more likely to stop abusing drugs. Obtaining stable housing was also associated with using an outpatient setting rather than the ED as the usual source of care.

 “Housing first” interventions are receiving growing attention, the researchers note, as a potential health care cost-containment strategy. As interventions for people with complex health conditions, changing housing status is “both possible and promising.”

Source:
Aidala AA, Wilson MG, Shubert V, et al.  Am J Public Health. 2016;106(1):e1-e23
doi: 10.2105/AJPH.2015.302905.

According to researchers from Columbia University in New York City, McMaster University in Hamilton, Ontario, Canada, and Ontario HIV Treatment Network, in Canada, homelessness and unstable housing situations are associated with higher rates of HIV and hepatitis C infection (HCV). They reviewed 152 studies involving 139,757 participants who had HIV or were co-infected with HCV. The researchers found “strong evidence” that the lack of stable, secure, adequate housing is a significant barrier to consistent and appropriate medical care, adherence to treatment, sustained viral suppression, and reduction of risk behaviors.

Research data showed that the worse the housing status, the less the engagement and utilization of HIV medical care. Homeless patients had more emergency department (ED) admissions; homeless males had longer hospital stays; and homeless injection-drug users were more often hospitalized than were people with HIV in high socioeconomic neighborhoods.

In another study, homelessness was significantly associated with baseline HCV-positive status. Twenty-five studies reported that homelessness or unstable housing was associated with significantly poorer outcomes on 1 or more indications of physical or mental health functioning and quality of life, mental health symptoms or diagnosis, or diagnosed physical health comorbidities, such as HCV and tuberculosis. The studies also showed the impact of having a home on both treatment and adherence to treatment. One study of co-infected patients who were on antiretroviral therapy (ART) or beginning HCV treatment found that good housing conditions reduced the risk of nonadherence to ART, regardless of the treatment of HCV. Stable housing also doubled the odds of ART use.     

 Data from another study also found participants with a fixed address were more likely to stop abusing drugs. Obtaining stable housing was also associated with using an outpatient setting rather than the ED as the usual source of care.

 “Housing first” interventions are receiving growing attention, the researchers note, as a potential health care cost-containment strategy. As interventions for people with complex health conditions, changing housing status is “both possible and promising.”

Source:
Aidala AA, Wilson MG, Shubert V, et al.  Am J Public Health. 2016;106(1):e1-e23
doi: 10.2105/AJPH.2015.302905.

According to researchers from Columbia University in New York City, McMaster University in Hamilton, Ontario, Canada, and Ontario HIV Treatment Network, in Canada, homelessness and unstable housing situations are associated with higher rates of HIV and hepatitis C infection (HCV). They reviewed 152 studies involving 139,757 participants who had HIV or were co-infected with HCV. The researchers found “strong evidence” that the lack of stable, secure, adequate housing is a significant barrier to consistent and appropriate medical care, adherence to treatment, sustained viral suppression, and reduction of risk behaviors.

Research data showed that the worse the housing status, the less the engagement and utilization of HIV medical care. Homeless patients had more emergency department (ED) admissions; homeless males had longer hospital stays; and homeless injection-drug users were more often hospitalized than were people with HIV in high socioeconomic neighborhoods.

In another study, homelessness was significantly associated with baseline HCV-positive status. Twenty-five studies reported that homelessness or unstable housing was associated with significantly poorer outcomes on 1 or more indications of physical or mental health functioning and quality of life, mental health symptoms or diagnosis, or diagnosed physical health comorbidities, such as HCV and tuberculosis. The studies also showed the impact of having a home on both treatment and adherence to treatment. One study of co-infected patients who were on antiretroviral therapy (ART) or beginning HCV treatment found that good housing conditions reduced the risk of nonadherence to ART, regardless of the treatment of HCV. Stable housing also doubled the odds of ART use.     

 Data from another study also found participants with a fixed address were more likely to stop abusing drugs. Obtaining stable housing was also associated with using an outpatient setting rather than the ED as the usual source of care.

 “Housing first” interventions are receiving growing attention, the researchers note, as a potential health care cost-containment strategy. As interventions for people with complex health conditions, changing housing status is “both possible and promising.”

Source:
Aidala AA, Wilson MG, Shubert V, et al.  Am J Public Health. 2016;106(1):e1-e23
doi: 10.2105/AJPH.2015.302905.

Cardiac surgery patients have a high risk of excessive postoperative bleeding as a consequence of procoagulant blood products, vasoconstrictors, and poor organ perfusion. Researchers who conducted a study at University Hospital in São Paulo, Brazil,  say that for clinicians to be prepared for timely interventions, it helps to know which patients to watch and when to identify the risk factors.

In their prospective study of 323 patients, episodes of excessive bleeding were concentrated in the first and second postoperative hours, and  21% of complications required interventions, such as vasoactive medication titration, protamine supplementation, and transfusions of blood products. During the immediate postoperative time, 105 patients developed excessive bleeding with 39 in the first hour, followed by 36 patients in the second hour, and 8 in the third hour.

The researchers found that other risk factors for excessive bleeding were chronic hypertension, greater height, body mass index (BMI) < 26.35 kg/m², higher hematocrit, and intraoperative heparin dose > 312.5 mg without subsequent platelet transfusion. The researchers say platelet transfusions may have been protective. Certain variables, such as lower BMI and male gender, may have been explained by greater clot strength and faster rate of fibrin formation in women.

Patients at risk for excessive bleeding also had lower preoperative platelet count, although the mean value was within the normal range. But given that more than half the study group used aspirin and 11% used an adenosine diphosphate-receptor blocker, the researchers say they may have had a higher prevalence of unknown platelet dysfunctions.

Source:
Lopes CT, Brunori EFR, Cavalcante AMRZ, et al. Heart Lung. 2016;45(1):64-69.e2.
doi: 10.1016/j.hrtlng.2015.09.

Cardiac surgery patients have a high risk of excessive postoperative bleeding as a consequence of procoagulant blood products, vasoconstrictors, and poor organ perfusion. Researchers who conducted a study at University Hospital in São Paulo, Brazil,  say that for clinicians to be prepared for timely interventions, it helps to know which patients to watch and when to identify the risk factors.

In their prospective study of 323 patients, episodes of excessive bleeding were concentrated in the first and second postoperative hours, and  21% of complications required interventions, such as vasoactive medication titration, protamine supplementation, and transfusions of blood products. During the immediate postoperative time, 105 patients developed excessive bleeding with 39 in the first hour, followed by 36 patients in the second hour, and 8 in the third hour.

The researchers found that other risk factors for excessive bleeding were chronic hypertension, greater height, body mass index (BMI) < 26.35 kg/m², higher hematocrit, and intraoperative heparin dose > 312.5 mg without subsequent platelet transfusion. The researchers say platelet transfusions may have been protective. Certain variables, such as lower BMI and male gender, may have been explained by greater clot strength and faster rate of fibrin formation in women.

Patients at risk for excessive bleeding also had lower preoperative platelet count, although the mean value was within the normal range. But given that more than half the study group used aspirin and 11% used an adenosine diphosphate-receptor blocker, the researchers say they may have had a higher prevalence of unknown platelet dysfunctions.

Source:
Lopes CT, Brunori EFR, Cavalcante AMRZ, et al. Heart Lung. 2016;45(1):64-69.e2.
doi: 10.1016/j.hrtlng.2015.09.

Cardiac surgery patients have a high risk of excessive postoperative bleeding as a consequence of procoagulant blood products, vasoconstrictors, and poor organ perfusion. Researchers who conducted a study at University Hospital in São Paulo, Brazil,  say that for clinicians to be prepared for timely interventions, it helps to know which patients to watch and when to identify the risk factors.

In their prospective study of 323 patients, episodes of excessive bleeding were concentrated in the first and second postoperative hours, and  21% of complications required interventions, such as vasoactive medication titration, protamine supplementation, and transfusions of blood products. During the immediate postoperative time, 105 patients developed excessive bleeding with 39 in the first hour, followed by 36 patients in the second hour, and 8 in the third hour.

The researchers found that other risk factors for excessive bleeding were chronic hypertension, greater height, body mass index (BMI) < 26.35 kg/m², higher hematocrit, and intraoperative heparin dose > 312.5 mg without subsequent platelet transfusion. The researchers say platelet transfusions may have been protective. Certain variables, such as lower BMI and male gender, may have been explained by greater clot strength and faster rate of fibrin formation in women.

Patients at risk for excessive bleeding also had lower preoperative platelet count, although the mean value was within the normal range. But given that more than half the study group used aspirin and 11% used an adenosine diphosphate-receptor blocker, the researchers say they may have had a higher prevalence of unknown platelet dysfunctions.

Source:
Lopes CT, Brunori EFR, Cavalcante AMRZ, et al. Heart Lung. 2016;45(1):64-69.e2.
doi: 10.1016/j.hrtlng.2015.09.

Adherence to positive airway pressure (PAP) therapy is a difficult patient management issue. Clinicians at the John D. Dingell VA Medical Center in Detroit (VAMC Detroit) developed the O’Brien criteria and extensive patient education materials to increase patient adherence. The importance of PAP therapy and the reasons veterans should sleep with a PAP machine for 7 to 9 hours each night are stressed (many sleep only 4 to 5 hours). Several recent studies have confirmed widely varying PAP therapy adherence rates (30%-84%).^1-13 A majority of patients indicated that mask discomfort is the primary reason for nonadherence.¹

Adherence is affected by many factors, including heated humidity, patient education, mask type, and type of PAP machine (eg, continuous PAP [CPAP] vs bilevel PAP [BPAP]; auto-PAP vs CPAP). Other factors, such as race and economic status, also affect adherence.¹⁴ The Wisconsin Sleep Cohort Study found that patients with moderate-to-severe untreated obstructive sleep apnea (OSA) were 4 to 5 times more likely to die of a cardiovascular event and 3 times more likely to die of any cause.¹⁵ The morbidity and mortality associated with severe untreated OSA led the clinicians to intensify treatment efforts.¹⁶In this article, the authors summarize the initiative at the VAMC Detroit to enhance PAP therapy adherence in patients with sleep apnea. The goal was to motivate patients to maximize PAP machine use. This article is a guide that federal health care providers and their civilian counterparts in the private sector can use to maximize PAP machine use. Working toward that goal, a set of PAP “super user” criteria was developed and used to create a 5-point method for encouraging patients to maximize adherence to PAP therapy.

Background

Positive airway pressure is the room air pressure, measured in centimeters of H₂O, which splints open the airway to prevent snoring, apneas, and hypopneas. An apnea is a 90%-plus airway obstruction that lasts longer than 10 seconds and is seen with sleep study polysomnography. A hypopnea is a 30%-plus airway obstruction that lasts longer than 10 seconds and is accompanied by a 3% drop in pulse oximetry (SpO₂).

A CPAP device delivers pressure continuously through a medical air compressor or flow generator called a PAP machine. The BPAP machine has separate inspiratory pressure and expiratory pressure. Auto-PAP machines give minimum pressure and maximum pressure usually between the range of 4 cm H₂O to 20 cm H₂O. This machine finds the user’s median pressure (90th percentile) and maximum pressure and averages pressure over a specified period of use. The auto-PAP can then be set to CPAP mode and the pressure fixed or set to the 90th percentile.

O’Brien Criteria

The O’Brien criteria for PAP super-user status (Table 1) were developed for maximizing PAP machine use and presented at the 2013 John D. Dingell Sleep and Wake Disorders Center Symposium. There is no other published reference or criteria proposed for maximizing PAP machine adherence. A recent study on sleep time criteria suggested that a higher percentage of patients achieved normal functioning with longer duration nightly CPAP therapy, which is in line with the authors’ recommended PAP machine use duration.¹⁷

Positive airway pressure therapy is eligible for insurance reimbursement by Medicare and third-party payers for adult patients who have OSA and achieve 4 hours of nightly use for 70% of nights over 30 days. Coverage for CPAP therapy is initially limited to 12 weeks during which beneficiaries with an OSA diagnosis can be identified and any therapy benefits documented. Subsequent CPAP therapy is covered only for those OSA patients who benefit during the 12-week period.¹⁸At VAMC Detroit, the data covering the previous 30 days of use is downloaded. Medicare allows for the best 30-day period out of the 12-week window. The hospital, along with Harper Hospital and the Detroit Medical Centers in conjunction with the Wayne State University sleep program, is an Academic Center of Distinction, which follows the sleep guidelines and practice parameters for Medicare, third-party insurance companies, and the American Academy of Sleep Medicine.

The sleep clinic clinicians follow the clinical guidelines for evaluation, management, and long-term care of adults with OSA.^19,20 Follow-up visits are scheduled and made on a consultation basis up to 90 days for the required download or as necessary for PAP therapy. In this initiative, practitioners offer veteran-specific patient care with PAP therapy that exceeds Medicare guidelines. The success of this process yielded a growing cohort of PAP super users at VAMC Detroit. These patients exceed the Medicare criterion of 4 hours of nightly use for 70% of nights over 30 days. Thus, 4 hours of nightly use for 100% of nights over the same period was proposed as another criterion.

The super-user criteria, which provide motivation to reach the top, stimulate many patients to achieve the Medicare criteria. All 5 criteria must be satisfied to attain super-user status, and becoming a super user is not easy. In fact, the expectation is that, if an adherence data study is conducted, it will show that only a small percentage of all users meet the criteria. Maximum adherence is expected to be the tail (3%-4%) of a bell-shaped curve.

PAP Super-User Status

At the initial evaluation, practitioners create a self-fulfilling prophecy that, as first described by Merton, sets expectations.²¹ A self-fulfilling prophecy is a prediction that directly or indirectly causes the prediction to become true as a result of the positive feedback between belief and behavior.²¹ The personnel at VAMC Detroit sleep clinic set a tone that enables patients to meet and exceed the Medicare sleep guidelines and their expectations. Patients are encouraged to make it their personal mission to achieve the goal of becoming a PAP super user. The patients receive the O’Brien criteria for PAP super-user status—guidelines thought to contribute to higher quality of life.

The Medicare criterion emphasized is the minimum required for full adherence. The goal is to reduce sleepiness and increase well-being. The literature shows that increasing duration of sleep results in lower daytime sleepiness.²² Inadequate sleep has many detrimental effects. According to a recent study, insufficient sleep contributes to weight gain.²² Desired patient outcomes are increased sleep time without arousals, increased slow-wave sleep (SWS), consolidation of memories and rapid eye movement (REM), and improvement in emotional and procedural skill memories.²³ Patients are informed that using a PAP machine for 7 to 9 hours can reduce excessive daytime sleepiness and allow for more SWS and REM sleep, which help improve memory, judgment, and concentration. Many other studies have shown how 7 to 9 hours of sleep benefit adults. Thus, 7 to 9 hours became the criterion for maximizing PAP sleep time.

Initial Evaluation and Sleep Study

A primary care provider can enroll a patient into the clinic for a sleep study by requesting an evaluation. The consultation is then triaged using the STOP-BANG (Snoring, Tiredness, Observed apnea, high blood Pressure–Body mass index > 35, Age > 50, Neck circumference > 40 cm, Gender male) questionnaire. The STOP-BANG has a high sensitivity for predicting moderate-to-severe (87.0%) and severe (70.4%) sleep-disordered breathing.²⁴ More than 3 affirmative answers indicate a high risk for sleep-disordered breathing and is cause for ordering a sleep study.

CPAP Group Class

Patients with a diagnosis of sleep apnea subsequently receive their CPAP machines when they attend a 2-hour group class taught by a respiratory therapist. Group education sessions increase the chance of issuing more machines and providing better education.²⁵ One study found that “attendance in a group clinic designed to encourage compliance with CPAP therapy provided a simple and effective means of improving treatment of OSA.”²⁵

In class, the respiratory therapist briefly assesses each patient’s CPAP prescription, describes the patient’s type of sleep apnea and final diagnosis, and reviews the CPAP machine’s features. Veterans are then instructed to take their CPAP machines home to use all night, every night for 4 weeks. All night is defined as a period of 7.5 to 8 hours, as population-based study results have shown that sleep of this duration is associated with lowest cardiovascular morbidity and mortality. After the initial 4-plus weeks of machine use, patients with all their CPAP equipment are seen in the sleep clinic.

First Sleep Clinic Follow-Up Visit

At first follow-up, patients are asked for a subjective evaluation of their sleep. Most state they are “better” with PAP therapy. Each patient’s mask is checked and refitted with the patient’s prescribed pressure.

Patients are informed of their PAP settings and requirements from the sleep study and told their particular “magic pressure.” Patients understand that a person’s magic pressure, determined in the laboratory, is the pressure of room air blown into the nose, mouth, or both that eliminates not only snoring, but also partial and complete airway obstructions (hypopneas, apneas). Patients are asked to remember their particular magic pressure and their AHI and told their OSA status (mild, moderate, or severe) as assessed by the laboratory study.²⁶ Extensive education on sleep apnea and treatment are also addressed. Education and training are among the most important tenets of PAP therapy, and these are incorporated into all encounters.^25,26

PAP Data Report and Leak

The CPAP data are downloaded and printed. If adherence is suboptimal, clinician and patient discuss increasing adherence and possibly becoming a super user. The patient receives a copy of the report, which can be compared with the patient’s adherence statistics and with the adherence statistics of similar patients who are super users. A few blacked-out names are posted on the board in front of the provider’s computer station. Patients can thus easily see that attaining super-user status is very difficult but possible. Some patients maximize their therapy and are designated PAP super users. These patients are proud to receive this designation, and they strive to keep it.

Data downloads are crucial for adherence. In a recent study, the American Thoracic Society stated, “Providers need to be able to interpret adherence systems.”²⁷

The clinic provides a summary report on each patient’s adherence. A provider interpretation is added, and the report is copied into the Computer Patient Record System.

After the report is downloaded, the provider checks for correct pressure and then for a large leak. A large leak is an unintentional leak (the total amount that leaks but not including leak from the mask) > 5% of the night. A leak of > 15 minutes was added to the super-user criteria, because some software provides the average time of a large leak per day in minutes.²⁸ Many veterans sleep only 4 to 5 hours nightly (300 minutes × 5% = 15 minutes). Therefore, the leak should not be more than 5% or 15 minutes for a veteran sleeping 5 hours.

The machine indicates a percentage of leak on the patient self-check LED screen for adherence. There is no standardized leak criterion used by all flow-generator manufacturers. Every mask has venting designed to leak intentionally so that the patient does not rebreathe air CO₂. The main concern is unintentional leaks above the intentional leak or venting threshold.

The ResMed CPAP (ResMed Corp, San Diego, CA) maximum intentional leak is 24 L/min.²⁹ Above that level is large leak. The exact leak amount varies by interface (mask) based on pressure and mask type.^2,12

The larger the interface surface area, the larger the leak. Unintentional leak is higher with the full-face mask than with the nasal mask, most likely because there is more opportunity for leakage with the larger surface area of the full-face mask. Nasal pillows seem to leak less because of their smaller surface area, but more studies on mask interfaces are needed to validate this finding.

Chin Strap

Adding a chin strap improved patient adherence, nightly duration of use, residual AHI, and leak in patients with sleep apnea.³⁰ Other investigators reported reduced OSA, confirmed by polysomnography and nasopharyngolaryngoscopy, with use of only a chin strap.³¹ When a nasal mask with chin strap is used, the strap should be made to fit properly over the chin, not on the throat. Properly used chin straps significantly reduce leakage and residual AHI.³⁰

A chin strap most likely reduces large leak and dry mouth.³⁰ Dry mouth can result from mouth leak, which is commonly caused by nasal congestion or high pressure and mouth breathing. The nasal turbinates help humidify, warm, and cool the air. Heated humidification of PAP can help prevent dry mouth.

Asking the Right Questions

The clinician should ask several key questions at the first follow-up: How is it going with your PAP machine? Do you feel PAP therapy is helping you sleep? Do you feel better with PAP therapy? To a patient who states he or she is not doing well with therapy, the clinician should ask, What type of problems are you having? In many cases, poor adherence is attributable to a large leak from a poorly fitting mask. A large leak can also increase residual AHI and cause frequent arousals.³⁰

Some machines cannot maintain the pressure of a large leak and will shut off and trigger an alarm that wakes the patient to readjust the mask. This situation causes some patients to discontinue CPAP/BPAP use. The mask leak must be adjusted. Another common complaint is morning dry mouth. This extreme dryness—a significant clue pointing to mouth leak caused in part by the mouth dropping open during sleep with PAP—should be addressed by fitting the patient with a chin strap.³⁰ Dry mouth also can be caused by low humidity; increasing the humidity setting usually resolves the problem. However, as one study found, use of controlled heated humidification did not improve adherence or quality of life.³² In the same study, the nasopharyngeal dryness that resulted from CPAP therapy without humidification was reduced immediately and during the first weeks of treatment.All current PAP machines feature heated humidification.

Mouth breathing can also result from nasal congestion, allergic or vasomotor rhinitis, nasal turbinate hypertrophy, obstruction from a deviated septum, polyps, or air hunger/insufficient PAP pressure. Chronic rhinosinusitis is a problem that affects up to 12.5% of the U.S. population.³³

Adherence is also increased with the elimination of leak and associated arousals. Patients are shown how to use their PAP machine’s heated humidity settings to obtain desired comfort levels. The clinician explains that the nasal turbinates heat and cool the air and that they can become swollen and irritated with PAP therapy. A heated hose may be prescribed to provide optimal humidification without condensation or water dripping into the hose (rainout).

A full-face mask is used only when the patient cannot breathe out the nose adequately or when PAP becomes too high. A 2013 study found no significant differences among ResMed, Respironics, and Fisher & Paykel CPAP interfaces (Fisher & Paykel Healthcare, Irvine, CA).³⁴ The clinician determines which mask is comfortable for a patient and tries to stay with that mask for that patient.

Adherence Report

A therapy data summary is downloaded and reviewed with the patient.²⁸ A pattern of use report that shows daily use with times over the month is also reviewed.²⁸ The software’s sleep therapy long-term trend report lists important statistics. The adherence data summary and the CPAP summary are also reviewed (Table 2).²⁸ This page is printed and given to patients to reieiw their progress. For some it represents a reward for using the CPAP/BPAP machine as well as a congratulatory note.

In the Example 1 summary download (Table 2), a patient used a PAP machine 4 hours or more on 93.3% of the 30 days the machine was used.²⁸ Residual AHI was low, 2.1, and there was no appreciable leak. The PAP of 11.2 cm H₂O was in the 90th percentile. The patient was fixed to 12 cm H₂O with expiratory pressure relief (EPR) of 1. The EPR is a comfort feature that reduces pressure from 1 cm H₂O to 3 cm H₂O to make it easier for the patient to exhale. (A flow generator that produces EPR of > 3 cm H₂O is a BPAP machine.)

This patient was not a super user. Overall use was low—5 hours, 28 minutes—which could indicate behaviorally insufficient sleep syndrome. Sleep time is controversial, but the National Sleep Foundation recommends 7 to 9 hours of sleep per night.

A different patient used a PAP machine 4 hours or more on 100% (28/28) of the days when the machine was used (Table 3).²⁹ Residual AHI was low (0.6), median use was 8 hours, 47 minutes, and there was no appreciable leak. The patient was using autoset mode with a minimum pressure of 13 cm H₂O and maximum pressure of 18 cm H₂O. The 95th percentile pressure was 13.6 cm H₂O. The patient’s pressure was changed to 14 cm H₂O with EPR of 3. This patient was a super user.

Sleep Hygiene Discussion

Providers must discuss sleep hygiene (good sleep habits) with veterans. If needed, AASM pamphlets on sleep hygiene and other educational materials can be provided. The bedroom should be cool, comfortable, quiet, and dark and should not include a television or computer. Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration and tells the brain it is time to wake up.³⁴

Patients are asked about the number of arousals they have per night. At first follow-up, providers must determine what is causing a patient to arouse while on CPAP/BPAP therapy. Some causes are air leak resulting in unresolved OSA, nocturia (may be triggered by unresolved OSA), dry mouth (indicating need for chin strap), nightmares (suggestive of unresolved OSA in REM sleep), posttraumatic stress disorder (PTSD), environmental noise, and claustrophobia. The provider should have thought-out answers to these problems in advance.

Epworth Sleepiness Scale

The Epworth Sleepiness Scale (ESS) is administered as part of the baseline comprehensive examination and at every sleep clinic follow-up after issuing a CPAP/BPAP machine.³⁵ The first evaluation after the machine is issued should show a reduction in ESS. No reduction in ESS indicates that a problem needs to be addressed. The most common reason for insufficient reduction in ESS is suboptimal PAP therapy adherence, usually because of a large leak. Some cases of poor adherence may be attributable to restless legs syndrome, periodic limb movement disorder, chronic musculoskeletal pain, and sleep fragmentation caused by alcohol, smoking, caffeine, or cocaine. Excessive daytime sleepiness may persist from use of pain medications or other sedating medications. One study found a correlation between sleep duration with CPAP therapy and reduction in ESS.³⁶ In addition to administering the ESS, patients are asked how they doing with PAP therapy, and the answer is documented. Treatment changes are made if needed to reduce excessive daytime sleepiness.

Ear-Nose-Throat Examination

A quick look into the nose with a nasal speculum is a crucial component of a thorough examination. The clinician looks for a deviated septum, swollen turbinates, obstruction, polyps, bleeding, infection, septal perforation, and discharge. In addition, the patient is checked for airflow amount, nasal congestion, and obstruction; if necessary a nasal steroid spray or a nasal saline spray is prescribed. In some cases, saline spray can be added to the steroid spray to help reduce or eliminate nasal congestion.³⁷

Treatment of congestion requires education, as many patients improperly use these sprays. The steroid spray is not an instant vasoconstrictor; a week of regular use is needed to reduce inflammation and congestion. Saline spray and saline irrigation can be used as a treatment adjunct for symptoms of chronic rhinosinusitis.³⁷If the steroid and saline sprays fail after a 2-month trial, consider an ear-nose-throat (ENT) consultation. A recent study found that adherence rates increased after septoplasty in patients with nasal obstruction.³⁸ The throat is examined for macroglossia or scalloping of the tongue.³⁹ Macroglossic Mallampati IV tongues are platterlike. They are big, long, and wide and often have impressions or scalloping along the outside from a molding of the teeth. The patient is shown a Mallampati diagram and given a Mallampati score.

Creating a Sense of Mission

The sleep physician assistant (PA)at the Detroit VAMC is a retired U.S. Army colonel who ensures that the language the physician uses aligns with the language veterans use. Behavioral techniques are used to create a common culture that helps overcome obstacles—allowing patients to understand the benefits of and need for full CPAP/BPAP therapy adherence. One technique reinforces their sense of mission accomplishment, their military pride, and their interservice rivalry to increase adherence. The mission with each patient is to “work until success is achieved...but the patient can’t quit.” The mantra given to a patient with a difficult case is, “We will not let you fail with CPAP/BPAP therapy,” which echoes a familiar military motto, “We will not leave you behind.” Also, the goal of the physician is: Never give up on the patient.

Behavioral and Psychological Principles

The behavioral and psychological principles for success with PAP super users should be studied to validate better outcomes with longer duration PAP machine use. Patients who are motivated to succeed and to participate in their care can make great strides in changing their behavior to get more and better sleep. Obese patients can get referrals to the MOVE! weight loss program. Some veterans simply follow instructions, pay attention to detail, and do what they are told regarding sleep, PAP education, and good sleep hygiene. Many veterans have poor sleep hygiene and insomnia because they watch television or play games on electronic devices right before bedtime. Many patients develop behaviorally insufficient sleep syndrome. Their behavior prevents them from going to bed at a time that will allow sufficient sleep. Some veterans smoke or drink caffeinated beverages or al cohol immediately before sleep time and then wonder why they have insomnia.

Veterans with insomnia may be referred to the insomnia clinic psychologist for cognitive behavioral therapy for insomnia.⁴⁰ Referral to this psychologist can be very helpful in the treatment of insomnia after the patient’s OSA has been treated. Veterans are encouraged to follow good sleep hygiene principles and permanently discontinue detrimental sleep behaviors.

For veterans with PTSD, imagery rehearsal before sleep has been effective in resolving disturbing nightmares and excluding their violent details.⁴¹ Clinicians recommend that these veterans rehearse a pleasant dream before sleep time. Cartwright and Lamberg performed extensive research on dreams and nightmares, and their book may provide insight into reducing nightmares for veterans with severe PTSD.⁴² Persistent nightmares associated with PTSD also can be reduced with use of prazosin. ⁴³

Sleep Clinic Economics

The economic impact of OSA is substantial because of increased risk of cardiovascular disease and risk of motor vehicle accidents and decreased quality of life and productivity. Results of cost-effectiveness analyses support the value of diagnosing and treating OSA. Studies have provided estimates from a payer perspective, ranging from $2,000 to $11,000 per quality-adjusted life year over 5 years for treating moderate-to-severe OSA. The Sleep Heart Health Study showed that OSA was associated with an 18% increase in predicted health care utilization based on medication use.^44,45 Moreover, CPAP therapy was found to be clinically more effective than no treatment: Therapy increased life expectancy in males and females, and effective treatment of OSA was associated with lower health care and disability costs and fewer missed workdays.

The authors’ initiatives to improve PAP therapy adherence required adding a PA and a registered respiratory therapist (RT) to the staff of 2 full-time equivalent (FTE) board-certified sleep physicians. The sleep physicians trained the PA to initiate and complete all the recommendations described, and the PA attended an AASM-sponsored review course for additional training. The PA is responsible for performing comprehensive face-to-face clinical evaluations in 4 half-day clinic sessions each week, as well as providing follow-up care in 4 additional half-day clinic sessions each week.

During these sessions, the PA provides education about sleep apnea and treatment. Thirty-minute follow-up clinic appointments are reserved for downloading CPAP data, providing interpretation, and educating patients to maximize PAP therapy and become super users. The remaining clinic sessions are run by 3 sleep fellows under the supervision of the sleep physicians. During all visits, providers encourage patients to maintain good sleep hygiene. Nonadherent patients are scheduled to be seen in a separate clinic session during which the RT troubleshoots and corrects PAP machine and mask-related problems.

Setting up the CPAP group classes and follow-up clinics required adding an FTE RT at a cost of $44,000 to $48,000 per year. By recruiting an FTE PA starting at GS-12 and $75,542 instead of another board-certified sleep physician, VAMC Detroit was able to provide increased access to patient care (8 clinics) at sizable financial savings (estimate, $75,000/y). A 0.5 FTE clinical psychologist provided cognitive behavioral therapy for insomnia and PAP therapy nonadherence and helped achieve the initiative’s goals.

The sleep center projects that the overall cost-effectiveness of these initiatives in terms of admission rates, life expectancy, and productivity would not be dissimilar to that reported in the peer-reviewed literature, as noted earlier. The center’s upcoming research projects will provide more data specific to its population. Educating patients requires that only motivated providers give patients instructions during a 30-minute follow-up clinic visit—there is no additional expense. This model of intensive care can be adopted at other VAMCs.

Conclusion

Maximizing PAP machine use is a unique approach that stimulates veterans to attain the highest level of adherence. This approach is based on clinical observation and patient encounters, and treatment recommendations over 8 years.

Showing enthusiasm with patients is crucial. Enthusiasm is contagious. Clinicians who are also PAP machine users should let patients know of their PAP super-user status and add that many others have attained this status, too. The benefits of optimal treatment are reviewed with patients: increased energy, lower risk of cardiovascular disease, lower blood pressure, better insulin sensitivity, and overall reduced mortality. Some patients have difficulty using the nasal mask and chin strap and understanding and adhering to PAP therapy. These impediments can be overcome with further education and follow-up. Sleep clinic clinicians take the time to show patients how to use the machine’s self-adherence check and leak functions. Patients can then monitor their progress daily.

To motivate patients, clinicians should set expectations early, invest time in providing education at follow-up; be diligent with respect to mask fitting and download evaluation. Sleep clinic providers should also speak the veterans’ language, create a self-fulfilling prophesy for success, and schedule a follow-up sleep clinic appointment if a patient is not fulfilling the Medicare adherence criterion of 4 hours’ nightly use for 70% of nights over 30 days.

PAP therapy coaching and persistent education with provider contact and enthusiasm can improve adherence. Encouragement and praise can help patients exceed Medicare’s minimum PAP therapy criterion and improve their overall PAP experience. The sleep team should tell patients they are proud of their accomplishments with such a difficult treatment. Being genuine and caring and showing concern about their evaluation, treatment, and follow-up is important. This helps reduce their OSA-related morbidity, lessen their depression, and improves their daily well-being and quality of life.

“The variation in responses to CPAP and acceptance of CPAP suggest that focused interventions, rather than one-size-fits-all interventions, may have a greater effect on the overall outcome of CPAP adherence,” wrote Weaver and Sawyer.⁴⁶

Finally, one cannot equate spending on veteran care with spending in other areas of the national budget. The real cost of not giving veterans appropriate care will be a loss of trust, given that the overarching mission is “to care for him who shall have borne the battle and for his widow and his orphan.” 

Adherence to positive airway pressure (PAP) therapy is a difficult patient management issue. Clinicians at the John D. Dingell VA Medical Center in Detroit (VAMC Detroit) developed the O’Brien criteria and extensive patient education materials to increase patient adherence. The importance of PAP therapy and the reasons veterans should sleep with a PAP machine for 7 to 9 hours each night are stressed (many sleep only 4 to 5 hours). Several recent studies have confirmed widely varying PAP therapy adherence rates (30%-84%).^1-13 A majority of patients indicated that mask discomfort is the primary reason for nonadherence.¹

Adherence is affected by many factors, including heated humidity, patient education, mask type, and type of PAP machine (eg, continuous PAP [CPAP] vs bilevel PAP [BPAP]; auto-PAP vs CPAP). Other factors, such as race and economic status, also affect adherence.¹⁴ The Wisconsin Sleep Cohort Study found that patients with moderate-to-severe untreated obstructive sleep apnea (OSA) were 4 to 5 times more likely to die of a cardiovascular event and 3 times more likely to die of any cause.¹⁵ The morbidity and mortality associated with severe untreated OSA led the clinicians to intensify treatment efforts.¹⁶In this article, the authors summarize the initiative at the VAMC Detroit to enhance PAP therapy adherence in patients with sleep apnea. The goal was to motivate patients to maximize PAP machine use. This article is a guide that federal health care providers and their civilian counterparts in the private sector can use to maximize PAP machine use. Working toward that goal, a set of PAP “super user” criteria was developed and used to create a 5-point method for encouraging patients to maximize adherence to PAP therapy.

Background

Positive airway pressure is the room air pressure, measured in centimeters of H₂O, which splints open the airway to prevent snoring, apneas, and hypopneas. An apnea is a 90%-plus airway obstruction that lasts longer than 10 seconds and is seen with sleep study polysomnography. A hypopnea is a 30%-plus airway obstruction that lasts longer than 10 seconds and is accompanied by a 3% drop in pulse oximetry (SpO₂).

A CPAP device delivers pressure continuously through a medical air compressor or flow generator called a PAP machine. The BPAP machine has separate inspiratory pressure and expiratory pressure. Auto-PAP machines give minimum pressure and maximum pressure usually between the range of 4 cm H₂O to 20 cm H₂O. This machine finds the user’s median pressure (90th percentile) and maximum pressure and averages pressure over a specified period of use. The auto-PAP can then be set to CPAP mode and the pressure fixed or set to the 90th percentile.

O’Brien Criteria

The O’Brien criteria for PAP super-user status (Table 1) were developed for maximizing PAP machine use and presented at the 2013 John D. Dingell Sleep and Wake Disorders Center Symposium. There is no other published reference or criteria proposed for maximizing PAP machine adherence. A recent study on sleep time criteria suggested that a higher percentage of patients achieved normal functioning with longer duration nightly CPAP therapy, which is in line with the authors’ recommended PAP machine use duration.¹⁷

Positive airway pressure therapy is eligible for insurance reimbursement by Medicare and third-party payers for adult patients who have OSA and achieve 4 hours of nightly use for 70% of nights over 30 days. Coverage for CPAP therapy is initially limited to 12 weeks during which beneficiaries with an OSA diagnosis can be identified and any therapy benefits documented. Subsequent CPAP therapy is covered only for those OSA patients who benefit during the 12-week period.¹⁸At VAMC Detroit, the data covering the previous 30 days of use is downloaded. Medicare allows for the best 30-day period out of the 12-week window. The hospital, along with Harper Hospital and the Detroit Medical Centers in conjunction with the Wayne State University sleep program, is an Academic Center of Distinction, which follows the sleep guidelines and practice parameters for Medicare, third-party insurance companies, and the American Academy of Sleep Medicine.

The sleep clinic clinicians follow the clinical guidelines for evaluation, management, and long-term care of adults with OSA.^19,20 Follow-up visits are scheduled and made on a consultation basis up to 90 days for the required download or as necessary for PAP therapy. In this initiative, practitioners offer veteran-specific patient care with PAP therapy that exceeds Medicare guidelines. The success of this process yielded a growing cohort of PAP super users at VAMC Detroit. These patients exceed the Medicare criterion of 4 hours of nightly use for 70% of nights over 30 days. Thus, 4 hours of nightly use for 100% of nights over the same period was proposed as another criterion.

The super-user criteria, which provide motivation to reach the top, stimulate many patients to achieve the Medicare criteria. All 5 criteria must be satisfied to attain super-user status, and becoming a super user is not easy. In fact, the expectation is that, if an adherence data study is conducted, it will show that only a small percentage of all users meet the criteria. Maximum adherence is expected to be the tail (3%-4%) of a bell-shaped curve.

PAP Super-User Status

At the initial evaluation, practitioners create a self-fulfilling prophecy that, as first described by Merton, sets expectations.²¹ A self-fulfilling prophecy is a prediction that directly or indirectly causes the prediction to become true as a result of the positive feedback between belief and behavior.²¹ The personnel at VAMC Detroit sleep clinic set a tone that enables patients to meet and exceed the Medicare sleep guidelines and their expectations. Patients are encouraged to make it their personal mission to achieve the goal of becoming a PAP super user. The patients receive the O’Brien criteria for PAP super-user status—guidelines thought to contribute to higher quality of life.

The Medicare criterion emphasized is the minimum required for full adherence. The goal is to reduce sleepiness and increase well-being. The literature shows that increasing duration of sleep results in lower daytime sleepiness.²² Inadequate sleep has many detrimental effects. According to a recent study, insufficient sleep contributes to weight gain.²² Desired patient outcomes are increased sleep time without arousals, increased slow-wave sleep (SWS), consolidation of memories and rapid eye movement (REM), and improvement in emotional and procedural skill memories.²³ Patients are informed that using a PAP machine for 7 to 9 hours can reduce excessive daytime sleepiness and allow for more SWS and REM sleep, which help improve memory, judgment, and concentration. Many other studies have shown how 7 to 9 hours of sleep benefit adults. Thus, 7 to 9 hours became the criterion for maximizing PAP sleep time.

Initial Evaluation and Sleep Study

A primary care provider can enroll a patient into the clinic for a sleep study by requesting an evaluation. The consultation is then triaged using the STOP-BANG (Snoring, Tiredness, Observed apnea, high blood Pressure–Body mass index > 35, Age > 50, Neck circumference > 40 cm, Gender male) questionnaire. The STOP-BANG has a high sensitivity for predicting moderate-to-severe (87.0%) and severe (70.4%) sleep-disordered breathing.²⁴ More than 3 affirmative answers indicate a high risk for sleep-disordered breathing and is cause for ordering a sleep study.

CPAP Group Class

Patients with a diagnosis of sleep apnea subsequently receive their CPAP machines when they attend a 2-hour group class taught by a respiratory therapist. Group education sessions increase the chance of issuing more machines and providing better education.²⁵ One study found that “attendance in a group clinic designed to encourage compliance with CPAP therapy provided a simple and effective means of improving treatment of OSA.”²⁵

In class, the respiratory therapist briefly assesses each patient’s CPAP prescription, describes the patient’s type of sleep apnea and final diagnosis, and reviews the CPAP machine’s features. Veterans are then instructed to take their CPAP machines home to use all night, every night for 4 weeks. All night is defined as a period of 7.5 to 8 hours, as population-based study results have shown that sleep of this duration is associated with lowest cardiovascular morbidity and mortality. After the initial 4-plus weeks of machine use, patients with all their CPAP equipment are seen in the sleep clinic.

First Sleep Clinic Follow-Up Visit

At first follow-up, patients are asked for a subjective evaluation of their sleep. Most state they are “better” with PAP therapy. Each patient’s mask is checked and refitted with the patient’s prescribed pressure.

Patients are informed of their PAP settings and requirements from the sleep study and told their particular “magic pressure.” Patients understand that a person’s magic pressure, determined in the laboratory, is the pressure of room air blown into the nose, mouth, or both that eliminates not only snoring, but also partial and complete airway obstructions (hypopneas, apneas). Patients are asked to remember their particular magic pressure and their AHI and told their OSA status (mild, moderate, or severe) as assessed by the laboratory study.²⁶ Extensive education on sleep apnea and treatment are also addressed. Education and training are among the most important tenets of PAP therapy, and these are incorporated into all encounters.^25,26

PAP Data Report and Leak

The CPAP data are downloaded and printed. If adherence is suboptimal, clinician and patient discuss increasing adherence and possibly becoming a super user. The patient receives a copy of the report, which can be compared with the patient’s adherence statistics and with the adherence statistics of similar patients who are super users. A few blacked-out names are posted on the board in front of the provider’s computer station. Patients can thus easily see that attaining super-user status is very difficult but possible. Some patients maximize their therapy and are designated PAP super users. These patients are proud to receive this designation, and they strive to keep it.

Data downloads are crucial for adherence. In a recent study, the American Thoracic Society stated, “Providers need to be able to interpret adherence systems.”²⁷

The clinic provides a summary report on each patient’s adherence. A provider interpretation is added, and the report is copied into the Computer Patient Record System.

After the report is downloaded, the provider checks for correct pressure and then for a large leak. A large leak is an unintentional leak (the total amount that leaks but not including leak from the mask) > 5% of the night. A leak of > 15 minutes was added to the super-user criteria, because some software provides the average time of a large leak per day in minutes.²⁸ Many veterans sleep only 4 to 5 hours nightly (300 minutes × 5% = 15 minutes). Therefore, the leak should not be more than 5% or 15 minutes for a veteran sleeping 5 hours.

The machine indicates a percentage of leak on the patient self-check LED screen for adherence. There is no standardized leak criterion used by all flow-generator manufacturers. Every mask has venting designed to leak intentionally so that the patient does not rebreathe air CO₂. The main concern is unintentional leaks above the intentional leak or venting threshold.

The ResMed CPAP (ResMed Corp, San Diego, CA) maximum intentional leak is 24 L/min.²⁹ Above that level is large leak. The exact leak amount varies by interface (mask) based on pressure and mask type.^2,12

The larger the interface surface area, the larger the leak. Unintentional leak is higher with the full-face mask than with the nasal mask, most likely because there is more opportunity for leakage with the larger surface area of the full-face mask. Nasal pillows seem to leak less because of their smaller surface area, but more studies on mask interfaces are needed to validate this finding.

Chin Strap

Adding a chin strap improved patient adherence, nightly duration of use, residual AHI, and leak in patients with sleep apnea.³⁰ Other investigators reported reduced OSA, confirmed by polysomnography and nasopharyngolaryngoscopy, with use of only a chin strap.³¹ When a nasal mask with chin strap is used, the strap should be made to fit properly over the chin, not on the throat. Properly used chin straps significantly reduce leakage and residual AHI.³⁰

A chin strap most likely reduces large leak and dry mouth.³⁰ Dry mouth can result from mouth leak, which is commonly caused by nasal congestion or high pressure and mouth breathing. The nasal turbinates help humidify, warm, and cool the air. Heated humidification of PAP can help prevent dry mouth.

Asking the Right Questions

The clinician should ask several key questions at the first follow-up: How is it going with your PAP machine? Do you feel PAP therapy is helping you sleep? Do you feel better with PAP therapy? To a patient who states he or she is not doing well with therapy, the clinician should ask, What type of problems are you having? In many cases, poor adherence is attributable to a large leak from a poorly fitting mask. A large leak can also increase residual AHI and cause frequent arousals.³⁰

Some machines cannot maintain the pressure of a large leak and will shut off and trigger an alarm that wakes the patient to readjust the mask. This situation causes some patients to discontinue CPAP/BPAP use. The mask leak must be adjusted. Another common complaint is morning dry mouth. This extreme dryness—a significant clue pointing to mouth leak caused in part by the mouth dropping open during sleep with PAP—should be addressed by fitting the patient with a chin strap.³⁰ Dry mouth also can be caused by low humidity; increasing the humidity setting usually resolves the problem. However, as one study found, use of controlled heated humidification did not improve adherence or quality of life.³² In the same study, the nasopharyngeal dryness that resulted from CPAP therapy without humidification was reduced immediately and during the first weeks of treatment.All current PAP machines feature heated humidification.

Mouth breathing can also result from nasal congestion, allergic or vasomotor rhinitis, nasal turbinate hypertrophy, obstruction from a deviated septum, polyps, or air hunger/insufficient PAP pressure. Chronic rhinosinusitis is a problem that affects up to 12.5% of the U.S. population.³³

Adherence is also increased with the elimination of leak and associated arousals. Patients are shown how to use their PAP machine’s heated humidity settings to obtain desired comfort levels. The clinician explains that the nasal turbinates heat and cool the air and that they can become swollen and irritated with PAP therapy. A heated hose may be prescribed to provide optimal humidification without condensation or water dripping into the hose (rainout).

A full-face mask is used only when the patient cannot breathe out the nose adequately or when PAP becomes too high. A 2013 study found no significant differences among ResMed, Respironics, and Fisher & Paykel CPAP interfaces (Fisher & Paykel Healthcare, Irvine, CA).³⁴ The clinician determines which mask is comfortable for a patient and tries to stay with that mask for that patient.

Adherence Report

A therapy data summary is downloaded and reviewed with the patient.²⁸ A pattern of use report that shows daily use with times over the month is also reviewed.²⁸ The software’s sleep therapy long-term trend report lists important statistics. The adherence data summary and the CPAP summary are also reviewed (Table 2).²⁸ This page is printed and given to patients to reieiw their progress. For some it represents a reward for using the CPAP/BPAP machine as well as a congratulatory note.

In the Example 1 summary download (Table 2), a patient used a PAP machine 4 hours or more on 93.3% of the 30 days the machine was used.²⁸ Residual AHI was low, 2.1, and there was no appreciable leak. The PAP of 11.2 cm H₂O was in the 90th percentile. The patient was fixed to 12 cm H₂O with expiratory pressure relief (EPR) of 1. The EPR is a comfort feature that reduces pressure from 1 cm H₂O to 3 cm H₂O to make it easier for the patient to exhale. (A flow generator that produces EPR of > 3 cm H₂O is a BPAP machine.)

This patient was not a super user. Overall use was low—5 hours, 28 minutes—which could indicate behaviorally insufficient sleep syndrome. Sleep time is controversial, but the National Sleep Foundation recommends 7 to 9 hours of sleep per night.

A different patient used a PAP machine 4 hours or more on 100% (28/28) of the days when the machine was used (Table 3).²⁹ Residual AHI was low (0.6), median use was 8 hours, 47 minutes, and there was no appreciable leak. The patient was using autoset mode with a minimum pressure of 13 cm H₂O and maximum pressure of 18 cm H₂O. The 95th percentile pressure was 13.6 cm H₂O. The patient’s pressure was changed to 14 cm H₂O with EPR of 3. This patient was a super user.

Sleep Hygiene Discussion

Providers must discuss sleep hygiene (good sleep habits) with veterans. If needed, AASM pamphlets on sleep hygiene and other educational materials can be provided. The bedroom should be cool, comfortable, quiet, and dark and should not include a television or computer. Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration and tells the brain it is time to wake up.³⁴

Patients are asked about the number of arousals they have per night. At first follow-up, providers must determine what is causing a patient to arouse while on CPAP/BPAP therapy. Some causes are air leak resulting in unresolved OSA, nocturia (may be triggered by unresolved OSA), dry mouth (indicating need for chin strap), nightmares (suggestive of unresolved OSA in REM sleep), posttraumatic stress disorder (PTSD), environmental noise, and claustrophobia. The provider should have thought-out answers to these problems in advance.

Epworth Sleepiness Scale

The Epworth Sleepiness Scale (ESS) is administered as part of the baseline comprehensive examination and at every sleep clinic follow-up after issuing a CPAP/BPAP machine.³⁵ The first evaluation after the machine is issued should show a reduction in ESS. No reduction in ESS indicates that a problem needs to be addressed. The most common reason for insufficient reduction in ESS is suboptimal PAP therapy adherence, usually because of a large leak. Some cases of poor adherence may be attributable to restless legs syndrome, periodic limb movement disorder, chronic musculoskeletal pain, and sleep fragmentation caused by alcohol, smoking, caffeine, or cocaine. Excessive daytime sleepiness may persist from use of pain medications or other sedating medications. One study found a correlation between sleep duration with CPAP therapy and reduction in ESS.³⁶ In addition to administering the ESS, patients are asked how they doing with PAP therapy, and the answer is documented. Treatment changes are made if needed to reduce excessive daytime sleepiness.

Ear-Nose-Throat Examination

A quick look into the nose with a nasal speculum is a crucial component of a thorough examination. The clinician looks for a deviated septum, swollen turbinates, obstruction, polyps, bleeding, infection, septal perforation, and discharge. In addition, the patient is checked for airflow amount, nasal congestion, and obstruction; if necessary a nasal steroid spray or a nasal saline spray is prescribed. In some cases, saline spray can be added to the steroid spray to help reduce or eliminate nasal congestion.³⁷

Treatment of congestion requires education, as many patients improperly use these sprays. The steroid spray is not an instant vasoconstrictor; a week of regular use is needed to reduce inflammation and congestion. Saline spray and saline irrigation can be used as a treatment adjunct for symptoms of chronic rhinosinusitis.³⁷If the steroid and saline sprays fail after a 2-month trial, consider an ear-nose-throat (ENT) consultation. A recent study found that adherence rates increased after septoplasty in patients with nasal obstruction.³⁸ The throat is examined for macroglossia or scalloping of the tongue.³⁹ Macroglossic Mallampati IV tongues are platterlike. They are big, long, and wide and often have impressions or scalloping along the outside from a molding of the teeth. The patient is shown a Mallampati diagram and given a Mallampati score.

Creating a Sense of Mission

The sleep physician assistant (PA)at the Detroit VAMC is a retired U.S. Army colonel who ensures that the language the physician uses aligns with the language veterans use. Behavioral techniques are used to create a common culture that helps overcome obstacles—allowing patients to understand the benefits of and need for full CPAP/BPAP therapy adherence. One technique reinforces their sense of mission accomplishment, their military pride, and their interservice rivalry to increase adherence. The mission with each patient is to “work until success is achieved...but the patient can’t quit.” The mantra given to a patient with a difficult case is, “We will not let you fail with CPAP/BPAP therapy,” which echoes a familiar military motto, “We will not leave you behind.” Also, the goal of the physician is: Never give up on the patient.

Behavioral and Psychological Principles

The behavioral and psychological principles for success with PAP super users should be studied to validate better outcomes with longer duration PAP machine use. Patients who are motivated to succeed and to participate in their care can make great strides in changing their behavior to get more and better sleep. Obese patients can get referrals to the MOVE! weight loss program. Some veterans simply follow instructions, pay attention to detail, and do what they are told regarding sleep, PAP education, and good sleep hygiene. Many veterans have poor sleep hygiene and insomnia because they watch television or play games on electronic devices right before bedtime. Many patients develop behaviorally insufficient sleep syndrome. Their behavior prevents them from going to bed at a time that will allow sufficient sleep. Some veterans smoke or drink caffeinated beverages or al cohol immediately before sleep time and then wonder why they have insomnia.

Veterans with insomnia may be referred to the insomnia clinic psychologist for cognitive behavioral therapy for insomnia.⁴⁰ Referral to this psychologist can be very helpful in the treatment of insomnia after the patient’s OSA has been treated. Veterans are encouraged to follow good sleep hygiene principles and permanently discontinue detrimental sleep behaviors.

For veterans with PTSD, imagery rehearsal before sleep has been effective in resolving disturbing nightmares and excluding their violent details.⁴¹ Clinicians recommend that these veterans rehearse a pleasant dream before sleep time. Cartwright and Lamberg performed extensive research on dreams and nightmares, and their book may provide insight into reducing nightmares for veterans with severe PTSD.⁴² Persistent nightmares associated with PTSD also can be reduced with use of prazosin. ⁴³

Sleep Clinic Economics

The economic impact of OSA is substantial because of increased risk of cardiovascular disease and risk of motor vehicle accidents and decreased quality of life and productivity. Results of cost-effectiveness analyses support the value of diagnosing and treating OSA. Studies have provided estimates from a payer perspective, ranging from $2,000 to $11,000 per quality-adjusted life year over 5 years for treating moderate-to-severe OSA. The Sleep Heart Health Study showed that OSA was associated with an 18% increase in predicted health care utilization based on medication use.^44,45 Moreover, CPAP therapy was found to be clinically more effective than no treatment: Therapy increased life expectancy in males and females, and effective treatment of OSA was associated with lower health care and disability costs and fewer missed workdays.

The authors’ initiatives to improve PAP therapy adherence required adding a PA and a registered respiratory therapist (RT) to the staff of 2 full-time equivalent (FTE) board-certified sleep physicians. The sleep physicians trained the PA to initiate and complete all the recommendations described, and the PA attended an AASM-sponsored review course for additional training. The PA is responsible for performing comprehensive face-to-face clinical evaluations in 4 half-day clinic sessions each week, as well as providing follow-up care in 4 additional half-day clinic sessions each week.

During these sessions, the PA provides education about sleep apnea and treatment. Thirty-minute follow-up clinic appointments are reserved for downloading CPAP data, providing interpretation, and educating patients to maximize PAP therapy and become super users. The remaining clinic sessions are run by 3 sleep fellows under the supervision of the sleep physicians. During all visits, providers encourage patients to maintain good sleep hygiene. Nonadherent patients are scheduled to be seen in a separate clinic session during which the RT troubleshoots and corrects PAP machine and mask-related problems.

Setting up the CPAP group classes and follow-up clinics required adding an FTE RT at a cost of $44,000 to $48,000 per year. By recruiting an FTE PA starting at GS-12 and $75,542 instead of another board-certified sleep physician, VAMC Detroit was able to provide increased access to patient care (8 clinics) at sizable financial savings (estimate, $75,000/y). A 0.5 FTE clinical psychologist provided cognitive behavioral therapy for insomnia and PAP therapy nonadherence and helped achieve the initiative’s goals.

The sleep center projects that the overall cost-effectiveness of these initiatives in terms of admission rates, life expectancy, and productivity would not be dissimilar to that reported in the peer-reviewed literature, as noted earlier. The center’s upcoming research projects will provide more data specific to its population. Educating patients requires that only motivated providers give patients instructions during a 30-minute follow-up clinic visit—there is no additional expense. This model of intensive care can be adopted at other VAMCs.

Conclusion

Maximizing PAP machine use is a unique approach that stimulates veterans to attain the highest level of adherence. This approach is based on clinical observation and patient encounters, and treatment recommendations over 8 years.

Showing enthusiasm with patients is crucial. Enthusiasm is contagious. Clinicians who are also PAP machine users should let patients know of their PAP super-user status and add that many others have attained this status, too. The benefits of optimal treatment are reviewed with patients: increased energy, lower risk of cardiovascular disease, lower blood pressure, better insulin sensitivity, and overall reduced mortality. Some patients have difficulty using the nasal mask and chin strap and understanding and adhering to PAP therapy. These impediments can be overcome with further education and follow-up. Sleep clinic clinicians take the time to show patients how to use the machine’s self-adherence check and leak functions. Patients can then monitor their progress daily.

To motivate patients, clinicians should set expectations early, invest time in providing education at follow-up; be diligent with respect to mask fitting and download evaluation. Sleep clinic providers should also speak the veterans’ language, create a self-fulfilling prophesy for success, and schedule a follow-up sleep clinic appointment if a patient is not fulfilling the Medicare adherence criterion of 4 hours’ nightly use for 70% of nights over 30 days.

PAP therapy coaching and persistent education with provider contact and enthusiasm can improve adherence. Encouragement and praise can help patients exceed Medicare’s minimum PAP therapy criterion and improve their overall PAP experience. The sleep team should tell patients they are proud of their accomplishments with such a difficult treatment. Being genuine and caring and showing concern about their evaluation, treatment, and follow-up is important. This helps reduce their OSA-related morbidity, lessen their depression, and improves their daily well-being and quality of life.

“The variation in responses to CPAP and acceptance of CPAP suggest that focused interventions, rather than one-size-fits-all interventions, may have a greater effect on the overall outcome of CPAP adherence,” wrote Weaver and Sawyer.⁴⁶

Finally, one cannot equate spending on veteran care with spending in other areas of the national budget. The real cost of not giving veterans appropriate care will be a loss of trust, given that the overarching mission is “to care for him who shall have borne the battle and for his widow and his orphan.” 

Adherence to positive airway pressure (PAP) therapy is a difficult patient management issue. Clinicians at the John D. Dingell VA Medical Center in Detroit (VAMC Detroit) developed the O’Brien criteria and extensive patient education materials to increase patient adherence. The importance of PAP therapy and the reasons veterans should sleep with a PAP machine for 7 to 9 hours each night are stressed (many sleep only 4 to 5 hours). Several recent studies have confirmed widely varying PAP therapy adherence rates (30%-84%).^1-13 A majority of patients indicated that mask discomfort is the primary reason for nonadherence.¹

Adherence is affected by many factors, including heated humidity, patient education, mask type, and type of PAP machine (eg, continuous PAP [CPAP] vs bilevel PAP [BPAP]; auto-PAP vs CPAP). Other factors, such as race and economic status, also affect adherence.¹⁴ The Wisconsin Sleep Cohort Study found that patients with moderate-to-severe untreated obstructive sleep apnea (OSA) were 4 to 5 times more likely to die of a cardiovascular event and 3 times more likely to die of any cause.¹⁵ The morbidity and mortality associated with severe untreated OSA led the clinicians to intensify treatment efforts.¹⁶In this article, the authors summarize the initiative at the VAMC Detroit to enhance PAP therapy adherence in patients with sleep apnea. The goal was to motivate patients to maximize PAP machine use. This article is a guide that federal health care providers and their civilian counterparts in the private sector can use to maximize PAP machine use. Working toward that goal, a set of PAP “super user” criteria was developed and used to create a 5-point method for encouraging patients to maximize adherence to PAP therapy.

Background

Positive airway pressure is the room air pressure, measured in centimeters of H₂O, which splints open the airway to prevent snoring, apneas, and hypopneas. An apnea is a 90%-plus airway obstruction that lasts longer than 10 seconds and is seen with sleep study polysomnography. A hypopnea is a 30%-plus airway obstruction that lasts longer than 10 seconds and is accompanied by a 3% drop in pulse oximetry (SpO₂).

A CPAP device delivers pressure continuously through a medical air compressor or flow generator called a PAP machine. The BPAP machine has separate inspiratory pressure and expiratory pressure. Auto-PAP machines give minimum pressure and maximum pressure usually between the range of 4 cm H₂O to 20 cm H₂O. This machine finds the user’s median pressure (90th percentile) and maximum pressure and averages pressure over a specified period of use. The auto-PAP can then be set to CPAP mode and the pressure fixed or set to the 90th percentile.

O’Brien Criteria

The O’Brien criteria for PAP super-user status (Table 1) were developed for maximizing PAP machine use and presented at the 2013 John D. Dingell Sleep and Wake Disorders Center Symposium. There is no other published reference or criteria proposed for maximizing PAP machine adherence. A recent study on sleep time criteria suggested that a higher percentage of patients achieved normal functioning with longer duration nightly CPAP therapy, which is in line with the authors’ recommended PAP machine use duration.¹⁷

Positive airway pressure therapy is eligible for insurance reimbursement by Medicare and third-party payers for adult patients who have OSA and achieve 4 hours of nightly use for 70% of nights over 30 days. Coverage for CPAP therapy is initially limited to 12 weeks during which beneficiaries with an OSA diagnosis can be identified and any therapy benefits documented. Subsequent CPAP therapy is covered only for those OSA patients who benefit during the 12-week period.¹⁸At VAMC Detroit, the data covering the previous 30 days of use is downloaded. Medicare allows for the best 30-day period out of the 12-week window. The hospital, along with Harper Hospital and the Detroit Medical Centers in conjunction with the Wayne State University sleep program, is an Academic Center of Distinction, which follows the sleep guidelines and practice parameters for Medicare, third-party insurance companies, and the American Academy of Sleep Medicine.

The sleep clinic clinicians follow the clinical guidelines for evaluation, management, and long-term care of adults with OSA.^19,20 Follow-up visits are scheduled and made on a consultation basis up to 90 days for the required download or as necessary for PAP therapy. In this initiative, practitioners offer veteran-specific patient care with PAP therapy that exceeds Medicare guidelines. The success of this process yielded a growing cohort of PAP super users at VAMC Detroit. These patients exceed the Medicare criterion of 4 hours of nightly use for 70% of nights over 30 days. Thus, 4 hours of nightly use for 100% of nights over the same period was proposed as another criterion.

The super-user criteria, which provide motivation to reach the top, stimulate many patients to achieve the Medicare criteria. All 5 criteria must be satisfied to attain super-user status, and becoming a super user is not easy. In fact, the expectation is that, if an adherence data study is conducted, it will show that only a small percentage of all users meet the criteria. Maximum adherence is expected to be the tail (3%-4%) of a bell-shaped curve.

PAP Super-User Status

At the initial evaluation, practitioners create a self-fulfilling prophecy that, as first described by Merton, sets expectations.²¹ A self-fulfilling prophecy is a prediction that directly or indirectly causes the prediction to become true as a result of the positive feedback between belief and behavior.²¹ The personnel at VAMC Detroit sleep clinic set a tone that enables patients to meet and exceed the Medicare sleep guidelines and their expectations. Patients are encouraged to make it their personal mission to achieve the goal of becoming a PAP super user. The patients receive the O’Brien criteria for PAP super-user status—guidelines thought to contribute to higher quality of life.

The Medicare criterion emphasized is the minimum required for full adherence. The goal is to reduce sleepiness and increase well-being. The literature shows that increasing duration of sleep results in lower daytime sleepiness.²² Inadequate sleep has many detrimental effects. According to a recent study, insufficient sleep contributes to weight gain.²² Desired patient outcomes are increased sleep time without arousals, increased slow-wave sleep (SWS), consolidation of memories and rapid eye movement (REM), and improvement in emotional and procedural skill memories.²³ Patients are informed that using a PAP machine for 7 to 9 hours can reduce excessive daytime sleepiness and allow for more SWS and REM sleep, which help improve memory, judgment, and concentration. Many other studies have shown how 7 to 9 hours of sleep benefit adults. Thus, 7 to 9 hours became the criterion for maximizing PAP sleep time.

Initial Evaluation and Sleep Study

A primary care provider can enroll a patient into the clinic for a sleep study by requesting an evaluation. The consultation is then triaged using the STOP-BANG (Snoring, Tiredness, Observed apnea, high blood Pressure–Body mass index > 35, Age > 50, Neck circumference > 40 cm, Gender male) questionnaire. The STOP-BANG has a high sensitivity for predicting moderate-to-severe (87.0%) and severe (70.4%) sleep-disordered breathing.²⁴ More than 3 affirmative answers indicate a high risk for sleep-disordered breathing and is cause for ordering a sleep study.

CPAP Group Class

Patients with a diagnosis of sleep apnea subsequently receive their CPAP machines when they attend a 2-hour group class taught by a respiratory therapist. Group education sessions increase the chance of issuing more machines and providing better education.²⁵ One study found that “attendance in a group clinic designed to encourage compliance with CPAP therapy provided a simple and effective means of improving treatment of OSA.”²⁵

In class, the respiratory therapist briefly assesses each patient’s CPAP prescription, describes the patient’s type of sleep apnea and final diagnosis, and reviews the CPAP machine’s features. Veterans are then instructed to take their CPAP machines home to use all night, every night for 4 weeks. All night is defined as a period of 7.5 to 8 hours, as population-based study results have shown that sleep of this duration is associated with lowest cardiovascular morbidity and mortality. After the initial 4-plus weeks of machine use, patients with all their CPAP equipment are seen in the sleep clinic.

First Sleep Clinic Follow-Up Visit

At first follow-up, patients are asked for a subjective evaluation of their sleep. Most state they are “better” with PAP therapy. Each patient’s mask is checked and refitted with the patient’s prescribed pressure.

Patients are informed of their PAP settings and requirements from the sleep study and told their particular “magic pressure.” Patients understand that a person’s magic pressure, determined in the laboratory, is the pressure of room air blown into the nose, mouth, or both that eliminates not only snoring, but also partial and complete airway obstructions (hypopneas, apneas). Patients are asked to remember their particular magic pressure and their AHI and told their OSA status (mild, moderate, or severe) as assessed by the laboratory study.²⁶ Extensive education on sleep apnea and treatment are also addressed. Education and training are among the most important tenets of PAP therapy, and these are incorporated into all encounters.^25,26

PAP Data Report and Leak

The CPAP data are downloaded and printed. If adherence is suboptimal, clinician and patient discuss increasing adherence and possibly becoming a super user. The patient receives a copy of the report, which can be compared with the patient’s adherence statistics and with the adherence statistics of similar patients who are super users. A few blacked-out names are posted on the board in front of the provider’s computer station. Patients can thus easily see that attaining super-user status is very difficult but possible. Some patients maximize their therapy and are designated PAP super users. These patients are proud to receive this designation, and they strive to keep it.

Data downloads are crucial for adherence. In a recent study, the American Thoracic Society stated, “Providers need to be able to interpret adherence systems.”²⁷

The clinic provides a summary report on each patient’s adherence. A provider interpretation is added, and the report is copied into the Computer Patient Record System.

After the report is downloaded, the provider checks for correct pressure and then for a large leak. A large leak is an unintentional leak (the total amount that leaks but not including leak from the mask) > 5% of the night. A leak of > 15 minutes was added to the super-user criteria, because some software provides the average time of a large leak per day in minutes.²⁸ Many veterans sleep only 4 to 5 hours nightly (300 minutes × 5% = 15 minutes). Therefore, the leak should not be more than 5% or 15 minutes for a veteran sleeping 5 hours.

The machine indicates a percentage of leak on the patient self-check LED screen for adherence. There is no standardized leak criterion used by all flow-generator manufacturers. Every mask has venting designed to leak intentionally so that the patient does not rebreathe air CO₂. The main concern is unintentional leaks above the intentional leak or venting threshold.

The ResMed CPAP (ResMed Corp, San Diego, CA) maximum intentional leak is 24 L/min.²⁹ Above that level is large leak. The exact leak amount varies by interface (mask) based on pressure and mask type.^2,12

The larger the interface surface area, the larger the leak. Unintentional leak is higher with the full-face mask than with the nasal mask, most likely because there is more opportunity for leakage with the larger surface area of the full-face mask. Nasal pillows seem to leak less because of their smaller surface area, but more studies on mask interfaces are needed to validate this finding.

Chin Strap

Adding a chin strap improved patient adherence, nightly duration of use, residual AHI, and leak in patients with sleep apnea.³⁰ Other investigators reported reduced OSA, confirmed by polysomnography and nasopharyngolaryngoscopy, with use of only a chin strap.³¹ When a nasal mask with chin strap is used, the strap should be made to fit properly over the chin, not on the throat. Properly used chin straps significantly reduce leakage and residual AHI.³⁰

A chin strap most likely reduces large leak and dry mouth.³⁰ Dry mouth can result from mouth leak, which is commonly caused by nasal congestion or high pressure and mouth breathing. The nasal turbinates help humidify, warm, and cool the air. Heated humidification of PAP can help prevent dry mouth.

Asking the Right Questions

The clinician should ask several key questions at the first follow-up: How is it going with your PAP machine? Do you feel PAP therapy is helping you sleep? Do you feel better with PAP therapy? To a patient who states he or she is not doing well with therapy, the clinician should ask, What type of problems are you having? In many cases, poor adherence is attributable to a large leak from a poorly fitting mask. A large leak can also increase residual AHI and cause frequent arousals.³⁰

Some machines cannot maintain the pressure of a large leak and will shut off and trigger an alarm that wakes the patient to readjust the mask. This situation causes some patients to discontinue CPAP/BPAP use. The mask leak must be adjusted. Another common complaint is morning dry mouth. This extreme dryness—a significant clue pointing to mouth leak caused in part by the mouth dropping open during sleep with PAP—should be addressed by fitting the patient with a chin strap.³⁰ Dry mouth also can be caused by low humidity; increasing the humidity setting usually resolves the problem. However, as one study found, use of controlled heated humidification did not improve adherence or quality of life.³² In the same study, the nasopharyngeal dryness that resulted from CPAP therapy without humidification was reduced immediately and during the first weeks of treatment.All current PAP machines feature heated humidification.

Mouth breathing can also result from nasal congestion, allergic or vasomotor rhinitis, nasal turbinate hypertrophy, obstruction from a deviated septum, polyps, or air hunger/insufficient PAP pressure. Chronic rhinosinusitis is a problem that affects up to 12.5% of the U.S. population.³³

Adherence is also increased with the elimination of leak and associated arousals. Patients are shown how to use their PAP machine’s heated humidity settings to obtain desired comfort levels. The clinician explains that the nasal turbinates heat and cool the air and that they can become swollen and irritated with PAP therapy. A heated hose may be prescribed to provide optimal humidification without condensation or water dripping into the hose (rainout).

A full-face mask is used only when the patient cannot breathe out the nose adequately or when PAP becomes too high. A 2013 study found no significant differences among ResMed, Respironics, and Fisher & Paykel CPAP interfaces (Fisher & Paykel Healthcare, Irvine, CA).³⁴ The clinician determines which mask is comfortable for a patient and tries to stay with that mask for that patient.

Adherence Report

A therapy data summary is downloaded and reviewed with the patient.²⁸ A pattern of use report that shows daily use with times over the month is also reviewed.²⁸ The software’s sleep therapy long-term trend report lists important statistics. The adherence data summary and the CPAP summary are also reviewed (Table 2).²⁸ This page is printed and given to patients to reieiw their progress. For some it represents a reward for using the CPAP/BPAP machine as well as a congratulatory note.

In the Example 1 summary download (Table 2), a patient used a PAP machine 4 hours or more on 93.3% of the 30 days the machine was used.²⁸ Residual AHI was low, 2.1, and there was no appreciable leak. The PAP of 11.2 cm H₂O was in the 90th percentile. The patient was fixed to 12 cm H₂O with expiratory pressure relief (EPR) of 1. The EPR is a comfort feature that reduces pressure from 1 cm H₂O to 3 cm H₂O to make it easier for the patient to exhale. (A flow generator that produces EPR of > 3 cm H₂O is a BPAP machine.)

This patient was not a super user. Overall use was low—5 hours, 28 minutes—which could indicate behaviorally insufficient sleep syndrome. Sleep time is controversial, but the National Sleep Foundation recommends 7 to 9 hours of sleep per night.

A different patient used a PAP machine 4 hours or more on 100% (28/28) of the days when the machine was used (Table 3).²⁹ Residual AHI was low (0.6), median use was 8 hours, 47 minutes, and there was no appreciable leak. The patient was using autoset mode with a minimum pressure of 13 cm H₂O and maximum pressure of 18 cm H₂O. The 95th percentile pressure was 13.6 cm H₂O. The patient’s pressure was changed to 14 cm H₂O with EPR of 3. This patient was a super user.

Sleep Hygiene Discussion

Providers must discuss sleep hygiene (good sleep habits) with veterans. If needed, AASM pamphlets on sleep hygiene and other educational materials can be provided. The bedroom should be cool, comfortable, quiet, and dark and should not include a television or computer. Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration and tells the brain it is time to wake up.³⁴

Patients are asked about the number of arousals they have per night. At first follow-up, providers must determine what is causing a patient to arouse while on CPAP/BPAP therapy. Some causes are air leak resulting in unresolved OSA, nocturia (may be triggered by unresolved OSA), dry mouth (indicating need for chin strap), nightmares (suggestive of unresolved OSA in REM sleep), posttraumatic stress disorder (PTSD), environmental noise, and claustrophobia. The provider should have thought-out answers to these problems in advance.

Epworth Sleepiness Scale

The Epworth Sleepiness Scale (ESS) is administered as part of the baseline comprehensive examination and at every sleep clinic follow-up after issuing a CPAP/BPAP machine.³⁵ The first evaluation after the machine is issued should show a reduction in ESS. No reduction in ESS indicates that a problem needs to be addressed. The most common reason for insufficient reduction in ESS is suboptimal PAP therapy adherence, usually because of a large leak. Some cases of poor adherence may be attributable to restless legs syndrome, periodic limb movement disorder, chronic musculoskeletal pain, and sleep fragmentation caused by alcohol, smoking, caffeine, or cocaine. Excessive daytime sleepiness may persist from use of pain medications or other sedating medications. One study found a correlation between sleep duration with CPAP therapy and reduction in ESS.³⁶ In addition to administering the ESS, patients are asked how they doing with PAP therapy, and the answer is documented. Treatment changes are made if needed to reduce excessive daytime sleepiness.

Ear-Nose-Throat Examination

A quick look into the nose with a nasal speculum is a crucial component of a thorough examination. The clinician looks for a deviated septum, swollen turbinates, obstruction, polyps, bleeding, infection, septal perforation, and discharge. In addition, the patient is checked for airflow amount, nasal congestion, and obstruction; if necessary a nasal steroid spray or a nasal saline spray is prescribed. In some cases, saline spray can be added to the steroid spray to help reduce or eliminate nasal congestion.³⁷

Treatment of congestion requires education, as many patients improperly use these sprays. The steroid spray is not an instant vasoconstrictor; a week of regular use is needed to reduce inflammation and congestion. Saline spray and saline irrigation can be used as a treatment adjunct for symptoms of chronic rhinosinusitis.³⁷If the steroid and saline sprays fail after a 2-month trial, consider an ear-nose-throat (ENT) consultation. A recent study found that adherence rates increased after septoplasty in patients with nasal obstruction.³⁸ The throat is examined for macroglossia or scalloping of the tongue.³⁹ Macroglossic Mallampati IV tongues are platterlike. They are big, long, and wide and often have impressions or scalloping along the outside from a molding of the teeth. The patient is shown a Mallampati diagram and given a Mallampati score.

Creating a Sense of Mission

The sleep physician assistant (PA)at the Detroit VAMC is a retired U.S. Army colonel who ensures that the language the physician uses aligns with the language veterans use. Behavioral techniques are used to create a common culture that helps overcome obstacles—allowing patients to understand the benefits of and need for full CPAP/BPAP therapy adherence. One technique reinforces their sense of mission accomplishment, their military pride, and their interservice rivalry to increase adherence. The mission with each patient is to “work until success is achieved...but the patient can’t quit.” The mantra given to a patient with a difficult case is, “We will not let you fail with CPAP/BPAP therapy,” which echoes a familiar military motto, “We will not leave you behind.” Also, the goal of the physician is: Never give up on the patient.

Behavioral and Psychological Principles

The behavioral and psychological principles for success with PAP super users should be studied to validate better outcomes with longer duration PAP machine use. Patients who are motivated to succeed and to participate in their care can make great strides in changing their behavior to get more and better sleep. Obese patients can get referrals to the MOVE! weight loss program. Some veterans simply follow instructions, pay attention to detail, and do what they are told regarding sleep, PAP education, and good sleep hygiene. Many veterans have poor sleep hygiene and insomnia because they watch television or play games on electronic devices right before bedtime. Many patients develop behaviorally insufficient sleep syndrome. Their behavior prevents them from going to bed at a time that will allow sufficient sleep. Some veterans smoke or drink caffeinated beverages or al cohol immediately before sleep time and then wonder why they have insomnia.

Veterans with insomnia may be referred to the insomnia clinic psychologist for cognitive behavioral therapy for insomnia.⁴⁰ Referral to this psychologist can be very helpful in the treatment of insomnia after the patient’s OSA has been treated. Veterans are encouraged to follow good sleep hygiene principles and permanently discontinue detrimental sleep behaviors.

For veterans with PTSD, imagery rehearsal before sleep has been effective in resolving disturbing nightmares and excluding their violent details.⁴¹ Clinicians recommend that these veterans rehearse a pleasant dream before sleep time. Cartwright and Lamberg performed extensive research on dreams and nightmares, and their book may provide insight into reducing nightmares for veterans with severe PTSD.⁴² Persistent nightmares associated with PTSD also can be reduced with use of prazosin. ⁴³

Sleep Clinic Economics

The economic impact of OSA is substantial because of increased risk of cardiovascular disease and risk of motor vehicle accidents and decreased quality of life and productivity. Results of cost-effectiveness analyses support the value of diagnosing and treating OSA. Studies have provided estimates from a payer perspective, ranging from $2,000 to $11,000 per quality-adjusted life year over 5 years for treating moderate-to-severe OSA. The Sleep Heart Health Study showed that OSA was associated with an 18% increase in predicted health care utilization based on medication use.^44,45 Moreover, CPAP therapy was found to be clinically more effective than no treatment: Therapy increased life expectancy in males and females, and effective treatment of OSA was associated with lower health care and disability costs and fewer missed workdays.

The authors’ initiatives to improve PAP therapy adherence required adding a PA and a registered respiratory therapist (RT) to the staff of 2 full-time equivalent (FTE) board-certified sleep physicians. The sleep physicians trained the PA to initiate and complete all the recommendations described, and the PA attended an AASM-sponsored review course for additional training. The PA is responsible for performing comprehensive face-to-face clinical evaluations in 4 half-day clinic sessions each week, as well as providing follow-up care in 4 additional half-day clinic sessions each week.

During these sessions, the PA provides education about sleep apnea and treatment. Thirty-minute follow-up clinic appointments are reserved for downloading CPAP data, providing interpretation, and educating patients to maximize PAP therapy and become super users. The remaining clinic sessions are run by 3 sleep fellows under the supervision of the sleep physicians. During all visits, providers encourage patients to maintain good sleep hygiene. Nonadherent patients are scheduled to be seen in a separate clinic session during which the RT troubleshoots and corrects PAP machine and mask-related problems.

Setting up the CPAP group classes and follow-up clinics required adding an FTE RT at a cost of $44,000 to $48,000 per year. By recruiting an FTE PA starting at GS-12 and $75,542 instead of another board-certified sleep physician, VAMC Detroit was able to provide increased access to patient care (8 clinics) at sizable financial savings (estimate, $75,000/y). A 0.5 FTE clinical psychologist provided cognitive behavioral therapy for insomnia and PAP therapy nonadherence and helped achieve the initiative’s goals.

The sleep center projects that the overall cost-effectiveness of these initiatives in terms of admission rates, life expectancy, and productivity would not be dissimilar to that reported in the peer-reviewed literature, as noted earlier. The center’s upcoming research projects will provide more data specific to its population. Educating patients requires that only motivated providers give patients instructions during a 30-minute follow-up clinic visit—there is no additional expense. This model of intensive care can be adopted at other VAMCs.

Conclusion

Maximizing PAP machine use is a unique approach that stimulates veterans to attain the highest level of adherence. This approach is based on clinical observation and patient encounters, and treatment recommendations over 8 years.

Showing enthusiasm with patients is crucial. Enthusiasm is contagious. Clinicians who are also PAP machine users should let patients know of their PAP super-user status and add that many others have attained this status, too. The benefits of optimal treatment are reviewed with patients: increased energy, lower risk of cardiovascular disease, lower blood pressure, better insulin sensitivity, and overall reduced mortality. Some patients have difficulty using the nasal mask and chin strap and understanding and adhering to PAP therapy. These impediments can be overcome with further education and follow-up. Sleep clinic clinicians take the time to show patients how to use the machine’s self-adherence check and leak functions. Patients can then monitor their progress daily.

To motivate patients, clinicians should set expectations early, invest time in providing education at follow-up; be diligent with respect to mask fitting and download evaluation. Sleep clinic providers should also speak the veterans’ language, create a self-fulfilling prophesy for success, and schedule a follow-up sleep clinic appointment if a patient is not fulfilling the Medicare adherence criterion of 4 hours’ nightly use for 70% of nights over 30 days.

PAP therapy coaching and persistent education with provider contact and enthusiasm can improve adherence. Encouragement and praise can help patients exceed Medicare’s minimum PAP therapy criterion and improve their overall PAP experience. The sleep team should tell patients they are proud of their accomplishments with such a difficult treatment. Being genuine and caring and showing concern about their evaluation, treatment, and follow-up is important. This helps reduce their OSA-related morbidity, lessen their depression, and improves their daily well-being and quality of life.

“The variation in responses to CPAP and acceptance of CPAP suggest that focused interventions, rather than one-size-fits-all interventions, may have a greater effect on the overall outcome of CPAP adherence,” wrote Weaver and Sawyer.⁴⁶

Finally, one cannot equate spending on veteran care with spending in other areas of the national budget. The real cost of not giving veterans appropriate care will be a loss of trust, given that the overarching mission is “to care for him who shall have borne the battle and for his widow and his orphan.” 

Complete atrioventricular (AV) block can occur due to structural or functional causes. Common structural etiologies include sclerodegenerative disease of the conduction system, ischemic heart disease in the acute or chronic setting, infiltrative myocardial disease, congenital heart disease, and cardiac surgery. Reversible etiologies of complete AV block include drug overdose and electrolyte abnormalities. In the following case study, the authors present a rare case of complete AV block caused by severe hypercalcemia related to malignancy that completely normalized after treatment of the hypercalcemia.

Case Report

A 63-year-old African-American man with metastatic carcinoma of the lungs (Figure 1) with unknown primary cancer was found to have a serum calcium level of 17.5 mg/dL (reference range:8.4-10.2 mg/dL) on routine preoperative laboratory testing prior to placement of a surgical port for chemotherapy. The patient also was noted to have a slow heart rate, and his electrocardiogram revealed a third-degree AV block with an escape rhythm at 29 bpm with a prolonged corrected QT (QTc) of 556 ms (Figure 2).

Although the patient reported nonspecific symptoms of fatigue, anorexia, dysphagia, and weight loss for 3 months, there were no new symptoms of dizziness, chest discomfort, or syncope. His past medical history included hypertension, hyperlipidemia, chronic kidney disease, obstructive sleep apnea, and the recently discovered bilateral lung metastasis. The patient reported no prior history of cardiac arrhythmias, coronary artery disease, or structural heart defects. His outpatient medications included aspirin, amlodipine, bupropion, hydralazine, and simvastatin.

At the physical examination the patient was cachectic but in no apparent distress. His heart rate escape rhythm was 29 bpm, with no murmurs and mildly reduced breath sounds. The patient’s blood pressure was 110/70. After correction for albumin, the serum calcium level was 17.8 mg/dL; ionized calcium level was 8.6 mg/dL; parathyroid hormone was 7.6 pg/mL (normal range, 12-88 pg/mL); parathyroid hormone-related protein was 6.4 pmol/L (normal range, < 2.0 pmol/L); potassium was 3.4 mmol/L (normal range, 3.5 – 5.1 mmol/L); and magnesium was 2.01 mg/dL. The patient’s thyroid stimulating hormone level was normal, and serial cardiac enzymes stayed within the reference range.

The patient was admitted to a cardiac care unit. A temporary transvenous pacemaker was placed, and the hypercalcemia was treated with aggressive fluid hydration, calcitonin, and zoledronic acid. Serum calcium gradually decreased to 14.6 mg/dL the following day and 9.6 mg/dL the subsequent day. The normalization of calcium resulted in resolution of complete heart block (Figure 3). The patient did not experience recurrence of AV nodal dysfunction and eventually died 3 months later due to his advanced metastatic disease.

Discussion

The reported cardiovascular effects of hypercalcemia include hypertension, arrhythmias, increased myocardial contractility at serum calcium level below 15 mg/dL, and myocardial depression above that level. Electrocardiographic manifestations of hypercalcemia include a shortened ST segment leading to a short corrected QT interval (QTc), slight increase in T wave duration, and rarely, Osborn waves or J waves.^1-3 However, its influence on the AV node is less clear.

One small study assessed the prevalence of cardiac arrhythmias and conduction disturbances in 20 patients with hyperparathyroidism and moderate hypercalcemia and found no increase in the frequency of arrhythmias or high grade AV block.⁴

There are reports of conduction abnormality secondary to experimentally induced hypercalcemia in the literature. Hoff and colleagues described findings of AV block generated by the injection of IV calcium in dogs.⁵ In 2 human subjects, sinus bradycardia was precipitated after they received IV infusion of calcium gluconate.⁶ Shah and colleagues described 2 patients with sinus node dysfunction attributed to hypercalcemia secondary to hyperparathyroidism.⁷

Case reports of AV nodal dysfunction provoked by hypercalcemia have primarily occurred in the setting of primary hyperparathyroidism.^8,9 Milk-alkali syndrome and vitamin D related hypercalcemia also have been reported to cause complete heart block.^10,11 Reports of malignancy-related hypercalcemia causing conduction abnormalities are rare. The authors also found one case report of marked sinus bradycardia due to hypercalcemia related to breast cancer.¹²The case study presented in this report is rare because the patient developed complete AV block due to malignancy-related hypercalcemia that resolved completely with resolution of hypercalcemia. The prolongation of the QTc interval was another unique electrocardiographic change observed in this case. Calcium levels are inversely proportional to the QTc interval, and hypercalcemia is typically associated with a shortened QTc interval. However, this patient had a prolonged QTc without any other clear-cut cause. His hypokalemia was of a mild degree and not severe enough to produce such a long QTc interval. A possible explanation of QTc prolongation may be an increase in the T wave width associated with a serum calcium level above 16 mg/dL.

The pathophysiology of hypercalcemia-induced AV nodal conduction system disease is unknown. Calcium deposition in AV nodes of elderly patients has been associated with paroxysmal 2:1 AV block.⁸ It could be postulated that elevated serum calcium levels predispose to calcium deposition in cardiac conduction tissue, leading to progressive dysfunction. Although this theory may be applicable in a chronic setting, the mechanism in an acute setting likely relates to elevated serum levels of calcium that causes an alteration in electrochemical gradients. These elevated serum levels also increase intracellular calcium. This rise may result in increased calmodulin activation on the intracellular portion of the myocyte cell membrane and consequent enhanced sodium channel activation, which may then inhibit AV nodal conduction.¹³

Conclusion

Physicians should be aware that severe hypercalcemia can cause significant conduction system alterations, including complete AV block. A short QTc interval is typical, but a prolonged QTc interval also may be seen. While temporary support with a transvenous pacemaker may be needed, the conduction system abnormality is expected to resolve by treatment of the underlying hypercalcemia.

Complete atrioventricular (AV) block can occur due to structural or functional causes. Common structural etiologies include sclerodegenerative disease of the conduction system, ischemic heart disease in the acute or chronic setting, infiltrative myocardial disease, congenital heart disease, and cardiac surgery. Reversible etiologies of complete AV block include drug overdose and electrolyte abnormalities. In the following case study, the authors present a rare case of complete AV block caused by severe hypercalcemia related to malignancy that completely normalized after treatment of the hypercalcemia.

Case Report

A 63-year-old African-American man with metastatic carcinoma of the lungs (Figure 1) with unknown primary cancer was found to have a serum calcium level of 17.5 mg/dL (reference range:8.4-10.2 mg/dL) on routine preoperative laboratory testing prior to placement of a surgical port for chemotherapy. The patient also was noted to have a slow heart rate, and his electrocardiogram revealed a third-degree AV block with an escape rhythm at 29 bpm with a prolonged corrected QT (QTc) of 556 ms (Figure 2).

Although the patient reported nonspecific symptoms of fatigue, anorexia, dysphagia, and weight loss for 3 months, there were no new symptoms of dizziness, chest discomfort, or syncope. His past medical history included hypertension, hyperlipidemia, chronic kidney disease, obstructive sleep apnea, and the recently discovered bilateral lung metastasis. The patient reported no prior history of cardiac arrhythmias, coronary artery disease, or structural heart defects. His outpatient medications included aspirin, amlodipine, bupropion, hydralazine, and simvastatin.

At the physical examination the patient was cachectic but in no apparent distress. His heart rate escape rhythm was 29 bpm, with no murmurs and mildly reduced breath sounds. The patient’s blood pressure was 110/70. After correction for albumin, the serum calcium level was 17.8 mg/dL; ionized calcium level was 8.6 mg/dL; parathyroid hormone was 7.6 pg/mL (normal range, 12-88 pg/mL); parathyroid hormone-related protein was 6.4 pmol/L (normal range, < 2.0 pmol/L); potassium was 3.4 mmol/L (normal range, 3.5 – 5.1 mmol/L); and magnesium was 2.01 mg/dL. The patient’s thyroid stimulating hormone level was normal, and serial cardiac enzymes stayed within the reference range.

The patient was admitted to a cardiac care unit. A temporary transvenous pacemaker was placed, and the hypercalcemia was treated with aggressive fluid hydration, calcitonin, and zoledronic acid. Serum calcium gradually decreased to 14.6 mg/dL the following day and 9.6 mg/dL the subsequent day. The normalization of calcium resulted in resolution of complete heart block (Figure 3). The patient did not experience recurrence of AV nodal dysfunction and eventually died 3 months later due to his advanced metastatic disease.

Discussion

The reported cardiovascular effects of hypercalcemia include hypertension, arrhythmias, increased myocardial contractility at serum calcium level below 15 mg/dL, and myocardial depression above that level. Electrocardiographic manifestations of hypercalcemia include a shortened ST segment leading to a short corrected QT interval (QTc), slight increase in T wave duration, and rarely, Osborn waves or J waves.^1-3 However, its influence on the AV node is less clear.

One small study assessed the prevalence of cardiac arrhythmias and conduction disturbances in 20 patients with hyperparathyroidism and moderate hypercalcemia and found no increase in the frequency of arrhythmias or high grade AV block.⁴

There are reports of conduction abnormality secondary to experimentally induced hypercalcemia in the literature. Hoff and colleagues described findings of AV block generated by the injection of IV calcium in dogs.⁵ In 2 human subjects, sinus bradycardia was precipitated after they received IV infusion of calcium gluconate.⁶ Shah and colleagues described 2 patients with sinus node dysfunction attributed to hypercalcemia secondary to hyperparathyroidism.⁷

Case reports of AV nodal dysfunction provoked by hypercalcemia have primarily occurred in the setting of primary hyperparathyroidism.^8,9 Milk-alkali syndrome and vitamin D related hypercalcemia also have been reported to cause complete heart block.^10,11 Reports of malignancy-related hypercalcemia causing conduction abnormalities are rare. The authors also found one case report of marked sinus bradycardia due to hypercalcemia related to breast cancer.¹²The case study presented in this report is rare because the patient developed complete AV block due to malignancy-related hypercalcemia that resolved completely with resolution of hypercalcemia. The prolongation of the QTc interval was another unique electrocardiographic change observed in this case. Calcium levels are inversely proportional to the QTc interval, and hypercalcemia is typically associated with a shortened QTc interval. However, this patient had a prolonged QTc without any other clear-cut cause. His hypokalemia was of a mild degree and not severe enough to produce such a long QTc interval. A possible explanation of QTc prolongation may be an increase in the T wave width associated with a serum calcium level above 16 mg/dL.

The pathophysiology of hypercalcemia-induced AV nodal conduction system disease is unknown. Calcium deposition in AV nodes of elderly patients has been associated with paroxysmal 2:1 AV block.⁸ It could be postulated that elevated serum calcium levels predispose to calcium deposition in cardiac conduction tissue, leading to progressive dysfunction. Although this theory may be applicable in a chronic setting, the mechanism in an acute setting likely relates to elevated serum levels of calcium that causes an alteration in electrochemical gradients. These elevated serum levels also increase intracellular calcium. This rise may result in increased calmodulin activation on the intracellular portion of the myocyte cell membrane and consequent enhanced sodium channel activation, which may then inhibit AV nodal conduction.¹³

Conclusion

Physicians should be aware that severe hypercalcemia can cause significant conduction system alterations, including complete AV block. A short QTc interval is typical, but a prolonged QTc interval also may be seen. While temporary support with a transvenous pacemaker may be needed, the conduction system abnormality is expected to resolve by treatment of the underlying hypercalcemia.

Complete atrioventricular (AV) block can occur due to structural or functional causes. Common structural etiologies include sclerodegenerative disease of the conduction system, ischemic heart disease in the acute or chronic setting, infiltrative myocardial disease, congenital heart disease, and cardiac surgery. Reversible etiologies of complete AV block include drug overdose and electrolyte abnormalities. In the following case study, the authors present a rare case of complete AV block caused by severe hypercalcemia related to malignancy that completely normalized after treatment of the hypercalcemia.

Case Report

A 63-year-old African-American man with metastatic carcinoma of the lungs (Figure 1) with unknown primary cancer was found to have a serum calcium level of 17.5 mg/dL (reference range:8.4-10.2 mg/dL) on routine preoperative laboratory testing prior to placement of a surgical port for chemotherapy. The patient also was noted to have a slow heart rate, and his electrocardiogram revealed a third-degree AV block with an escape rhythm at 29 bpm with a prolonged corrected QT (QTc) of 556 ms (Figure 2).

Although the patient reported nonspecific symptoms of fatigue, anorexia, dysphagia, and weight loss for 3 months, there were no new symptoms of dizziness, chest discomfort, or syncope. His past medical history included hypertension, hyperlipidemia, chronic kidney disease, obstructive sleep apnea, and the recently discovered bilateral lung metastasis. The patient reported no prior history of cardiac arrhythmias, coronary artery disease, or structural heart defects. His outpatient medications included aspirin, amlodipine, bupropion, hydralazine, and simvastatin.

At the physical examination the patient was cachectic but in no apparent distress. His heart rate escape rhythm was 29 bpm, with no murmurs and mildly reduced breath sounds. The patient’s blood pressure was 110/70. After correction for albumin, the serum calcium level was 17.8 mg/dL; ionized calcium level was 8.6 mg/dL; parathyroid hormone was 7.6 pg/mL (normal range, 12-88 pg/mL); parathyroid hormone-related protein was 6.4 pmol/L (normal range, < 2.0 pmol/L); potassium was 3.4 mmol/L (normal range, 3.5 – 5.1 mmol/L); and magnesium was 2.01 mg/dL. The patient’s thyroid stimulating hormone level was normal, and serial cardiac enzymes stayed within the reference range.

The patient was admitted to a cardiac care unit. A temporary transvenous pacemaker was placed, and the hypercalcemia was treated with aggressive fluid hydration, calcitonin, and zoledronic acid. Serum calcium gradually decreased to 14.6 mg/dL the following day and 9.6 mg/dL the subsequent day. The normalization of calcium resulted in resolution of complete heart block (Figure 3). The patient did not experience recurrence of AV nodal dysfunction and eventually died 3 months later due to his advanced metastatic disease.

Discussion

The reported cardiovascular effects of hypercalcemia include hypertension, arrhythmias, increased myocardial contractility at serum calcium level below 15 mg/dL, and myocardial depression above that level. Electrocardiographic manifestations of hypercalcemia include a shortened ST segment leading to a short corrected QT interval (QTc), slight increase in T wave duration, and rarely, Osborn waves or J waves.^1-3 However, its influence on the AV node is less clear.

One small study assessed the prevalence of cardiac arrhythmias and conduction disturbances in 20 patients with hyperparathyroidism and moderate hypercalcemia and found no increase in the frequency of arrhythmias or high grade AV block.⁴

There are reports of conduction abnormality secondary to experimentally induced hypercalcemia in the literature. Hoff and colleagues described findings of AV block generated by the injection of IV calcium in dogs.⁵ In 2 human subjects, sinus bradycardia was precipitated after they received IV infusion of calcium gluconate.⁶ Shah and colleagues described 2 patients with sinus node dysfunction attributed to hypercalcemia secondary to hyperparathyroidism.⁷

Case reports of AV nodal dysfunction provoked by hypercalcemia have primarily occurred in the setting of primary hyperparathyroidism.^8,9 Milk-alkali syndrome and vitamin D related hypercalcemia also have been reported to cause complete heart block.^10,11 Reports of malignancy-related hypercalcemia causing conduction abnormalities are rare. The authors also found one case report of marked sinus bradycardia due to hypercalcemia related to breast cancer.¹²The case study presented in this report is rare because the patient developed complete AV block due to malignancy-related hypercalcemia that resolved completely with resolution of hypercalcemia. The prolongation of the QTc interval was another unique electrocardiographic change observed in this case. Calcium levels are inversely proportional to the QTc interval, and hypercalcemia is typically associated with a shortened QTc interval. However, this patient had a prolonged QTc without any other clear-cut cause. His hypokalemia was of a mild degree and not severe enough to produce such a long QTc interval. A possible explanation of QTc prolongation may be an increase in the T wave width associated with a serum calcium level above 16 mg/dL.

The pathophysiology of hypercalcemia-induced AV nodal conduction system disease is unknown. Calcium deposition in AV nodes of elderly patients has been associated with paroxysmal 2:1 AV block.⁸ It could be postulated that elevated serum calcium levels predispose to calcium deposition in cardiac conduction tissue, leading to progressive dysfunction. Although this theory may be applicable in a chronic setting, the mechanism in an acute setting likely relates to elevated serum levels of calcium that causes an alteration in electrochemical gradients. These elevated serum levels also increase intracellular calcium. This rise may result in increased calmodulin activation on the intracellular portion of the myocyte cell membrane and consequent enhanced sodium channel activation, which may then inhibit AV nodal conduction.¹³

Conclusion

Physicians should be aware that severe hypercalcemia can cause significant conduction system alterations, including complete AV block. A short QTc interval is typical, but a prolonged QTc interval also may be seen. While temporary support with a transvenous pacemaker may be needed, the conduction system abnormality is expected to resolve by treatment of the underlying hypercalcemia.

With an increasing demand for mental health services for veterans in rural clinics, telehealth can deliver services to veterans at home or in other nonclinic settings. Telehealth can reduce demands on VA clinic space and staff required for traditional videoconferencing.

Clinic-based telemental health started at the VA in 2003 and has provided access to more than 1 million appointments.¹ Despite the great strides in accessibility, logistic barriers limit expansion of clinic-based telehealth appointments. A VA staff member at the patient site must be available to “greet and seat” the veteran; scheduling requires 2 separate appointments (on patient and provider sites); and limited telehealth equipment and clinic space need to be reserved ahead of time.

The first known use of telehealth technologies to deliver mental health services within the VA network information technology system to at-home veterans occurred in 2009 at the VA Portland Health Care System (VAPORHCS) in Oregon. Between 2010 and 2013, the VAPORHCS Home-Based Telemental Health (HBTMH) pilot served about 82 veterans through about 740 appointments. The HBTMH pilot transitioned from a single facility to a regional implementation model under an Office of Innovation Grant Innovation #669: Home-Based Telemental Health (Innovation), which served about 84 veterans from 2013 to 2014.

In 2014, about 4,200 veterans accessed some health care via the national Clinical Video Telehealth–Into the Home (CVT-IH) program, with all 21 VISNs participating (John Peters, e-mail communication, February 2014). In all 3 implementation models (HBTMH pilot, Innovation, and CVT-IH), the veteran can receive health services via videoconferencing in real time, on personal or loaned computers, at home or in another nonclinic setting.

As the VA’s use of telehealth services grows in non-VA settings, technical support remains a significant challenge.² Increased use of CVT-IH through veterans’ personal computers and devices has generated a corresponding need for technical support. The National Telehealth Technical Help Desk (NTTHD), which supports the national CVT-IH program, does not provide technical support directly to veterans. Instead, recommendations are given to the providers who are expected to transmit and implement the technical solutions with the veterans. Similarly, HBTMH pilot providers were initially responsible for all technical issues for home-based telehealth work, including helping patients with software installation and subsequent troubleshooting.

Providers participating in the HBTMH pilot project encountered veterans with all levels of comfort and skill with the required technology. Some veterans have never used a personal computer, e-mail, and/or webcam. Addressing technical issues often required up to 15 to 20 minutes during an HBTMH pilot session; some cases took hours spread over several days. In VISN 20, providers in Oregon and Washington have reported discontinuation of treatment of veterans enrolled in CVT-IH for technical reasons, including poor connections, lack of timely technical support, and incompatibility of veteran-owned computers with VA-approved third-party software (Anders Goranson, Sara Smucker Barnwell, Kathleen Woodside, e-mail communication, December 2013).

A peer technical consultant (PTC) who directly serves patients and providers may be better positioned to meet the technical needs of everyone involved in a home-based telehealth program. The PTC role was developed for the HBTMH Pilot and expanded during the Innovation program. The authors describe the role of the PTC, outline key responsibilities, and highlight how the PTC can provide effective technical support and improve provider and patient access and engagement with nonclinic-based telehealth services.

Methods

Lessons from the initial phases of the HBTMH pilot strongly suggested that technical barriers had to be reduced. In 2010, a former patient in the HBTMH pilot who had a background in information technology and computer systems and interest in helping other veterans contacted Dr. Peter Shore. They developed the novel role of a PTC, focused on delivering technical support with compassion (Table 1). A functional statement and position description were submitted to volunteer services at the VAPORHCS (Appendix). With the regionwide expansion of the HBTMH pilot into the Innovation program, the PTC was hired as a full-time contract employee to increase the availability of technical support.

The PTC assumed responsibility for installations and troubleshooting for both providers and veterans enrolled in the HBTMH pilot. The PTC, who was based at the VAPORHCS, received referrals, contacted veterans by telephone, addressed technical problems, and reported the result to the provider. No face-to-face contact occurred between the PTC and the veterans. The PTC received regular supervision from the project director. Starting in mid-2012, local providers who were using the national CVT-IH program also requested PTC services. The PTC was able to add technical support for veterans beyond the NTTHD model, allowing for immediate in-session attention in some cases.

For the Innovation program, which loaned devices (netbooks or iPads) and connectivity (mobile broadband Internet access) to veterans who needed them, the role of PTC expanded to become a technology concierge, helping to set up and manage all mobile telecommunication devices. The PTC phoned veterans when they received their device and provided a virtual tour, helped familiarize them with the technology by using test calls, and guided them in the use of relevant mobile applications installed on the device. During treatment, the PTC called enrolled veterans to follow up and to answer additional questions. The PTC also provided assistance to veterans interested in enrolling in the patient online portal My HealtheVet to access health information, communicate with providers, and request medication refills.

The VAPORHCS received institutional review board approval to present HBTMH pilot research data and program evaluation data for Innovation (as a quality improvement project). An initial evaluation of the position was completed through review of PTC workload and productivity, informal feedback from telehealth providers, and veteran and provider surveys during and after treatment.

Results

From March 2010 through April 2012, the PTC logged more than 2,500 hours of volunteer service on behalf of the HBTMH pilot (before the Innovation expansion). The dropout rate due to nonclinical reasons for veterans enrolled in the HBTMH pilot was 11%.³ During the HBTMH pilot, 78% of veterans reported that they had enough technical support (ie, from the volunteer PTC), whereas among veterans receiving clinic-based videoconferencing sessions, 61% reported having adequate technical support (ie, from telehealth clinical technicians employed by the VA).³

During 2013 to 2014, veterans and providers were surveyed during and after Innovation program treatment. Eighty percent of participants stated that the PTC was prompt in resolving any issues (20% reported “neutral”). One hundred percent of providers indicated that the PTC was able to resolve the technical issues and that they were “very likely” to continue participating in HBTMH if the PTC was involved. Eighty-nine percent of veterans reported they felt there was enough technical support, and 11% responded “neutral” to this question. Table 2 describes typical PTC services provided during the Innovation program.

Informal summary observations from the PTC confirmed that the most frequent interventions were device and software orientation, assessment of audio and/or video disruptions during sessions, and software log-in configuration and support. Common technical issues included audio and video bandwidth limitations and the need to clean up veterans’ personal computers to restore functionality or improve performance (eg, problems due to malware and viruses; e-mail communication, various dates, William Cannon).

Troubleshooting was performed immediately during a session about half the time (vs between sessions) and initiated by veterans about half the time (vs by providers on their behalf) according to informal observations. The average length of a technical support appointment was about 30 minutes for veterans who were comfortable with technology; in contrast, appointments with veterans who were unfamiliar with technology averaged about 90 minutes.

The task logs recorded instances where flexibility and availability were needed for optimal task completion. Although many tasks seemed to be routine, others showed considerable use of the PTC’s time or direct participation during a session.

One PTC noted, “Client called around 9:30 and had me put [provider’s name] info into Jabber. Also Jabber had an issue of being stuck but forced a call and issue cleared up. 15 min. Stayed online with client to ensure appointment connection went well. 5 min.”

Malware, although not the most common issue, seemed to be time consuming. A task that required 4 hours for resolution of multiple issues was described as “requested outside assist due to drivers. Troubleshooting discovered 240 plus malware and numerous Trojan [horses].”

Another time-consuming issue involved software or updates to existing software interfering with the videoconferencing program, with the following example logged for 90 minutes: “Jabber will not store contacts. Updated IOS. Deleted games. Deleted and reinstalled Jabber. Re-updated Jabber. Problem finally resolved” (December 19, 2014). Other patients simply needed more time to familiarize themselves with the technology, as in this example: “2.5 hours of training and using the iPad” (November 25, 2014).

Informal feedback from providers as well as formal feedback from a program audit indicated appreciation for the PTC’s ability to facilitate engagement and surmount technical hurdles. One provider reflected on a particular instance in which the PTC worked with both the veteran and the provider over the phone and webchat to teach them to use the equipment. “[Veteran] and the peer technician developed a friendly rapport and [veteran] expressed gratitude for the team’s efforts to deliver treatment that he would not have had otherwise.” Another provider commented, “The [National] Help Desk is almost too general. You have to explain who you are each time, and never get to explain who [the] veteran is. … They are aware of national problems. Otherwise, they can’t help out much.”

In 2012, the Office of Telehealth Services completed its Conditions of Participation review of all VISN 20 Telehealth programs and in their final report commended the practices of the HBTMH program, highlighting the associated peer-to-peer volunteer program.⁴

Discussion

The number of technical issues addressed by the PTC demonstrates the versatility and potential impact of this role. In each case, the PTC accommodates the specific needs of the veteran and any factors that might impact their technology use (eg, low cognitive functioning, hyperarousal, slowed processing speed, low frustration tolerance, or paranoia). This model could be expanded within or outside the VA, although due to the limited scope of the evaluation and the unique qualifications of the individual who filled the PTC role, generalizability remains to be established.

By providing direct support, the PTC attempts to meet veterans where they are and helps them become comfortable with the technology so they are not preoccupied with technical problems while receiving health care. In doing so, engagement in telehealth care is enhanced for patients and providers, and dropouts due to technologic problems may be prevented. Initial program evaluation of this role also suggests considerable provider and veteran satisfaction.

The PTC’s interactions help minimize potential frustrations related to technology use for the delivery of mental health care. Frequently, veterans using in-home telehealth have little experience with technology. Moreover, technology use has been found to be lower for rural dwelling adults.⁵ Other populations (eg, geriatric) may have greater technology challenges and need additional support.⁶ When patients start CVT services, there is a potential for dropout if there are initial connection problems, particularly among patients who may have low stress tolerance. The PTC can develop an ongoing relationship with veterans who have a history of technologic difficulties and help monitor them.

Technology barriers and limited support are also a documented barrier to provider engagement.⁷ Given the inherent limitations and reported provider discouragement with the NTTHD model, more directed technical support may enhance provider engagement and efficiency. With the immediate and one-on-one support given by the PTC, this concern has been assertively addressed. In VISN 20 some mental health care providers elected not to use the CVT-IH program technical support system of the and chose instead to work with the Innovation PTC.

Programmatically, the PTC role is consistent with the VA Office of Mental Health Services and the VA Central Office initiative to increase involvement of peer support programs. From a recovery model perspective, the role of the PTC goes beyond technical support in connecting veterans to other veterans who are encouraged to take control of their health care by making self-directed choices. They can experience empowerment through interactions with another veteran who may share some of their experiences. Further investigation into the effects of using a peer technical support system on veterans, providers, and PTCs compared with the existing national VA technical support help desk system might be useful, particularly with regard to rates of initiation of care or dropouts.

Integration of this role should be done in a purposeful and direct manner, defining peer roles and establishing clear policies and practices. Logistically, the transition of the PTC from a volunteer to a contract employee afforded increased credentialing to allow for improved integration with the other HBTMH team members. The PTC was able to effectively coordinate with clinical, support and administrative staff to share information, resolve issues collaboratively, and bridge gaps in technology knowledge.

Conclusion

Between the HBTMH pilot and the Innovation program, the authors have demonstrated the growing need for personalized and attentive technical support for patients enrolled in home-based telehealth services. Under a current call center help desk model, satisfaction and services may be inadequate for some veterans’ needs. The authors contend that the PTC is an effective way to deliver the necessary specialized technical assistance to veterans and providers and encourage further implementation and evaluation of this approach.

There is preliminary evidence suggesting that this support can have a beneficial impact on provider and veteran engagement in telehealth services. The PTC offers much needed support to providers who frequently do not have the time or knowledge to address all the technical issues that arise during telehealth care. Veterans helping veterans is a powerful alternative deserving of national resources and policy change. Although this case developed in a very VA-specific context, peer technical support may be applicable to other organizations as well. 

Acknowledgements
Being the first to do anything in the VA takes courage, tenacity, and luck. The following individuals greatly assisted with the HBTMH pilot and the subsequent Innovation: William “Bear” Cannon, David Greaves, Tracy Dekelboum, William Minium, Sean O’Connor, Joe Ronzio, Kit Teague, and Mark Ward. For assistance with data entry and analysis, the authors thank Athalia White. For help with administrative approvals, the authors thank Bradford Felker and Carol Simons.

This article is dedicated to William “Bear” Cannon, who reinvented himself while serving as the PTC and saved his life along the way. His unwavering commitment to serve his fellow veterans is unheralded. May he be the shining light to those who follow him.

With an increasing demand for mental health services for veterans in rural clinics, telehealth can deliver services to veterans at home or in other nonclinic settings. Telehealth can reduce demands on VA clinic space and staff required for traditional videoconferencing.

Clinic-based telemental health started at the VA in 2003 and has provided access to more than 1 million appointments.¹ Despite the great strides in accessibility, logistic barriers limit expansion of clinic-based telehealth appointments. A VA staff member at the patient site must be available to “greet and seat” the veteran; scheduling requires 2 separate appointments (on patient and provider sites); and limited telehealth equipment and clinic space need to be reserved ahead of time.

The first known use of telehealth technologies to deliver mental health services within the VA network information technology system to at-home veterans occurred in 2009 at the VA Portland Health Care System (VAPORHCS) in Oregon. Between 2010 and 2013, the VAPORHCS Home-Based Telemental Health (HBTMH) pilot served about 82 veterans through about 740 appointments. The HBTMH pilot transitioned from a single facility to a regional implementation model under an Office of Innovation Grant Innovation #669: Home-Based Telemental Health (Innovation), which served about 84 veterans from 2013 to 2014.

In 2014, about 4,200 veterans accessed some health care via the national Clinical Video Telehealth–Into the Home (CVT-IH) program, with all 21 VISNs participating (John Peters, e-mail communication, February 2014). In all 3 implementation models (HBTMH pilot, Innovation, and CVT-IH), the veteran can receive health services via videoconferencing in real time, on personal or loaned computers, at home or in another nonclinic setting.

As the VA’s use of telehealth services grows in non-VA settings, technical support remains a significant challenge.² Increased use of CVT-IH through veterans’ personal computers and devices has generated a corresponding need for technical support. The National Telehealth Technical Help Desk (NTTHD), which supports the national CVT-IH program, does not provide technical support directly to veterans. Instead, recommendations are given to the providers who are expected to transmit and implement the technical solutions with the veterans. Similarly, HBTMH pilot providers were initially responsible for all technical issues for home-based telehealth work, including helping patients with software installation and subsequent troubleshooting.

Providers participating in the HBTMH pilot project encountered veterans with all levels of comfort and skill with the required technology. Some veterans have never used a personal computer, e-mail, and/or webcam. Addressing technical issues often required up to 15 to 20 minutes during an HBTMH pilot session; some cases took hours spread over several days. In VISN 20, providers in Oregon and Washington have reported discontinuation of treatment of veterans enrolled in CVT-IH for technical reasons, including poor connections, lack of timely technical support, and incompatibility of veteran-owned computers with VA-approved third-party software (Anders Goranson, Sara Smucker Barnwell, Kathleen Woodside, e-mail communication, December 2013).

A peer technical consultant (PTC) who directly serves patients and providers may be better positioned to meet the technical needs of everyone involved in a home-based telehealth program. The PTC role was developed for the HBTMH Pilot and expanded during the Innovation program. The authors describe the role of the PTC, outline key responsibilities, and highlight how the PTC can provide effective technical support and improve provider and patient access and engagement with nonclinic-based telehealth services.

Methods

Lessons from the initial phases of the HBTMH pilot strongly suggested that technical barriers had to be reduced. In 2010, a former patient in the HBTMH pilot who had a background in information technology and computer systems and interest in helping other veterans contacted Dr. Peter Shore. They developed the novel role of a PTC, focused on delivering technical support with compassion (Table 1). A functional statement and position description were submitted to volunteer services at the VAPORHCS (Appendix). With the regionwide expansion of the HBTMH pilot into the Innovation program, the PTC was hired as a full-time contract employee to increase the availability of technical support.

The PTC assumed responsibility for installations and troubleshooting for both providers and veterans enrolled in the HBTMH pilot. The PTC, who was based at the VAPORHCS, received referrals, contacted veterans by telephone, addressed technical problems, and reported the result to the provider. No face-to-face contact occurred between the PTC and the veterans. The PTC received regular supervision from the project director. Starting in mid-2012, local providers who were using the national CVT-IH program also requested PTC services. The PTC was able to add technical support for veterans beyond the NTTHD model, allowing for immediate in-session attention in some cases.

For the Innovation program, which loaned devices (netbooks or iPads) and connectivity (mobile broadband Internet access) to veterans who needed them, the role of PTC expanded to become a technology concierge, helping to set up and manage all mobile telecommunication devices. The PTC phoned veterans when they received their device and provided a virtual tour, helped familiarize them with the technology by using test calls, and guided them in the use of relevant mobile applications installed on the device. During treatment, the PTC called enrolled veterans to follow up and to answer additional questions. The PTC also provided assistance to veterans interested in enrolling in the patient online portal My HealtheVet to access health information, communicate with providers, and request medication refills.

The VAPORHCS received institutional review board approval to present HBTMH pilot research data and program evaluation data for Innovation (as a quality improvement project). An initial evaluation of the position was completed through review of PTC workload and productivity, informal feedback from telehealth providers, and veteran and provider surveys during and after treatment.

Results

From March 2010 through April 2012, the PTC logged more than 2,500 hours of volunteer service on behalf of the HBTMH pilot (before the Innovation expansion). The dropout rate due to nonclinical reasons for veterans enrolled in the HBTMH pilot was 11%.³ During the HBTMH pilot, 78% of veterans reported that they had enough technical support (ie, from the volunteer PTC), whereas among veterans receiving clinic-based videoconferencing sessions, 61% reported having adequate technical support (ie, from telehealth clinical technicians employed by the VA).³

During 2013 to 2014, veterans and providers were surveyed during and after Innovation program treatment. Eighty percent of participants stated that the PTC was prompt in resolving any issues (20% reported “neutral”). One hundred percent of providers indicated that the PTC was able to resolve the technical issues and that they were “very likely” to continue participating in HBTMH if the PTC was involved. Eighty-nine percent of veterans reported they felt there was enough technical support, and 11% responded “neutral” to this question. Table 2 describes typical PTC services provided during the Innovation program.

Informal summary observations from the PTC confirmed that the most frequent interventions were device and software orientation, assessment of audio and/or video disruptions during sessions, and software log-in configuration and support. Common technical issues included audio and video bandwidth limitations and the need to clean up veterans’ personal computers to restore functionality or improve performance (eg, problems due to malware and viruses; e-mail communication, various dates, William Cannon).

Troubleshooting was performed immediately during a session about half the time (vs between sessions) and initiated by veterans about half the time (vs by providers on their behalf) according to informal observations. The average length of a technical support appointment was about 30 minutes for veterans who were comfortable with technology; in contrast, appointments with veterans who were unfamiliar with technology averaged about 90 minutes.

The task logs recorded instances where flexibility and availability were needed for optimal task completion. Although many tasks seemed to be routine, others showed considerable use of the PTC’s time or direct participation during a session.

One PTC noted, “Client called around 9:30 and had me put [provider’s name] info into Jabber. Also Jabber had an issue of being stuck but forced a call and issue cleared up. 15 min. Stayed online with client to ensure appointment connection went well. 5 min.”

Malware, although not the most common issue, seemed to be time consuming. A task that required 4 hours for resolution of multiple issues was described as “requested outside assist due to drivers. Troubleshooting discovered 240 plus malware and numerous Trojan [horses].”

Another time-consuming issue involved software or updates to existing software interfering with the videoconferencing program, with the following example logged for 90 minutes: “Jabber will not store contacts. Updated IOS. Deleted games. Deleted and reinstalled Jabber. Re-updated Jabber. Problem finally resolved” (December 19, 2014). Other patients simply needed more time to familiarize themselves with the technology, as in this example: “2.5 hours of training and using the iPad” (November 25, 2014).

Informal feedback from providers as well as formal feedback from a program audit indicated appreciation for the PTC’s ability to facilitate engagement and surmount technical hurdles. One provider reflected on a particular instance in which the PTC worked with both the veteran and the provider over the phone and webchat to teach them to use the equipment. “[Veteran] and the peer technician developed a friendly rapport and [veteran] expressed gratitude for the team’s efforts to deliver treatment that he would not have had otherwise.” Another provider commented, “The [National] Help Desk is almost too general. You have to explain who you are each time, and never get to explain who [the] veteran is. … They are aware of national problems. Otherwise, they can’t help out much.”

In 2012, the Office of Telehealth Services completed its Conditions of Participation review of all VISN 20 Telehealth programs and in their final report commended the practices of the HBTMH program, highlighting the associated peer-to-peer volunteer program.⁴

Discussion

The number of technical issues addressed by the PTC demonstrates the versatility and potential impact of this role. In each case, the PTC accommodates the specific needs of the veteran and any factors that might impact their technology use (eg, low cognitive functioning, hyperarousal, slowed processing speed, low frustration tolerance, or paranoia). This model could be expanded within or outside the VA, although due to the limited scope of the evaluation and the unique qualifications of the individual who filled the PTC role, generalizability remains to be established.

By providing direct support, the PTC attempts to meet veterans where they are and helps them become comfortable with the technology so they are not preoccupied with technical problems while receiving health care. In doing so, engagement in telehealth care is enhanced for patients and providers, and dropouts due to technologic problems may be prevented. Initial program evaluation of this role also suggests considerable provider and veteran satisfaction.

The PTC’s interactions help minimize potential frustrations related to technology use for the delivery of mental health care. Frequently, veterans using in-home telehealth have little experience with technology. Moreover, technology use has been found to be lower for rural dwelling adults.⁵ Other populations (eg, geriatric) may have greater technology challenges and need additional support.⁶ When patients start CVT services, there is a potential for dropout if there are initial connection problems, particularly among patients who may have low stress tolerance. The PTC can develop an ongoing relationship with veterans who have a history of technologic difficulties and help monitor them.

Technology barriers and limited support are also a documented barrier to provider engagement.⁷ Given the inherent limitations and reported provider discouragement with the NTTHD model, more directed technical support may enhance provider engagement and efficiency. With the immediate and one-on-one support given by the PTC, this concern has been assertively addressed. In VISN 20 some mental health care providers elected not to use the CVT-IH program technical support system of the and chose instead to work with the Innovation PTC.

Programmatically, the PTC role is consistent with the VA Office of Mental Health Services and the VA Central Office initiative to increase involvement of peer support programs. From a recovery model perspective, the role of the PTC goes beyond technical support in connecting veterans to other veterans who are encouraged to take control of their health care by making self-directed choices. They can experience empowerment through interactions with another veteran who may share some of their experiences. Further investigation into the effects of using a peer technical support system on veterans, providers, and PTCs compared with the existing national VA technical support help desk system might be useful, particularly with regard to rates of initiation of care or dropouts.

Integration of this role should be done in a purposeful and direct manner, defining peer roles and establishing clear policies and practices. Logistically, the transition of the PTC from a volunteer to a contract employee afforded increased credentialing to allow for improved integration with the other HBTMH team members. The PTC was able to effectively coordinate with clinical, support and administrative staff to share information, resolve issues collaboratively, and bridge gaps in technology knowledge.

Conclusion

Between the HBTMH pilot and the Innovation program, the authors have demonstrated the growing need for personalized and attentive technical support for patients enrolled in home-based telehealth services. Under a current call center help desk model, satisfaction and services may be inadequate for some veterans’ needs. The authors contend that the PTC is an effective way to deliver the necessary specialized technical assistance to veterans and providers and encourage further implementation and evaluation of this approach.

There is preliminary evidence suggesting that this support can have a beneficial impact on provider and veteran engagement in telehealth services. The PTC offers much needed support to providers who frequently do not have the time or knowledge to address all the technical issues that arise during telehealth care. Veterans helping veterans is a powerful alternative deserving of national resources and policy change. Although this case developed in a very VA-specific context, peer technical support may be applicable to other organizations as well. 

Acknowledgements
Being the first to do anything in the VA takes courage, tenacity, and luck. The following individuals greatly assisted with the HBTMH pilot and the subsequent Innovation: William “Bear” Cannon, David Greaves, Tracy Dekelboum, William Minium, Sean O’Connor, Joe Ronzio, Kit Teague, and Mark Ward. For assistance with data entry and analysis, the authors thank Athalia White. For help with administrative approvals, the authors thank Bradford Felker and Carol Simons.

This article is dedicated to William “Bear” Cannon, who reinvented himself while serving as the PTC and saved his life along the way. His unwavering commitment to serve his fellow veterans is unheralded. May he be the shining light to those who follow him.

With an increasing demand for mental health services for veterans in rural clinics, telehealth can deliver services to veterans at home or in other nonclinic settings. Telehealth can reduce demands on VA clinic space and staff required for traditional videoconferencing.

Clinic-based telemental health started at the VA in 2003 and has provided access to more than 1 million appointments.¹ Despite the great strides in accessibility, logistic barriers limit expansion of clinic-based telehealth appointments. A VA staff member at the patient site must be available to “greet and seat” the veteran; scheduling requires 2 separate appointments (on patient and provider sites); and limited telehealth equipment and clinic space need to be reserved ahead of time.

The first known use of telehealth technologies to deliver mental health services within the VA network information technology system to at-home veterans occurred in 2009 at the VA Portland Health Care System (VAPORHCS) in Oregon. Between 2010 and 2013, the VAPORHCS Home-Based Telemental Health (HBTMH) pilot served about 82 veterans through about 740 appointments. The HBTMH pilot transitioned from a single facility to a regional implementation model under an Office of Innovation Grant Innovation #669: Home-Based Telemental Health (Innovation), which served about 84 veterans from 2013 to 2014.

In 2014, about 4,200 veterans accessed some health care via the national Clinical Video Telehealth–Into the Home (CVT-IH) program, with all 21 VISNs participating (John Peters, e-mail communication, February 2014). In all 3 implementation models (HBTMH pilot, Innovation, and CVT-IH), the veteran can receive health services via videoconferencing in real time, on personal or loaned computers, at home or in another nonclinic setting.

As the VA’s use of telehealth services grows in non-VA settings, technical support remains a significant challenge.² Increased use of CVT-IH through veterans’ personal computers and devices has generated a corresponding need for technical support. The National Telehealth Technical Help Desk (NTTHD), which supports the national CVT-IH program, does not provide technical support directly to veterans. Instead, recommendations are given to the providers who are expected to transmit and implement the technical solutions with the veterans. Similarly, HBTMH pilot providers were initially responsible for all technical issues for home-based telehealth work, including helping patients with software installation and subsequent troubleshooting.

Providers participating in the HBTMH pilot project encountered veterans with all levels of comfort and skill with the required technology. Some veterans have never used a personal computer, e-mail, and/or webcam. Addressing technical issues often required up to 15 to 20 minutes during an HBTMH pilot session; some cases took hours spread over several days. In VISN 20, providers in Oregon and Washington have reported discontinuation of treatment of veterans enrolled in CVT-IH for technical reasons, including poor connections, lack of timely technical support, and incompatibility of veteran-owned computers with VA-approved third-party software (Anders Goranson, Sara Smucker Barnwell, Kathleen Woodside, e-mail communication, December 2013).

A peer technical consultant (PTC) who directly serves patients and providers may be better positioned to meet the technical needs of everyone involved in a home-based telehealth program. The PTC role was developed for the HBTMH Pilot and expanded during the Innovation program. The authors describe the role of the PTC, outline key responsibilities, and highlight how the PTC can provide effective technical support and improve provider and patient access and engagement with nonclinic-based telehealth services.

Methods

Lessons from the initial phases of the HBTMH pilot strongly suggested that technical barriers had to be reduced. In 2010, a former patient in the HBTMH pilot who had a background in information technology and computer systems and interest in helping other veterans contacted Dr. Peter Shore. They developed the novel role of a PTC, focused on delivering technical support with compassion (Table 1). A functional statement and position description were submitted to volunteer services at the VAPORHCS (Appendix). With the regionwide expansion of the HBTMH pilot into the Innovation program, the PTC was hired as a full-time contract employee to increase the availability of technical support.

The PTC assumed responsibility for installations and troubleshooting for both providers and veterans enrolled in the HBTMH pilot. The PTC, who was based at the VAPORHCS, received referrals, contacted veterans by telephone, addressed technical problems, and reported the result to the provider. No face-to-face contact occurred between the PTC and the veterans. The PTC received regular supervision from the project director. Starting in mid-2012, local providers who were using the national CVT-IH program also requested PTC services. The PTC was able to add technical support for veterans beyond the NTTHD model, allowing for immediate in-session attention in some cases.

For the Innovation program, which loaned devices (netbooks or iPads) and connectivity (mobile broadband Internet access) to veterans who needed them, the role of PTC expanded to become a technology concierge, helping to set up and manage all mobile telecommunication devices. The PTC phoned veterans when they received their device and provided a virtual tour, helped familiarize them with the technology by using test calls, and guided them in the use of relevant mobile applications installed on the device. During treatment, the PTC called enrolled veterans to follow up and to answer additional questions. The PTC also provided assistance to veterans interested in enrolling in the patient online portal My HealtheVet to access health information, communicate with providers, and request medication refills.

The VAPORHCS received institutional review board approval to present HBTMH pilot research data and program evaluation data for Innovation (as a quality improvement project). An initial evaluation of the position was completed through review of PTC workload and productivity, informal feedback from telehealth providers, and veteran and provider surveys during and after treatment.

Results

From March 2010 through April 2012, the PTC logged more than 2,500 hours of volunteer service on behalf of the HBTMH pilot (before the Innovation expansion). The dropout rate due to nonclinical reasons for veterans enrolled in the HBTMH pilot was 11%.³ During the HBTMH pilot, 78% of veterans reported that they had enough technical support (ie, from the volunteer PTC), whereas among veterans receiving clinic-based videoconferencing sessions, 61% reported having adequate technical support (ie, from telehealth clinical technicians employed by the VA).³

During 2013 to 2014, veterans and providers were surveyed during and after Innovation program treatment. Eighty percent of participants stated that the PTC was prompt in resolving any issues (20% reported “neutral”). One hundred percent of providers indicated that the PTC was able to resolve the technical issues and that they were “very likely” to continue participating in HBTMH if the PTC was involved. Eighty-nine percent of veterans reported they felt there was enough technical support, and 11% responded “neutral” to this question. Table 2 describes typical PTC services provided during the Innovation program.

Informal summary observations from the PTC confirmed that the most frequent interventions were device and software orientation, assessment of audio and/or video disruptions during sessions, and software log-in configuration and support. Common technical issues included audio and video bandwidth limitations and the need to clean up veterans’ personal computers to restore functionality or improve performance (eg, problems due to malware and viruses; e-mail communication, various dates, William Cannon).

Troubleshooting was performed immediately during a session about half the time (vs between sessions) and initiated by veterans about half the time (vs by providers on their behalf) according to informal observations. The average length of a technical support appointment was about 30 minutes for veterans who were comfortable with technology; in contrast, appointments with veterans who were unfamiliar with technology averaged about 90 minutes.

The task logs recorded instances where flexibility and availability were needed for optimal task completion. Although many tasks seemed to be routine, others showed considerable use of the PTC’s time or direct participation during a session.

One PTC noted, “Client called around 9:30 and had me put [provider’s name] info into Jabber. Also Jabber had an issue of being stuck but forced a call and issue cleared up. 15 min. Stayed online with client to ensure appointment connection went well. 5 min.”

Malware, although not the most common issue, seemed to be time consuming. A task that required 4 hours for resolution of multiple issues was described as “requested outside assist due to drivers. Troubleshooting discovered 240 plus malware and numerous Trojan [horses].”

Another time-consuming issue involved software or updates to existing software interfering with the videoconferencing program, with the following example logged for 90 minutes: “Jabber will not store contacts. Updated IOS. Deleted games. Deleted and reinstalled Jabber. Re-updated Jabber. Problem finally resolved” (December 19, 2014). Other patients simply needed more time to familiarize themselves with the technology, as in this example: “2.5 hours of training and using the iPad” (November 25, 2014).

Informal feedback from providers as well as formal feedback from a program audit indicated appreciation for the PTC’s ability to facilitate engagement and surmount technical hurdles. One provider reflected on a particular instance in which the PTC worked with both the veteran and the provider over the phone and webchat to teach them to use the equipment. “[Veteran] and the peer technician developed a friendly rapport and [veteran] expressed gratitude for the team’s efforts to deliver treatment that he would not have had otherwise.” Another provider commented, “The [National] Help Desk is almost too general. You have to explain who you are each time, and never get to explain who [the] veteran is. … They are aware of national problems. Otherwise, they can’t help out much.”

In 2012, the Office of Telehealth Services completed its Conditions of Participation review of all VISN 20 Telehealth programs and in their final report commended the practices of the HBTMH program, highlighting the associated peer-to-peer volunteer program.⁴

Discussion

The number of technical issues addressed by the PTC demonstrates the versatility and potential impact of this role. In each case, the PTC accommodates the specific needs of the veteran and any factors that might impact their technology use (eg, low cognitive functioning, hyperarousal, slowed processing speed, low frustration tolerance, or paranoia). This model could be expanded within or outside the VA, although due to the limited scope of the evaluation and the unique qualifications of the individual who filled the PTC role, generalizability remains to be established.

By providing direct support, the PTC attempts to meet veterans where they are and helps them become comfortable with the technology so they are not preoccupied with technical problems while receiving health care. In doing so, engagement in telehealth care is enhanced for patients and providers, and dropouts due to technologic problems may be prevented. Initial program evaluation of this role also suggests considerable provider and veteran satisfaction.

The PTC’s interactions help minimize potential frustrations related to technology use for the delivery of mental health care. Frequently, veterans using in-home telehealth have little experience with technology. Moreover, technology use has been found to be lower for rural dwelling adults.⁵ Other populations (eg, geriatric) may have greater technology challenges and need additional support.⁶ When patients start CVT services, there is a potential for dropout if there are initial connection problems, particularly among patients who may have low stress tolerance. The PTC can develop an ongoing relationship with veterans who have a history of technologic difficulties and help monitor them.

Technology barriers and limited support are also a documented barrier to provider engagement.⁷ Given the inherent limitations and reported provider discouragement with the NTTHD model, more directed technical support may enhance provider engagement and efficiency. With the immediate and one-on-one support given by the PTC, this concern has been assertively addressed. In VISN 20 some mental health care providers elected not to use the CVT-IH program technical support system of the and chose instead to work with the Innovation PTC.

Programmatically, the PTC role is consistent with the VA Office of Mental Health Services and the VA Central Office initiative to increase involvement of peer support programs. From a recovery model perspective, the role of the PTC goes beyond technical support in connecting veterans to other veterans who are encouraged to take control of their health care by making self-directed choices. They can experience empowerment through interactions with another veteran who may share some of their experiences. Further investigation into the effects of using a peer technical support system on veterans, providers, and PTCs compared with the existing national VA technical support help desk system might be useful, particularly with regard to rates of initiation of care or dropouts.

Integration of this role should be done in a purposeful and direct manner, defining peer roles and establishing clear policies and practices. Logistically, the transition of the PTC from a volunteer to a contract employee afforded increased credentialing to allow for improved integration with the other HBTMH team members. The PTC was able to effectively coordinate with clinical, support and administrative staff to share information, resolve issues collaboratively, and bridge gaps in technology knowledge.

Conclusion

Between the HBTMH pilot and the Innovation program, the authors have demonstrated the growing need for personalized and attentive technical support for patients enrolled in home-based telehealth services. Under a current call center help desk model, satisfaction and services may be inadequate for some veterans’ needs. The authors contend that the PTC is an effective way to deliver the necessary specialized technical assistance to veterans and providers and encourage further implementation and evaluation of this approach.

There is preliminary evidence suggesting that this support can have a beneficial impact on provider and veteran engagement in telehealth services. The PTC offers much needed support to providers who frequently do not have the time or knowledge to address all the technical issues that arise during telehealth care. Veterans helping veterans is a powerful alternative deserving of national resources and policy change. Although this case developed in a very VA-specific context, peer technical support may be applicable to other organizations as well. 

Acknowledgements
Being the first to do anything in the VA takes courage, tenacity, and luck. The following individuals greatly assisted with the HBTMH pilot and the subsequent Innovation: William “Bear” Cannon, David Greaves, Tracy Dekelboum, William Minium, Sean O’Connor, Joe Ronzio, Kit Teague, and Mark Ward. For assistance with data entry and analysis, the authors thank Athalia White. For help with administrative approvals, the authors thank Bradford Felker and Carol Simons.

This article is dedicated to William “Bear” Cannon, who reinvented himself while serving as the PTC and saved his life along the way. His unwavering commitment to serve his fellow veterans is unheralded. May he be the shining light to those who follow him.

In 2009, the VA announced a goal of ending veteran homelessness by 2015.¹ The primary focus of this new policy has been housing veterans experiencing chronic homelessness, many of whom languish outside the VA housing system. Since that time, progress has been made with point-in-time enumerations indicating that veteran homelessness has decreased nationally. Despite this progress, however, more than 55,000 veterans are still estimated to experience homelessness each night.²

Historically, the VA has offered an array of services specifically meant to alleviate veteran homelessness (grant, per diem, and other transitional housing programs; vocational rehabilitation, etc).³ The majority of these programs require some period of veteran abstinence as a condition for providing housing services. The recent move toward permanent “housing first” programs with few conditions for enrollment and participation provides new opportunities for housing veterans experiencing chronic homelessness, who are the specific target of the goal of ending veteran homelessness.⁴

Because veterans experiencing chronic homelessness have additional, substantial need for medical, psychiatric, and substance-abuse services, the VA also offers these services to this population.^5-7 Veterans experiencing homelessness also may access parallel non-VA services.⁸ Information about veterans outside of traditional VA housing services, specifically those housed in low-demand shelters, is needed to develop services for this population and will be critical to success in ending veteran homelessness.

The Behavioral Model of Health Services Use^9-11 and its later refinement, the Behavioral Model for Vulnerable Persons,¹² have been used to conceptualize health care service use (Figure). In these models, health service use is predicted by 3 types of factors: predisposing factors (eg, age, race, gender, residential history), enabling factors (eg, availability, accessibility, affordability, acceptability), and service need factors (eg, substance-use disorders, mental health problems, physical health problems).

Studies applying these models of health care service use to both general homeless populations and, specifically to populations of veterans experiencing homelessness have found that service use is most influenced by need-based factors (eg, drug abuse, poor health, mental health problems).^6,12-20 These same studies indicate that predisposing factors (eg, age, race, and gender) and enabling factors (eg, insurance, use of other services, and usual place of care) are also associated with service use, though less consistently.

Studies focused on veterans experiencing homelessness, however, included only treatment-seeking populations, which are not necessarily representative of the broader population of veterans experiencing homelessness. Additionally, none of these prior studies focused on the unique subset of veterans residing in low-demand shelters (characterized by unlimited duration of stay, no government ID or fee required for entry, and no requirement for service participation). This is a population that seems to be less engaged in services but nevertheless is challenged.²¹ This study, therefore, is focused on nontreatment seeking veterans residing in a low-demand shelter. The study applied the Behavioral Model of Health Services Use and the Behavioral Model for Vulnerable Persons to examine use of VA and non-VA services.

Study Parameters

This study was conducted in Fort Worth, Texas, the 17th largest city in the U.S. with more than 810,000 residents.²² In 2013, a biennial point-in-time count identified about 2,300 individuals who were homeless in Fort Worth. Most were found in emergency shelters (n = 1,126, 50%) or transitional housing (n = 965, 40%). Slightly more than 10% (n = 281) were found to be unsheltered: sleeping on the streets or in encampments, automobiles, or abandoned buildings.²³ Although national estimates identify 12% of all adults who are homeless as veterans,² only 8% (n = 189) of people experiencing homelessness in Fort Worth reported military service.²³

Access to the full array of VA emergency department (ED), inpatient, and outpatient medical, psychiatric, and substance-abuse services are available to veterans experiencing homelessness at the Dallas VA Medical Center (DVAMC), located 35 miles away. Only VA outpatient medical, psychiatric, and substance-related services are available in Fort Worth through the VA Outpatient Clinic and Health Care for the Homeless Veterans (HCHV) program. If veterans experiencing homelessness seek care outside of the VA system, a comprehensive network of emergency, inpatient and outpatient medical, psychiatric, and substance-related services is available in Fort Worth.

Sample

The study sample included 110 adult male veterans randomly recruited as they awaited admission to a private, low-demand emergency shelter. The study excluded veterans with a dishonorable discharge to ensure participants were eligible for VA services. Institutional review board approvals were obtained prior to the study from the University of Texas at Arlington and DVAMC. All participants provided informed consent and were given a $5 gift for their involvement.

Instruments

Through structured interviews, experienced research staff collected demographics, history of homelessness, military service, and substance abuse in the previous 30 days. Data on alcohol and drug problems in the past 12 months were obtained using the Short Michigan Alcohol Screening Test (SMAST) and the Drug Abuse Screening Test. The Veterans RAND 12-Item Health Survey (VR-12) was used to measure physical and mental health functioning in the previous 4 weeks. Finally, participants reported their use of VA or non-VA medical (ED, inpatient, and outpatient), psychiatric (ED, inpatient, and outpatient), and substance abuse-related (inpatient and outpatient) services in the 12 months prior to the interview. These measures have been shown to be valid and reliable with acceptable psychometrics.^24-26

Data Analysis

Statistical analysis was completed using IBM SPSS Statistics version 19. Descriptive data were summarized using counts, percentages, means, and standard deviations. A dichotomous variable for alcohol abuse was defined as SMAST score ≥ 3. A variable representing participant’s VR-12 mental component summary scores was used as an indicator of mental health functioning.

McNemar’s test was used to compare the use of VA and non-VA medical, psychiatric, and substance-related services using dichotomous variables for each overall sector as well as respective sector subcomponent services (emergency, inpatient, and outpatient for medical and psychiatric sectors and inpatient and outpatient for the substance-related sector). Statistical significance level was set at α = .05.

Logistic regression was used to predict psychiatric and substance abuse-related service use with separate dependent variables for VA, non-VA, and both VA and non-VA services. Need-based factors included in all models as independent variables were mental health functioning, alcohol abuse, and a dichotomous variable representing cocaine use in the previous 30 days. Independent variables for the other service sectors were included as enabling factors (eg, medical and substance-related problems predicting psychiatric service use), aligning all service use variables in the model to the same provider system (eg, VA service sector independent variables with VA service sector dependent variables).

Results

The sample mean age was 49.2 years (SD = 9.2), and fewer than half (n = 45, 41%) were white. Three-fourths (n = 82, 75%) had ever been married, and few participants (n = 5, 5%) were currently married. Total mean lifetime experience of homelessness was 3.9 years (SD = 4.3). One-third of the samples participants (n = 36, 33%) reported that their current episode of homelessness had lasted 1 year or longer. Most had an adult felony conviction (n = 78, 71%) and a history of incarceration as an adult (n = 104, 95%). All military branches were represented, with 49% serving in the Army, 23% in the Marine Corps, 17% in the Navy, 10% in the Air Force, and 1% in the Coast Guard.

Most of the sample’s veterans served during the Vietnam era (n = 43, 43%) or the post-Vietnam era (n = 49, 45%), but 12 (11%) served during the Persian Gulf era (including Operation Iraqi Freedom and Operation Enduring Freedom). Few received a nonservice connected VA pension (n = 21, 19%) or service-connected disability benefits (n = 20, 18%). The mean income earned in the previous 30 days was $466 (SD = $431). None of these predisposing factors were associated with any service variables.

The sample’s mean VR-12 physical functioning score was 43.8 (SD = 9.1), which was significantly higher (t = 6.2, df = 109, P < .001) than the 38.4 (SD = 12.2) population norm used with the instrument. The sample’s mean mental health functioning score of 39.4 (SD = 14.3) was significantly lower (t = -8.6, df = 109, P < .001) than the population norm (51.1, SD = 11.4).²⁷ Substance-related problems were prevalent, with an identified alcohol problem in 62% (n = 68) and a drug problem in 79% (n = 87) of participants. More than half reported illicit drug use in the past 30 days (n = 61, 56%), especially cocaine (n = 42, 38%) and marijuana (n = 37, 33%).

The majority of veterans (n = 96, 87%) reported using some type of service in the past 12 months (Table 1). Most survey respondents used medical services. About half used psychiatric services, and almost one-third used substance-related services. More veterans used non-VA ED services than used VA ED services. More veterans used VA outpatient medical services than used non-VA outpatient medical services. Examining service sectors indicated that more veterans used VA psychiatric services than used non-VA psychiatric services, especially VA outpatient psychiatric services. More veterans used non-VA substance abuse-related services, especially outpatient services, rather than similar services offered by the VA.

Separate logistic regression models predicted use of psychiatric and substance-abuse services with 3 models (VA, non-VA, or any service use) for each dependent variable from independent variables that reflected need and enabling factors (Tables 2 and 3). Demographic predisposing factors, which were not associated with service use, were not included as covariates in these models. For the model predicting the use of non-VA substance-abuse services, collinearity between the alcohol-abuse and cocaine-abuse variables required separate models for each of the 2 variables.

Medical sector service use predicted psychiatric sector service use in all models. In fact, VA medical service use was the only predictor of use of VA psychiatric services. Lower mental health functioning predicted the use of any (VA or non-VA) psychiatric service use. In addition to the use of medical services, 30-day cocaine use predicted non-VA psychiatric service use.

Any substance-related sector service use was predicted by lower mental health functioning, self-reported alcohol problem, and any medical services utilization. No independent variables included in the model predicted any VA substance-related service use. Non-VA substance abuse service use was predicted by non-VA psychiatric service use and alcohol abuse. In the separate analysis that replaced alcohol problems with 30-day cocaine use variable, only 30-day cocaine use predicted non-VA substance-related service utilization.

Discussion

This study examined the use of medical, psychiatric, and substance-abuse services by randomly sampled veterans from a low-demand emergency shelter. Random selection of the sample and its high (98%) participation rate virtually eliminated potential for bias within this sample. Another strength of this study is its focus on low-demand shelter users—a population that has not been well studied. This low-demand shelter-dwelling population of veterans experiencing homelessness is of interest because more substance-abuse problems and histories of incarceration seem to make them especially disadvantaged and challenged.

The limitation of the sample to users of a low-demand shelter at only 1 location may reduce generalizability to other veteran homeless populations and settings. The study also may not generalize to populations of female veterans experiencing homelessness. Another limitation of the study is that it did not use diagnostic assessments for psychiatric and substance use disorders and objective collateral information such as agency record data. Finally, although the limited size of the sample may have been insufficient to adequately test certain hypotheses, it was a relatively large sample of this population and was large enough to yield significant findings.

This study found that need-based factors predicted the use of some service sectors intended for those needs. For example, mental health functioning appropriately predicted any psychiatric service use, and presence of an alcohol problem appropriately predicted any substance abuse service use. Specifically for non-VA services, both cocaine use and presence of an alcohol problem in separate models predicted substance-abuse service use. However for VA substance-abuse services, neither cocaine use nor presence of an alcohol problem predicted service use. Despite the high need, very few veterans used substance-abuse services, and they rarely used VA substance-abuse services.

For 2 service sectors, need-based factors predicted the use of services intended for other needs. Cocaine use predicted non-VA psychiatric service use, and low mental health functioning predicted substance-abuse service use. One potential explanation for this finding could be that providers or patients incorrectly classified cocaine-related substance use problems as psychiatric. The VR-12 mental health functioning measure also may have incorrectly classified cocaine-related problems as psychiatric.

Three enabling factors predicted service use by sector and type. The first 2 are preference for VA-provided services and the geographic availability of services, which competed for veterans’ selection of service providers. When both VA and non-VA services were present in Fort Worth, a preference for VA-provided services was observed, with the exception of outpatient substance abuse services which were highly underutilized in general. No preference was observed for any non-VA services when both were present. When VA services were not present in Fort Worth, veterans used geographically available non-VA providers for some services, but for other services they used Dallas-based VA and Fort Worth-based non-VA providers equally (Table 3 and Table 4).

The third enabling factor influencing service use was through other service use as an enabling pathway. Those veterans who opted out of locally available services in favor of VA services in Dallas may have been prompted to do so by provider referrals, which were further facilitated by VA and public transportation between Fort Worth and Dallas. The most consistent enabling pathway was medical service use, which predicted all types of psychiatric service use (VA and non-VA combined, VA only, and non-VA only), and any substance-related service use. Psychiatric service use predicted substance abuse service use but only in non-VA settings; no pathways led from VA medical or psychiatric services to VA substance abuse services.

Conclusions

These findings suggest, in large part, the validity of the Andersen and Gelberg models of health care service use. Consistent with prior studies, need-based factors predicted the use of any psychiatric and substance-related sector services as well as the use of non-VA subcomponent services for both sectors. Also consistent with prior studies, enabling factors (medical sector service use) predicted service use, with the exception of VA or non-VA substance-abuse services. Unlike prior studies, however, predisposing factors (eg, age, race, marital status, and income) were not associated with service use.

This study could not determine why veterans underutilized substance-abuse services, even those available locally to them in Fort Worth. One possible barrier to care is that the services are designed or delivered in a manner that does not engage these veterans (eg, expectations regarding abstinence or service involvement). Another barrier could be that referral pathways between VA outpatient medical and psychiatric service providers and VA substance-related services are not sufficiently facilitative. Future investigations could build upon the findings of this study by collecting data that could help assess these potential barriers.

The data from this study suggest 3 opportunities to improve the utilization of services most needed by this population. The first opportunity would be to accurately differentiate between substance abuse and psychiatric problems in clinical assessment and identify the most appropriate type of care. Another opportunity, linked closely to the first, would be to facilitate more effective and efficient referral pathways among VA service sectors, especially from medical and psychiatric services to substance-abuse services. Another strategy to improve referral pathways would be for VA service networks to systematically examine local service systems for factors or processes that may disrupt integrated care and implement program improvements.²⁸ For homeless veterans navigating an inherently complex VA health care system, peer-to-peer and patient navigator programs have helped improve service efficiency and service outcomes.²⁹ The third opportunity to improve utilization of services would be to ensure geographic availability and accessibility by strategic placement of these services.

The results from this study, while informative, point directly to needed areas for further inquiry to inform public health response. Although the low-demand shelter users are a particularly challenging subgroup of veterans experiencing chronic homelessness, other equally challenging populations warrant additional study. For example, veterans outside of both VA and community services (eg, unsheltered populations) are likely to require different approaches to engage in appropriate services. Additionally, changes to the homeless policy implemented in the period after this sample was recruited suggest the need to revisit the service-using behaviors of this population. Finally, interventions developed as part of the national response need to be assessed for their ability to engage these difficult-to-reach veterans.

Acknowledgements
This study was funded by a U.S. Department of Veterans Affairs Office of Academic Affiliations Pre-Doctoral Social Work Research Fellowship award.

In 2009, the VA announced a goal of ending veteran homelessness by 2015.¹ The primary focus of this new policy has been housing veterans experiencing chronic homelessness, many of whom languish outside the VA housing system. Since that time, progress has been made with point-in-time enumerations indicating that veteran homelessness has decreased nationally. Despite this progress, however, more than 55,000 veterans are still estimated to experience homelessness each night.²

Historically, the VA has offered an array of services specifically meant to alleviate veteran homelessness (grant, per diem, and other transitional housing programs; vocational rehabilitation, etc).³ The majority of these programs require some period of veteran abstinence as a condition for providing housing services. The recent move toward permanent “housing first” programs with few conditions for enrollment and participation provides new opportunities for housing veterans experiencing chronic homelessness, who are the specific target of the goal of ending veteran homelessness.⁴

Because veterans experiencing chronic homelessness have additional, substantial need for medical, psychiatric, and substance-abuse services, the VA also offers these services to this population.^5-7 Veterans experiencing homelessness also may access parallel non-VA services.⁸ Information about veterans outside of traditional VA housing services, specifically those housed in low-demand shelters, is needed to develop services for this population and will be critical to success in ending veteran homelessness.

The Behavioral Model of Health Services Use^9-11 and its later refinement, the Behavioral Model for Vulnerable Persons,¹² have been used to conceptualize health care service use (Figure). In these models, health service use is predicted by 3 types of factors: predisposing factors (eg, age, race, gender, residential history), enabling factors (eg, availability, accessibility, affordability, acceptability), and service need factors (eg, substance-use disorders, mental health problems, physical health problems).

Studies applying these models of health care service use to both general homeless populations and, specifically to populations of veterans experiencing homelessness have found that service use is most influenced by need-based factors (eg, drug abuse, poor health, mental health problems).^6,12-20 These same studies indicate that predisposing factors (eg, age, race, and gender) and enabling factors (eg, insurance, use of other services, and usual place of care) are also associated with service use, though less consistently.

Studies focused on veterans experiencing homelessness, however, included only treatment-seeking populations, which are not necessarily representative of the broader population of veterans experiencing homelessness. Additionally, none of these prior studies focused on the unique subset of veterans residing in low-demand shelters (characterized by unlimited duration of stay, no government ID or fee required for entry, and no requirement for service participation). This is a population that seems to be less engaged in services but nevertheless is challenged.²¹ This study, therefore, is focused on nontreatment seeking veterans residing in a low-demand shelter. The study applied the Behavioral Model of Health Services Use and the Behavioral Model for Vulnerable Persons to examine use of VA and non-VA services.

Study Parameters

This study was conducted in Fort Worth, Texas, the 17th largest city in the U.S. with more than 810,000 residents.²² In 2013, a biennial point-in-time count identified about 2,300 individuals who were homeless in Fort Worth. Most were found in emergency shelters (n = 1,126, 50%) or transitional housing (n = 965, 40%). Slightly more than 10% (n = 281) were found to be unsheltered: sleeping on the streets or in encampments, automobiles, or abandoned buildings.²³ Although national estimates identify 12% of all adults who are homeless as veterans,² only 8% (n = 189) of people experiencing homelessness in Fort Worth reported military service.²³

Access to the full array of VA emergency department (ED), inpatient, and outpatient medical, psychiatric, and substance-abuse services are available to veterans experiencing homelessness at the Dallas VA Medical Center (DVAMC), located 35 miles away. Only VA outpatient medical, psychiatric, and substance-related services are available in Fort Worth through the VA Outpatient Clinic and Health Care for the Homeless Veterans (HCHV) program. If veterans experiencing homelessness seek care outside of the VA system, a comprehensive network of emergency, inpatient and outpatient medical, psychiatric, and substance-related services is available in Fort Worth.

Sample

The study sample included 110 adult male veterans randomly recruited as they awaited admission to a private, low-demand emergency shelter. The study excluded veterans with a dishonorable discharge to ensure participants were eligible for VA services. Institutional review board approvals were obtained prior to the study from the University of Texas at Arlington and DVAMC. All participants provided informed consent and were given a $5 gift for their involvement.

Instruments

Through structured interviews, experienced research staff collected demographics, history of homelessness, military service, and substance abuse in the previous 30 days. Data on alcohol and drug problems in the past 12 months were obtained using the Short Michigan Alcohol Screening Test (SMAST) and the Drug Abuse Screening Test. The Veterans RAND 12-Item Health Survey (VR-12) was used to measure physical and mental health functioning in the previous 4 weeks. Finally, participants reported their use of VA or non-VA medical (ED, inpatient, and outpatient), psychiatric (ED, inpatient, and outpatient), and substance abuse-related (inpatient and outpatient) services in the 12 months prior to the interview. These measures have been shown to be valid and reliable with acceptable psychometrics.^24-26

Data Analysis

Statistical analysis was completed using IBM SPSS Statistics version 19. Descriptive data were summarized using counts, percentages, means, and standard deviations. A dichotomous variable for alcohol abuse was defined as SMAST score ≥ 3. A variable representing participant’s VR-12 mental component summary scores was used as an indicator of mental health functioning.

McNemar’s test was used to compare the use of VA and non-VA medical, psychiatric, and substance-related services using dichotomous variables for each overall sector as well as respective sector subcomponent services (emergency, inpatient, and outpatient for medical and psychiatric sectors and inpatient and outpatient for the substance-related sector). Statistical significance level was set at α = .05.

Logistic regression was used to predict psychiatric and substance abuse-related service use with separate dependent variables for VA, non-VA, and both VA and non-VA services. Need-based factors included in all models as independent variables were mental health functioning, alcohol abuse, and a dichotomous variable representing cocaine use in the previous 30 days. Independent variables for the other service sectors were included as enabling factors (eg, medical and substance-related problems predicting psychiatric service use), aligning all service use variables in the model to the same provider system (eg, VA service sector independent variables with VA service sector dependent variables).

Results

The sample mean age was 49.2 years (SD = 9.2), and fewer than half (n = 45, 41%) were white. Three-fourths (n = 82, 75%) had ever been married, and few participants (n = 5, 5%) were currently married. Total mean lifetime experience of homelessness was 3.9 years (SD = 4.3). One-third of the samples participants (n = 36, 33%) reported that their current episode of homelessness had lasted 1 year or longer. Most had an adult felony conviction (n = 78, 71%) and a history of incarceration as an adult (n = 104, 95%). All military branches were represented, with 49% serving in the Army, 23% in the Marine Corps, 17% in the Navy, 10% in the Air Force, and 1% in the Coast Guard.

Most of the sample’s veterans served during the Vietnam era (n = 43, 43%) or the post-Vietnam era (n = 49, 45%), but 12 (11%) served during the Persian Gulf era (including Operation Iraqi Freedom and Operation Enduring Freedom). Few received a nonservice connected VA pension (n = 21, 19%) or service-connected disability benefits (n = 20, 18%). The mean income earned in the previous 30 days was $466 (SD = $431). None of these predisposing factors were associated with any service variables.

The sample’s mean VR-12 physical functioning score was 43.8 (SD = 9.1), which was significantly higher (t = 6.2, df = 109, P < .001) than the 38.4 (SD = 12.2) population norm used with the instrument. The sample’s mean mental health functioning score of 39.4 (SD = 14.3) was significantly lower (t = -8.6, df = 109, P < .001) than the population norm (51.1, SD = 11.4).²⁷ Substance-related problems were prevalent, with an identified alcohol problem in 62% (n = 68) and a drug problem in 79% (n = 87) of participants. More than half reported illicit drug use in the past 30 days (n = 61, 56%), especially cocaine (n = 42, 38%) and marijuana (n = 37, 33%).

The majority of veterans (n = 96, 87%) reported using some type of service in the past 12 months (Table 1). Most survey respondents used medical services. About half used psychiatric services, and almost one-third used substance-related services. More veterans used non-VA ED services than used VA ED services. More veterans used VA outpatient medical services than used non-VA outpatient medical services. Examining service sectors indicated that more veterans used VA psychiatric services than used non-VA psychiatric services, especially VA outpatient psychiatric services. More veterans used non-VA substance abuse-related services, especially outpatient services, rather than similar services offered by the VA.

Separate logistic regression models predicted use of psychiatric and substance-abuse services with 3 models (VA, non-VA, or any service use) for each dependent variable from independent variables that reflected need and enabling factors (Tables 2 and 3). Demographic predisposing factors, which were not associated with service use, were not included as covariates in these models. For the model predicting the use of non-VA substance-abuse services, collinearity between the alcohol-abuse and cocaine-abuse variables required separate models for each of the 2 variables.

Medical sector service use predicted psychiatric sector service use in all models. In fact, VA medical service use was the only predictor of use of VA psychiatric services. Lower mental health functioning predicted the use of any (VA or non-VA) psychiatric service use. In addition to the use of medical services, 30-day cocaine use predicted non-VA psychiatric service use.

Any substance-related sector service use was predicted by lower mental health functioning, self-reported alcohol problem, and any medical services utilization. No independent variables included in the model predicted any VA substance-related service use. Non-VA substance abuse service use was predicted by non-VA psychiatric service use and alcohol abuse. In the separate analysis that replaced alcohol problems with 30-day cocaine use variable, only 30-day cocaine use predicted non-VA substance-related service utilization.

Discussion

This study examined the use of medical, psychiatric, and substance-abuse services by randomly sampled veterans from a low-demand emergency shelter. Random selection of the sample and its high (98%) participation rate virtually eliminated potential for bias within this sample. Another strength of this study is its focus on low-demand shelter users—a population that has not been well studied. This low-demand shelter-dwelling population of veterans experiencing homelessness is of interest because more substance-abuse problems and histories of incarceration seem to make them especially disadvantaged and challenged.

The limitation of the sample to users of a low-demand shelter at only 1 location may reduce generalizability to other veteran homeless populations and settings. The study also may not generalize to populations of female veterans experiencing homelessness. Another limitation of the study is that it did not use diagnostic assessments for psychiatric and substance use disorders and objective collateral information such as agency record data. Finally, although the limited size of the sample may have been insufficient to adequately test certain hypotheses, it was a relatively large sample of this population and was large enough to yield significant findings.

This study found that need-based factors predicted the use of some service sectors intended for those needs. For example, mental health functioning appropriately predicted any psychiatric service use, and presence of an alcohol problem appropriately predicted any substance abuse service use. Specifically for non-VA services, both cocaine use and presence of an alcohol problem in separate models predicted substance-abuse service use. However for VA substance-abuse services, neither cocaine use nor presence of an alcohol problem predicted service use. Despite the high need, very few veterans used substance-abuse services, and they rarely used VA substance-abuse services.

For 2 service sectors, need-based factors predicted the use of services intended for other needs. Cocaine use predicted non-VA psychiatric service use, and low mental health functioning predicted substance-abuse service use. One potential explanation for this finding could be that providers or patients incorrectly classified cocaine-related substance use problems as psychiatric. The VR-12 mental health functioning measure also may have incorrectly classified cocaine-related problems as psychiatric.

Three enabling factors predicted service use by sector and type. The first 2 are preference for VA-provided services and the geographic availability of services, which competed for veterans’ selection of service providers. When both VA and non-VA services were present in Fort Worth, a preference for VA-provided services was observed, with the exception of outpatient substance abuse services which were highly underutilized in general. No preference was observed for any non-VA services when both were present. When VA services were not present in Fort Worth, veterans used geographically available non-VA providers for some services, but for other services they used Dallas-based VA and Fort Worth-based non-VA providers equally (Table 3 and Table 4).

The third enabling factor influencing service use was through other service use as an enabling pathway. Those veterans who opted out of locally available services in favor of VA services in Dallas may have been prompted to do so by provider referrals, which were further facilitated by VA and public transportation between Fort Worth and Dallas. The most consistent enabling pathway was medical service use, which predicted all types of psychiatric service use (VA and non-VA combined, VA only, and non-VA only), and any substance-related service use. Psychiatric service use predicted substance abuse service use but only in non-VA settings; no pathways led from VA medical or psychiatric services to VA substance abuse services.

Conclusions

These findings suggest, in large part, the validity of the Andersen and Gelberg models of health care service use. Consistent with prior studies, need-based factors predicted the use of any psychiatric and substance-related sector services as well as the use of non-VA subcomponent services for both sectors. Also consistent with prior studies, enabling factors (medical sector service use) predicted service use, with the exception of VA or non-VA substance-abuse services. Unlike prior studies, however, predisposing factors (eg, age, race, marital status, and income) were not associated with service use.

This study could not determine why veterans underutilized substance-abuse services, even those available locally to them in Fort Worth. One possible barrier to care is that the services are designed or delivered in a manner that does not engage these veterans (eg, expectations regarding abstinence or service involvement). Another barrier could be that referral pathways between VA outpatient medical and psychiatric service providers and VA substance-related services are not sufficiently facilitative. Future investigations could build upon the findings of this study by collecting data that could help assess these potential barriers.

The data from this study suggest 3 opportunities to improve the utilization of services most needed by this population. The first opportunity would be to accurately differentiate between substance abuse and psychiatric problems in clinical assessment and identify the most appropriate type of care. Another opportunity, linked closely to the first, would be to facilitate more effective and efficient referral pathways among VA service sectors, especially from medical and psychiatric services to substance-abuse services. Another strategy to improve referral pathways would be for VA service networks to systematically examine local service systems for factors or processes that may disrupt integrated care and implement program improvements.²⁸ For homeless veterans navigating an inherently complex VA health care system, peer-to-peer and patient navigator programs have helped improve service efficiency and service outcomes.²⁹ The third opportunity to improve utilization of services would be to ensure geographic availability and accessibility by strategic placement of these services.

The results from this study, while informative, point directly to needed areas for further inquiry to inform public health response. Although the low-demand shelter users are a particularly challenging subgroup of veterans experiencing chronic homelessness, other equally challenging populations warrant additional study. For example, veterans outside of both VA and community services (eg, unsheltered populations) are likely to require different approaches to engage in appropriate services. Additionally, changes to the homeless policy implemented in the period after this sample was recruited suggest the need to revisit the service-using behaviors of this population. Finally, interventions developed as part of the national response need to be assessed for their ability to engage these difficult-to-reach veterans.

Acknowledgements
This study was funded by a U.S. Department of Veterans Affairs Office of Academic Affiliations Pre-Doctoral Social Work Research Fellowship award.

In 2009, the VA announced a goal of ending veteran homelessness by 2015.¹ The primary focus of this new policy has been housing veterans experiencing chronic homelessness, many of whom languish outside the VA housing system. Since that time, progress has been made with point-in-time enumerations indicating that veteran homelessness has decreased nationally. Despite this progress, however, more than 55,000 veterans are still estimated to experience homelessness each night.²

Historically, the VA has offered an array of services specifically meant to alleviate veteran homelessness (grant, per diem, and other transitional housing programs; vocational rehabilitation, etc).³ The majority of these programs require some period of veteran abstinence as a condition for providing housing services. The recent move toward permanent “housing first” programs with few conditions for enrollment and participation provides new opportunities for housing veterans experiencing chronic homelessness, who are the specific target of the goal of ending veteran homelessness.⁴

Because veterans experiencing chronic homelessness have additional, substantial need for medical, psychiatric, and substance-abuse services, the VA also offers these services to this population.^5-7 Veterans experiencing homelessness also may access parallel non-VA services.⁸ Information about veterans outside of traditional VA housing services, specifically those housed in low-demand shelters, is needed to develop services for this population and will be critical to success in ending veteran homelessness.

The Behavioral Model of Health Services Use^9-11 and its later refinement, the Behavioral Model for Vulnerable Persons,¹² have been used to conceptualize health care service use (Figure). In these models, health service use is predicted by 3 types of factors: predisposing factors (eg, age, race, gender, residential history), enabling factors (eg, availability, accessibility, affordability, acceptability), and service need factors (eg, substance-use disorders, mental health problems, physical health problems).

Studies applying these models of health care service use to both general homeless populations and, specifically to populations of veterans experiencing homelessness have found that service use is most influenced by need-based factors (eg, drug abuse, poor health, mental health problems).^6,12-20 These same studies indicate that predisposing factors (eg, age, race, and gender) and enabling factors (eg, insurance, use of other services, and usual place of care) are also associated with service use, though less consistently.

Studies focused on veterans experiencing homelessness, however, included only treatment-seeking populations, which are not necessarily representative of the broader population of veterans experiencing homelessness. Additionally, none of these prior studies focused on the unique subset of veterans residing in low-demand shelters (characterized by unlimited duration of stay, no government ID or fee required for entry, and no requirement for service participation). This is a population that seems to be less engaged in services but nevertheless is challenged.²¹ This study, therefore, is focused on nontreatment seeking veterans residing in a low-demand shelter. The study applied the Behavioral Model of Health Services Use and the Behavioral Model for Vulnerable Persons to examine use of VA and non-VA services.

Study Parameters

This study was conducted in Fort Worth, Texas, the 17th largest city in the U.S. with more than 810,000 residents.²² In 2013, a biennial point-in-time count identified about 2,300 individuals who were homeless in Fort Worth. Most were found in emergency shelters (n = 1,126, 50%) or transitional housing (n = 965, 40%). Slightly more than 10% (n = 281) were found to be unsheltered: sleeping on the streets or in encampments, automobiles, or abandoned buildings.²³ Although national estimates identify 12% of all adults who are homeless as veterans,² only 8% (n = 189) of people experiencing homelessness in Fort Worth reported military service.²³

Access to the full array of VA emergency department (ED), inpatient, and outpatient medical, psychiatric, and substance-abuse services are available to veterans experiencing homelessness at the Dallas VA Medical Center (DVAMC), located 35 miles away. Only VA outpatient medical, psychiatric, and substance-related services are available in Fort Worth through the VA Outpatient Clinic and Health Care for the Homeless Veterans (HCHV) program. If veterans experiencing homelessness seek care outside of the VA system, a comprehensive network of emergency, inpatient and outpatient medical, psychiatric, and substance-related services is available in Fort Worth.

Sample

The study sample included 110 adult male veterans randomly recruited as they awaited admission to a private, low-demand emergency shelter. The study excluded veterans with a dishonorable discharge to ensure participants were eligible for VA services. Institutional review board approvals were obtained prior to the study from the University of Texas at Arlington and DVAMC. All participants provided informed consent and were given a $5 gift for their involvement.

Instruments

Through structured interviews, experienced research staff collected demographics, history of homelessness, military service, and substance abuse in the previous 30 days. Data on alcohol and drug problems in the past 12 months were obtained using the Short Michigan Alcohol Screening Test (SMAST) and the Drug Abuse Screening Test. The Veterans RAND 12-Item Health Survey (VR-12) was used to measure physical and mental health functioning in the previous 4 weeks. Finally, participants reported their use of VA or non-VA medical (ED, inpatient, and outpatient), psychiatric (ED, inpatient, and outpatient), and substance abuse-related (inpatient and outpatient) services in the 12 months prior to the interview. These measures have been shown to be valid and reliable with acceptable psychometrics.^24-26

Data Analysis

Statistical analysis was completed using IBM SPSS Statistics version 19. Descriptive data were summarized using counts, percentages, means, and standard deviations. A dichotomous variable for alcohol abuse was defined as SMAST score ≥ 3. A variable representing participant’s VR-12 mental component summary scores was used as an indicator of mental health functioning.

McNemar’s test was used to compare the use of VA and non-VA medical, psychiatric, and substance-related services using dichotomous variables for each overall sector as well as respective sector subcomponent services (emergency, inpatient, and outpatient for medical and psychiatric sectors and inpatient and outpatient for the substance-related sector). Statistical significance level was set at α = .05.

Logistic regression was used to predict psychiatric and substance abuse-related service use with separate dependent variables for VA, non-VA, and both VA and non-VA services. Need-based factors included in all models as independent variables were mental health functioning, alcohol abuse, and a dichotomous variable representing cocaine use in the previous 30 days. Independent variables for the other service sectors were included as enabling factors (eg, medical and substance-related problems predicting psychiatric service use), aligning all service use variables in the model to the same provider system (eg, VA service sector independent variables with VA service sector dependent variables).

Results

The sample mean age was 49.2 years (SD = 9.2), and fewer than half (n = 45, 41%) were white. Three-fourths (n = 82, 75%) had ever been married, and few participants (n = 5, 5%) were currently married. Total mean lifetime experience of homelessness was 3.9 years (SD = 4.3). One-third of the samples participants (n = 36, 33%) reported that their current episode of homelessness had lasted 1 year or longer. Most had an adult felony conviction (n = 78, 71%) and a history of incarceration as an adult (n = 104, 95%). All military branches were represented, with 49% serving in the Army, 23% in the Marine Corps, 17% in the Navy, 10% in the Air Force, and 1% in the Coast Guard.

Most of the sample’s veterans served during the Vietnam era (n = 43, 43%) or the post-Vietnam era (n = 49, 45%), but 12 (11%) served during the Persian Gulf era (including Operation Iraqi Freedom and Operation Enduring Freedom). Few received a nonservice connected VA pension (n = 21, 19%) or service-connected disability benefits (n = 20, 18%). The mean income earned in the previous 30 days was $466 (SD = $431). None of these predisposing factors were associated with any service variables.

The sample’s mean VR-12 physical functioning score was 43.8 (SD = 9.1), which was significantly higher (t = 6.2, df = 109, P < .001) than the 38.4 (SD = 12.2) population norm used with the instrument. The sample’s mean mental health functioning score of 39.4 (SD = 14.3) was significantly lower (t = -8.6, df = 109, P < .001) than the population norm (51.1, SD = 11.4).²⁷ Substance-related problems were prevalent, with an identified alcohol problem in 62% (n = 68) and a drug problem in 79% (n = 87) of participants. More than half reported illicit drug use in the past 30 days (n = 61, 56%), especially cocaine (n = 42, 38%) and marijuana (n = 37, 33%).

The majority of veterans (n = 96, 87%) reported using some type of service in the past 12 months (Table 1). Most survey respondents used medical services. About half used psychiatric services, and almost one-third used substance-related services. More veterans used non-VA ED services than used VA ED services. More veterans used VA outpatient medical services than used non-VA outpatient medical services. Examining service sectors indicated that more veterans used VA psychiatric services than used non-VA psychiatric services, especially VA outpatient psychiatric services. More veterans used non-VA substance abuse-related services, especially outpatient services, rather than similar services offered by the VA.

Separate logistic regression models predicted use of psychiatric and substance-abuse services with 3 models (VA, non-VA, or any service use) for each dependent variable from independent variables that reflected need and enabling factors (Tables 2 and 3). Demographic predisposing factors, which were not associated with service use, were not included as covariates in these models. For the model predicting the use of non-VA substance-abuse services, collinearity between the alcohol-abuse and cocaine-abuse variables required separate models for each of the 2 variables.

Medical sector service use predicted psychiatric sector service use in all models. In fact, VA medical service use was the only predictor of use of VA psychiatric services. Lower mental health functioning predicted the use of any (VA or non-VA) psychiatric service use. In addition to the use of medical services, 30-day cocaine use predicted non-VA psychiatric service use.

Any substance-related sector service use was predicted by lower mental health functioning, self-reported alcohol problem, and any medical services utilization. No independent variables included in the model predicted any VA substance-related service use. Non-VA substance abuse service use was predicted by non-VA psychiatric service use and alcohol abuse. In the separate analysis that replaced alcohol problems with 30-day cocaine use variable, only 30-day cocaine use predicted non-VA substance-related service utilization.

Discussion

This study examined the use of medical, psychiatric, and substance-abuse services by randomly sampled veterans from a low-demand emergency shelter. Random selection of the sample and its high (98%) participation rate virtually eliminated potential for bias within this sample. Another strength of this study is its focus on low-demand shelter users—a population that has not been well studied. This low-demand shelter-dwelling population of veterans experiencing homelessness is of interest because more substance-abuse problems and histories of incarceration seem to make them especially disadvantaged and challenged.

The limitation of the sample to users of a low-demand shelter at only 1 location may reduce generalizability to other veteran homeless populations and settings. The study also may not generalize to populations of female veterans experiencing homelessness. Another limitation of the study is that it did not use diagnostic assessments for psychiatric and substance use disorders and objective collateral information such as agency record data. Finally, although the limited size of the sample may have been insufficient to adequately test certain hypotheses, it was a relatively large sample of this population and was large enough to yield significant findings.

This study found that need-based factors predicted the use of some service sectors intended for those needs. For example, mental health functioning appropriately predicted any psychiatric service use, and presence of an alcohol problem appropriately predicted any substance abuse service use. Specifically for non-VA services, both cocaine use and presence of an alcohol problem in separate models predicted substance-abuse service use. However for VA substance-abuse services, neither cocaine use nor presence of an alcohol problem predicted service use. Despite the high need, very few veterans used substance-abuse services, and they rarely used VA substance-abuse services.

For 2 service sectors, need-based factors predicted the use of services intended for other needs. Cocaine use predicted non-VA psychiatric service use, and low mental health functioning predicted substance-abuse service use. One potential explanation for this finding could be that providers or patients incorrectly classified cocaine-related substance use problems as psychiatric. The VR-12 mental health functioning measure also may have incorrectly classified cocaine-related problems as psychiatric.

Three enabling factors predicted service use by sector and type. The first 2 are preference for VA-provided services and the geographic availability of services, which competed for veterans’ selection of service providers. When both VA and non-VA services were present in Fort Worth, a preference for VA-provided services was observed, with the exception of outpatient substance abuse services which were highly underutilized in general. No preference was observed for any non-VA services when both were present. When VA services were not present in Fort Worth, veterans used geographically available non-VA providers for some services, but for other services they used Dallas-based VA and Fort Worth-based non-VA providers equally (Table 3 and Table 4).

The third enabling factor influencing service use was through other service use as an enabling pathway. Those veterans who opted out of locally available services in favor of VA services in Dallas may have been prompted to do so by provider referrals, which were further facilitated by VA and public transportation between Fort Worth and Dallas. The most consistent enabling pathway was medical service use, which predicted all types of psychiatric service use (VA and non-VA combined, VA only, and non-VA only), and any substance-related service use. Psychiatric service use predicted substance abuse service use but only in non-VA settings; no pathways led from VA medical or psychiatric services to VA substance abuse services.

Conclusions

These findings suggest, in large part, the validity of the Andersen and Gelberg models of health care service use. Consistent with prior studies, need-based factors predicted the use of any psychiatric and substance-related sector services as well as the use of non-VA subcomponent services for both sectors. Also consistent with prior studies, enabling factors (medical sector service use) predicted service use, with the exception of VA or non-VA substance-abuse services. Unlike prior studies, however, predisposing factors (eg, age, race, marital status, and income) were not associated with service use.

This study could not determine why veterans underutilized substance-abuse services, even those available locally to them in Fort Worth. One possible barrier to care is that the services are designed or delivered in a manner that does not engage these veterans (eg, expectations regarding abstinence or service involvement). Another barrier could be that referral pathways between VA outpatient medical and psychiatric service providers and VA substance-related services are not sufficiently facilitative. Future investigations could build upon the findings of this study by collecting data that could help assess these potential barriers.

The data from this study suggest 3 opportunities to improve the utilization of services most needed by this population. The first opportunity would be to accurately differentiate between substance abuse and psychiatric problems in clinical assessment and identify the most appropriate type of care. Another opportunity, linked closely to the first, would be to facilitate more effective and efficient referral pathways among VA service sectors, especially from medical and psychiatric services to substance-abuse services. Another strategy to improve referral pathways would be for VA service networks to systematically examine local service systems for factors or processes that may disrupt integrated care and implement program improvements.²⁸ For homeless veterans navigating an inherently complex VA health care system, peer-to-peer and patient navigator programs have helped improve service efficiency and service outcomes.²⁹ The third opportunity to improve utilization of services would be to ensure geographic availability and accessibility by strategic placement of these services.

The results from this study, while informative, point directly to needed areas for further inquiry to inform public health response. Although the low-demand shelter users are a particularly challenging subgroup of veterans experiencing chronic homelessness, other equally challenging populations warrant additional study. For example, veterans outside of both VA and community services (eg, unsheltered populations) are likely to require different approaches to engage in appropriate services. Additionally, changes to the homeless policy implemented in the period after this sample was recruited suggest the need to revisit the service-using behaviors of this population. Finally, interventions developed as part of the national response need to be assessed for their ability to engage these difficult-to-reach veterans.

Acknowledgements
This study was funded by a U.S. Department of Veterans Affairs Office of Academic Affiliations Pre-Doctoral Social Work Research Fellowship award.

Faced with a patient who had a massive retroperitoneal hemorrhage, clinicians from Saint Vincent Hospital in Worcester, Massachusetts, had to decide whether the patient had multiple myeloma or plasma cell leukemia,

The patient, a 64-year-old woman, came to the emergency department (ED) with month-long worsening, debilitating lower back pain. She also had a low-grade fever, shortness of breath for about 3 weeks, and weight loss of 10 pounds.

One month earlier, she had visited the ED for right lower quadrant pain and was discharged with the diagnosis of diverticulitis. An abdominal computed tomography (CT) scan revealed incidental splenomegaly. When she next came to the ED, an abdominal examination revealed rigidity, distention, tender splenomegaly, and Grey Turner’s sign. A neurologic examination revealed weakness and numbness with hyperreflexia in her lower legs. Another CT scan showed that the splenomegaly had worsened, and magneting resonance imaging (MRI) showed a compressed spinal cord.

The patient was in severe hemorrhagic shock and was transferred to the intensive care unit. Based on the clinical and laboratory data, the clinicians excluded plasma cell leukemia, since the peripheral blood showed < 20% plasma cells—the major criterion for diagnosing the condition. In the absence of a bleeding disorder, vascular disease, and anticoagulation medications, the authors say their case illustrates a rare and aggressive form of multiple myeloma. The clinical presentation with major spontaneous bleeding is uncommon. In fact, they say, it’s the first time this type of presentation has been reported in the medical literature.

Source: Alawadhi A, Leb L. Case Rep Hematol. 2016;2016:1-3.
doi:10.1155/2016/8206826.

Faced with a patient who had a massive retroperitoneal hemorrhage, clinicians from Saint Vincent Hospital in Worcester, Massachusetts, had to decide whether the patient had multiple myeloma or plasma cell leukemia,

The patient, a 64-year-old woman, came to the emergency department (ED) with month-long worsening, debilitating lower back pain. She also had a low-grade fever, shortness of breath for about 3 weeks, and weight loss of 10 pounds.

One month earlier, she had visited the ED for right lower quadrant pain and was discharged with the diagnosis of diverticulitis. An abdominal computed tomography (CT) scan revealed incidental splenomegaly. When she next came to the ED, an abdominal examination revealed rigidity, distention, tender splenomegaly, and Grey Turner’s sign. A neurologic examination revealed weakness and numbness with hyperreflexia in her lower legs. Another CT scan showed that the splenomegaly had worsened, and magneting resonance imaging (MRI) showed a compressed spinal cord.

The patient was in severe hemorrhagic shock and was transferred to the intensive care unit. Based on the clinical and laboratory data, the clinicians excluded plasma cell leukemia, since the peripheral blood showed < 20% plasma cells—the major criterion for diagnosing the condition. In the absence of a bleeding disorder, vascular disease, and anticoagulation medications, the authors say their case illustrates a rare and aggressive form of multiple myeloma. The clinical presentation with major spontaneous bleeding is uncommon. In fact, they say, it’s the first time this type of presentation has been reported in the medical literature.

Source: Alawadhi A, Leb L. Case Rep Hematol. 2016;2016:1-3.
doi:10.1155/2016/8206826.

Faced with a patient who had a massive retroperitoneal hemorrhage, clinicians from Saint Vincent Hospital in Worcester, Massachusetts, had to decide whether the patient had multiple myeloma or plasma cell leukemia,

The patient, a 64-year-old woman, came to the emergency department (ED) with month-long worsening, debilitating lower back pain. She also had a low-grade fever, shortness of breath for about 3 weeks, and weight loss of 10 pounds.

One month earlier, she had visited the ED for right lower quadrant pain and was discharged with the diagnosis of diverticulitis. An abdominal computed tomography (CT) scan revealed incidental splenomegaly. When she next came to the ED, an abdominal examination revealed rigidity, distention, tender splenomegaly, and Grey Turner’s sign. A neurologic examination revealed weakness and numbness with hyperreflexia in her lower legs. Another CT scan showed that the splenomegaly had worsened, and magneting resonance imaging (MRI) showed a compressed spinal cord.

The patient was in severe hemorrhagic shock and was transferred to the intensive care unit. Based on the clinical and laboratory data, the clinicians excluded plasma cell leukemia, since the peripheral blood showed < 20% plasma cells—the major criterion for diagnosing the condition. In the absence of a bleeding disorder, vascular disease, and anticoagulation medications, the authors say their case illustrates a rare and aggressive form of multiple myeloma. The clinical presentation with major spontaneous bleeding is uncommon. In fact, they say, it’s the first time this type of presentation has been reported in the medical literature.

Source: Alawadhi A, Leb L. Case Rep Hematol. 2016;2016:1-3.
doi:10.1155/2016/8206826.