Original Research

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.

When given a choice between VA and non-VA outpatient services in Fort Worth, significantly more veterans chose to use VA medical and psychiatric services, but outpatient substance abuse-related services were used equally. For ED and inpatient services, more veterans selected non-VA ED medical and inpatient substance abuse-related services located in Fort Worth than comparable VA services available in Dallas. There were no differences between use of VA and non-VA services for emergency psychiatric, inpatient medical, and psychiatric services, even though these services were available only in Dallas.

 

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.

When given a choice between VA and non-VA outpatient services in Fort Worth, significantly more veterans chose to use VA medical and psychiatric services, but outpatient substance abuse-related services were used equally. For ED and inpatient services, more veterans selected non-VA ED medical and inpatient substance abuse-related services located in Fort Worth than comparable VA services available in Dallas. There were no differences between use of VA and non-VA services for emergency psychiatric, inpatient medical, and psychiatric services, even though these services were available only in Dallas.

 

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.

When given a choice between VA and non-VA outpatient services in Fort Worth, significantly more veterans chose to use VA medical and psychiatric services, but outpatient substance abuse-related services were used equally. For ED and inpatient services, more veterans selected non-VA ED medical and inpatient substance abuse-related services located in Fort Worth than comparable VA services available in Dallas. There were no differences between use of VA and non-VA services for emergency psychiatric, inpatient medical, and psychiatric services, even though these services were available only in Dallas.

 

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.