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Drug Overdose and Suicide Among Veteran Enrollees in the VHA: Comparison Among Local, Regional, and National Data
Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.1 In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.2,3
Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.3 About one-half of VHA veterans have been diagnosed with chronic pain.4 A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.5
One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.4 Increased prescribing of opioid medications has been associated with opioid overdose and suicides.6-10 Opioids are the most common drugs found in suicide by overdose.11 The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.12 The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.13
In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.14 Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.15 In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).16
The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.17 To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.
The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.18
The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.19 Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.19 The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.18
Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.20 However, another study suggested a risk of increased pain with opioid tapering.21 The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.22 Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.23 However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.10 The link between opioid tapering and the risk of suicide or overdose is uncertain.
Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.7 Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,7 such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.
Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,18 this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.
Methods
In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.
Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.
In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.24 The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.25
This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.
Results
Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).
From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.
Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).
This study shows that NF/SGVHS had the lowest average annual rate of suicide (9.1 per 100,000) during the study period, which was 4 times lower than that of VHA national and 2.6 times lower than VISN 8.
Discussion
This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.
First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.14 By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.
Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.7 We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.
Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.
Limitations
The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.26 Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.
Conclusions
The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.
1. American Foundation for Suicide Prevention. Suicide statistics. https://afsp.org/about-suicide/suicide-statistics. Updated 2019. Accessed September 2, 2020.
2. Shane L 3rd. New veteran suicide numbers raise concerns among experts hoping for positive news. https://www.militarytimes.com/news/pentagon-congress/2019/10/09/new-veteran-suicide-numbers-raise-concerns-among-experts-hoping-for-positive-news. Published October 9, 2019. Accessed July 23, 2020.
3. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Veteran suicide data report, 2005–2017. https://www.mentalhealth.va.gov/docs/data-sheets/2019/2019_National_Veteran_Suicide_Prevention_Annual_Report_508.pdf. Published September 2019. Accessed July 20, 2020.
4. Gallagher RM. Advancing the pain agenda in the veteran population. Anesthesiol Clin. 2016;34(2):357-378. doi:10.1016/j.anclin.2016.01.003
5. Ilgen MA, Kleinberg F, Ignacio RV, et al. Noncancer pain conditions and risk of suicide. JAMA Psychiatry. 2013;70(7):692-697. doi:10.1001/jamapsychiatry.2013.908
6. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999-2012. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/products/databriefs/db189.htm. Published February 25, 2015. Accessed July 20, 2020.
7. Bohnert ASB, Ilgen MA. Understanding links among opioid use, overdose, and suicide. N Engl J Med. 2019;380(14):71-79. doi:10.1056/NEJMc1901540
8. Dunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152(2):85-92. doi:10.7326/0003-4819-152-2-201001190-00006
9. Gomes T, Mamdani MM, Dhalla IA, Paterson JM, Juurlink DN. Opioid dose and drug-related mortality in patients with nonmalignant pain. Arch Intern Med. 2011;171(7):686-691. doi:10.1001/archinternmed.2011.117
10. Ilgen MA, Bohnert AS, Ganoczy D, Bair MJ, McCarthy JF, Blow FC. Opioid dose and risk of suicide. Pain. 2016;157(5):1079-1084. doi:10.1097/j.pain.0000000000000484
11. Sinyor M, Howlett A, Cheung AH, Schaffer A. Substances used in completed suicide by overdose in Toronto: an observational study of coroner’s data. Can J Psychiatry. 2012;57(3):184-191. doi:10.1177/070674371205700308
12. Wilcox HC, Conner KR, Caine ED. Association of alcohol and drug use disorders and completed suicide: an empirical review of cohort studies. Drug Alcohol Depend. 2004;76(suppl):S11-S19 doi:10.1016/j.drugalcdep.2004.08.003.
13. Baser OL, Mardekian XJ, Schaaf D, Wang L, Joshi AV. Prevalence of diagnosed opioid abuse and its economic burden in the Veterans Health Administration. Pain Pract. 2014;14(5):437-445. doi:10.1111/papr.12097
14. Hedegaard H, Warner M, Miniño AM. Drug overdose deaths in the united states, 1999-2015. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/data/databriefs/db273.pdf. Published February 2017. Accessed July 20, 2020.
15. Rudd RA, Seth P, David F, Scholl L. Increases in drug and opioid-involved overdose deaths—United States, 2010-2015. MMWR Morb Mortal Wkly Rep. 2016;65(50-51):1445-1452. doi:10.15585/mmwr.mm655051e1
16. Scholl L, Seth P, Kariisa M, Wilson N, Baldwin G. Drug and opioid-involved overdose deaths—United States, 2013-2017. MMWR Morb Mortal Wkly Rep. 2019,67(5152):1419-1427. doi:10.15585/mmwr.mm675152e1
17. US Department of Veterans Affairs and Department of Defense. VA/DOD clinical practice guideline for opioid therapy for chronic pain version 3.0. https://www.healthquality.va.gov/guidelines/pain/cot. Updated March 1, 2018. Accessed July 20, 2020.
18. Vaughn IA, Beyth RJ, Ayers ML, et al. Multispecialty opioid risk reduction program targeting chronic pain and addiction management in veterans. Fed Pract. 2019;36(9):406-411.
19. Gellad WF, Good CB, Shulkin DJ. Addressing the opioid epidemic in the United States: lessons from the Department of Veterans Affairs. JAMA Intern Med. 2017;177(5):611-612. doi:10.1001/jamainternmed.2017.0147
20. Frank JW, Lovejoy TI, Becker WC, et al. Patient outcomes in dose reduction or discontinuation of long-term opioid therapy: a systematic review. Ann Intern Med. 2017;167(3):181-191. doi:10.7326/M17-0598
21. Berna C, Kulich RJ, Rathmell JP. Tapering long-term opioid therapy in chronic noncancer pain: evidence and recommendations for everyday practice. Mayo Clin Proc. 2015;90(6):828-842. doi:10.1016/j.mayocp.2015.04.003
22. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Opioid use and suicide risk. https://www.mentalhealth.va.gov/suicide_prevention/docs/Literature_Review_Opioid_Use_and_Suicide_Risk_508_FINAL_04-26-2019.pdf. Published April 26, 2019. Accessed July 20, 2020.
23. Demidenko MI, Dobscha SK, Morasco BJ, Meath THA, Ilgen MA, Lovejoy TI. Suicidal ideation and suicidal self-directed violence following clinician-initiated prescription opioid discontinuation among long-term opioid users. Gen Hosp Psychiatry. 2017;47:29-35. doi:10.1016/j.genhosppsych.2017.04.011
24. National Institute on Drug Abuse. Intentional versus unintentional overdose deaths. https://www.drugabuse.gov/related-topics/treatment/intentional-vs-unintentional-overdose-deaths. Updated February 13, 2017. Accessed July 20, 2020.
25. Centers for Disease Control and Prevention. Preventing suicide. https://www.cdc.gov/violenceprevention/pdf/suicide-factsheet.pdf. Published 2018. Accessed July 20, 2020.
26. Webster LR. Pain and suicide: the other side of the opioid story. Pain Med. 2014;15(3):345-346. doi:10.1111/pme.12398
Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.1 In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.2,3
Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.3 About one-half of VHA veterans have been diagnosed with chronic pain.4 A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.5
One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.4 Increased prescribing of opioid medications has been associated with opioid overdose and suicides.6-10 Opioids are the most common drugs found in suicide by overdose.11 The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.12 The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.13
In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.14 Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.15 In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).16
The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.17 To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.
The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.18
The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.19 Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.19 The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.18
Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.20 However, another study suggested a risk of increased pain with opioid tapering.21 The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.22 Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.23 However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.10 The link between opioid tapering and the risk of suicide or overdose is uncertain.
Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.7 Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,7 such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.
Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,18 this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.
Methods
In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.
Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.
In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.24 The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.25
This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.
Results
Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).
From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.
Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).
This study shows that NF/SGVHS had the lowest average annual rate of suicide (9.1 per 100,000) during the study period, which was 4 times lower than that of VHA national and 2.6 times lower than VISN 8.
Discussion
This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.
First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.14 By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.
Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.7 We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.
Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.
Limitations
The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.26 Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.
Conclusions
The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.
Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.1 In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.2,3
Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.3 About one-half of VHA veterans have been diagnosed with chronic pain.4 A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.5
One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.4 Increased prescribing of opioid medications has been associated with opioid overdose and suicides.6-10 Opioids are the most common drugs found in suicide by overdose.11 The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.12 The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.13
In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.14 Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.15 In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).16
The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.17 To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.
The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.18
The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.19 Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.19 The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.18
Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.20 However, another study suggested a risk of increased pain with opioid tapering.21 The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.22 Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.23 However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.10 The link between opioid tapering and the risk of suicide or overdose is uncertain.
Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.7 Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,7 such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.
Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,18 this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.
Methods
In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.
Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.
In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.24 The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.25
This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.
Results
Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).
From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.
Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).
This study shows that NF/SGVHS had the lowest average annual rate of suicide (9.1 per 100,000) during the study period, which was 4 times lower than that of VHA national and 2.6 times lower than VISN 8.
Discussion
This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.
First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.14 By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.
Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.7 We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.
Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.
Limitations
The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.26 Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.
Conclusions
The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.
1. American Foundation for Suicide Prevention. Suicide statistics. https://afsp.org/about-suicide/suicide-statistics. Updated 2019. Accessed September 2, 2020.
2. Shane L 3rd. New veteran suicide numbers raise concerns among experts hoping for positive news. https://www.militarytimes.com/news/pentagon-congress/2019/10/09/new-veteran-suicide-numbers-raise-concerns-among-experts-hoping-for-positive-news. Published October 9, 2019. Accessed July 23, 2020.
3. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Veteran suicide data report, 2005–2017. https://www.mentalhealth.va.gov/docs/data-sheets/2019/2019_National_Veteran_Suicide_Prevention_Annual_Report_508.pdf. Published September 2019. Accessed July 20, 2020.
4. Gallagher RM. Advancing the pain agenda in the veteran population. Anesthesiol Clin. 2016;34(2):357-378. doi:10.1016/j.anclin.2016.01.003
5. Ilgen MA, Kleinberg F, Ignacio RV, et al. Noncancer pain conditions and risk of suicide. JAMA Psychiatry. 2013;70(7):692-697. doi:10.1001/jamapsychiatry.2013.908
6. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999-2012. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/products/databriefs/db189.htm. Published February 25, 2015. Accessed July 20, 2020.
7. Bohnert ASB, Ilgen MA. Understanding links among opioid use, overdose, and suicide. N Engl J Med. 2019;380(14):71-79. doi:10.1056/NEJMc1901540
8. Dunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152(2):85-92. doi:10.7326/0003-4819-152-2-201001190-00006
9. Gomes T, Mamdani MM, Dhalla IA, Paterson JM, Juurlink DN. Opioid dose and drug-related mortality in patients with nonmalignant pain. Arch Intern Med. 2011;171(7):686-691. doi:10.1001/archinternmed.2011.117
10. Ilgen MA, Bohnert AS, Ganoczy D, Bair MJ, McCarthy JF, Blow FC. Opioid dose and risk of suicide. Pain. 2016;157(5):1079-1084. doi:10.1097/j.pain.0000000000000484
11. Sinyor M, Howlett A, Cheung AH, Schaffer A. Substances used in completed suicide by overdose in Toronto: an observational study of coroner’s data. Can J Psychiatry. 2012;57(3):184-191. doi:10.1177/070674371205700308
12. Wilcox HC, Conner KR, Caine ED. Association of alcohol and drug use disorders and completed suicide: an empirical review of cohort studies. Drug Alcohol Depend. 2004;76(suppl):S11-S19 doi:10.1016/j.drugalcdep.2004.08.003.
13. Baser OL, Mardekian XJ, Schaaf D, Wang L, Joshi AV. Prevalence of diagnosed opioid abuse and its economic burden in the Veterans Health Administration. Pain Pract. 2014;14(5):437-445. doi:10.1111/papr.12097
14. Hedegaard H, Warner M, Miniño AM. Drug overdose deaths in the united states, 1999-2015. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/data/databriefs/db273.pdf. Published February 2017. Accessed July 20, 2020.
15. Rudd RA, Seth P, David F, Scholl L. Increases in drug and opioid-involved overdose deaths—United States, 2010-2015. MMWR Morb Mortal Wkly Rep. 2016;65(50-51):1445-1452. doi:10.15585/mmwr.mm655051e1
16. Scholl L, Seth P, Kariisa M, Wilson N, Baldwin G. Drug and opioid-involved overdose deaths—United States, 2013-2017. MMWR Morb Mortal Wkly Rep. 2019,67(5152):1419-1427. doi:10.15585/mmwr.mm675152e1
17. US Department of Veterans Affairs and Department of Defense. VA/DOD clinical practice guideline for opioid therapy for chronic pain version 3.0. https://www.healthquality.va.gov/guidelines/pain/cot. Updated March 1, 2018. Accessed July 20, 2020.
18. Vaughn IA, Beyth RJ, Ayers ML, et al. Multispecialty opioid risk reduction program targeting chronic pain and addiction management in veterans. Fed Pract. 2019;36(9):406-411.
19. Gellad WF, Good CB, Shulkin DJ. Addressing the opioid epidemic in the United States: lessons from the Department of Veterans Affairs. JAMA Intern Med. 2017;177(5):611-612. doi:10.1001/jamainternmed.2017.0147
20. Frank JW, Lovejoy TI, Becker WC, et al. Patient outcomes in dose reduction or discontinuation of long-term opioid therapy: a systematic review. Ann Intern Med. 2017;167(3):181-191. doi:10.7326/M17-0598
21. Berna C, Kulich RJ, Rathmell JP. Tapering long-term opioid therapy in chronic noncancer pain: evidence and recommendations for everyday practice. Mayo Clin Proc. 2015;90(6):828-842. doi:10.1016/j.mayocp.2015.04.003
22. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Opioid use and suicide risk. https://www.mentalhealth.va.gov/suicide_prevention/docs/Literature_Review_Opioid_Use_and_Suicide_Risk_508_FINAL_04-26-2019.pdf. Published April 26, 2019. Accessed July 20, 2020.
23. Demidenko MI, Dobscha SK, Morasco BJ, Meath THA, Ilgen MA, Lovejoy TI. Suicidal ideation and suicidal self-directed violence following clinician-initiated prescription opioid discontinuation among long-term opioid users. Gen Hosp Psychiatry. 2017;47:29-35. doi:10.1016/j.genhosppsych.2017.04.011
24. National Institute on Drug Abuse. Intentional versus unintentional overdose deaths. https://www.drugabuse.gov/related-topics/treatment/intentional-vs-unintentional-overdose-deaths. Updated February 13, 2017. Accessed July 20, 2020.
25. Centers for Disease Control and Prevention. Preventing suicide. https://www.cdc.gov/violenceprevention/pdf/suicide-factsheet.pdf. Published 2018. Accessed July 20, 2020.
26. Webster LR. Pain and suicide: the other side of the opioid story. Pain Med. 2014;15(3):345-346. doi:10.1111/pme.12398
1. American Foundation for Suicide Prevention. Suicide statistics. https://afsp.org/about-suicide/suicide-statistics. Updated 2019. Accessed September 2, 2020.
2. Shane L 3rd. New veteran suicide numbers raise concerns among experts hoping for positive news. https://www.militarytimes.com/news/pentagon-congress/2019/10/09/new-veteran-suicide-numbers-raise-concerns-among-experts-hoping-for-positive-news. Published October 9, 2019. Accessed July 23, 2020.
3. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Veteran suicide data report, 2005–2017. https://www.mentalhealth.va.gov/docs/data-sheets/2019/2019_National_Veteran_Suicide_Prevention_Annual_Report_508.pdf. Published September 2019. Accessed July 20, 2020.
4. Gallagher RM. Advancing the pain agenda in the veteran population. Anesthesiol Clin. 2016;34(2):357-378. doi:10.1016/j.anclin.2016.01.003
5. Ilgen MA, Kleinberg F, Ignacio RV, et al. Noncancer pain conditions and risk of suicide. JAMA Psychiatry. 2013;70(7):692-697. doi:10.1001/jamapsychiatry.2013.908
6. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999-2012. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/products/databriefs/db189.htm. Published February 25, 2015. Accessed July 20, 2020.
7. Bohnert ASB, Ilgen MA. Understanding links among opioid use, overdose, and suicide. N Engl J Med. 2019;380(14):71-79. doi:10.1056/NEJMc1901540
8. Dunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152(2):85-92. doi:10.7326/0003-4819-152-2-201001190-00006
9. Gomes T, Mamdani MM, Dhalla IA, Paterson JM, Juurlink DN. Opioid dose and drug-related mortality in patients with nonmalignant pain. Arch Intern Med. 2011;171(7):686-691. doi:10.1001/archinternmed.2011.117
10. Ilgen MA, Bohnert AS, Ganoczy D, Bair MJ, McCarthy JF, Blow FC. Opioid dose and risk of suicide. Pain. 2016;157(5):1079-1084. doi:10.1097/j.pain.0000000000000484
11. Sinyor M, Howlett A, Cheung AH, Schaffer A. Substances used in completed suicide by overdose in Toronto: an observational study of coroner’s data. Can J Psychiatry. 2012;57(3):184-191. doi:10.1177/070674371205700308
12. Wilcox HC, Conner KR, Caine ED. Association of alcohol and drug use disorders and completed suicide: an empirical review of cohort studies. Drug Alcohol Depend. 2004;76(suppl):S11-S19 doi:10.1016/j.drugalcdep.2004.08.003.
13. Baser OL, Mardekian XJ, Schaaf D, Wang L, Joshi AV. Prevalence of diagnosed opioid abuse and its economic burden in the Veterans Health Administration. Pain Pract. 2014;14(5):437-445. doi:10.1111/papr.12097
14. Hedegaard H, Warner M, Miniño AM. Drug overdose deaths in the united states, 1999-2015. National Center for Health Statistics data brief. https://www.cdc.gov/nchs/data/databriefs/db273.pdf. Published February 2017. Accessed July 20, 2020.
15. Rudd RA, Seth P, David F, Scholl L. Increases in drug and opioid-involved overdose deaths—United States, 2010-2015. MMWR Morb Mortal Wkly Rep. 2016;65(50-51):1445-1452. doi:10.15585/mmwr.mm655051e1
16. Scholl L, Seth P, Kariisa M, Wilson N, Baldwin G. Drug and opioid-involved overdose deaths—United States, 2013-2017. MMWR Morb Mortal Wkly Rep. 2019,67(5152):1419-1427. doi:10.15585/mmwr.mm675152e1
17. US Department of Veterans Affairs and Department of Defense. VA/DOD clinical practice guideline for opioid therapy for chronic pain version 3.0. https://www.healthquality.va.gov/guidelines/pain/cot. Updated March 1, 2018. Accessed July 20, 2020.
18. Vaughn IA, Beyth RJ, Ayers ML, et al. Multispecialty opioid risk reduction program targeting chronic pain and addiction management in veterans. Fed Pract. 2019;36(9):406-411.
19. Gellad WF, Good CB, Shulkin DJ. Addressing the opioid epidemic in the United States: lessons from the Department of Veterans Affairs. JAMA Intern Med. 2017;177(5):611-612. doi:10.1001/jamainternmed.2017.0147
20. Frank JW, Lovejoy TI, Becker WC, et al. Patient outcomes in dose reduction or discontinuation of long-term opioid therapy: a systematic review. Ann Intern Med. 2017;167(3):181-191. doi:10.7326/M17-0598
21. Berna C, Kulich RJ, Rathmell JP. Tapering long-term opioid therapy in chronic noncancer pain: evidence and recommendations for everyday practice. Mayo Clin Proc. 2015;90(6):828-842. doi:10.1016/j.mayocp.2015.04.003
22. Veterans Health Administration, Office of Mental Health and Suicide Prevention. Opioid use and suicide risk. https://www.mentalhealth.va.gov/suicide_prevention/docs/Literature_Review_Opioid_Use_and_Suicide_Risk_508_FINAL_04-26-2019.pdf. Published April 26, 2019. Accessed July 20, 2020.
23. Demidenko MI, Dobscha SK, Morasco BJ, Meath THA, Ilgen MA, Lovejoy TI. Suicidal ideation and suicidal self-directed violence following clinician-initiated prescription opioid discontinuation among long-term opioid users. Gen Hosp Psychiatry. 2017;47:29-35. doi:10.1016/j.genhosppsych.2017.04.011
24. National Institute on Drug Abuse. Intentional versus unintentional overdose deaths. https://www.drugabuse.gov/related-topics/treatment/intentional-vs-unintentional-overdose-deaths. Updated February 13, 2017. Accessed July 20, 2020.
25. Centers for Disease Control and Prevention. Preventing suicide. https://www.cdc.gov/violenceprevention/pdf/suicide-factsheet.pdf. Published 2018. Accessed July 20, 2020.
26. Webster LR. Pain and suicide: the other side of the opioid story. Pain Med. 2014;15(3):345-346. doi:10.1111/pme.12398
Trends in VA Telerehabilitation Patients and Encounters Over Time and by Rurality
Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.1 Travel distance and time are often barriers to accessing health care for many veterans.2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.12,13
A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.14 Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I2, 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I2, 96%) in patients with any diagnosed primary musculoskeletal condition.14
Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.
Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).15 User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.
Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.16 Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,17-19 improve treatment adherence,12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.13,21-24
Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.14 In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.2
Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.
In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.
Methods
The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.
It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:
- Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
- Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
- Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.
In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.
Results
Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1).
Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.
Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.
Trends by Rurality
Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4).
The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.
Discussion
Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.
Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.26
It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.
The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations
With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.
In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.
Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.
Conclusion
Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.
1. Shane L. What’s in the VA secretary’s 10-point plan to reform his department? https://rebootcamp.militarytimes.com/news/pentagon-congress/2017/02/28/what-s-in-the-va-secretary-s-10-point-plan-to-reform-his-department. Published February 28, 2017. Accessed November 21, 2018.
2. Burgess JF, DeFiore DA. The effect of distance to a VA facility on the choice and level of utilization of VA outpatient services. Soc Science Med. 1994;39(1):95-104.
3. LaVela SL, Smith B, Weaver FM, Miskevics SA. Geographical proximity and health care utilization in veterans with SCI&D in the USA. Soc Science Med. 2004;59:2387-2399.
4. Piette JD, Moos RH. The influence of distance on ambulatory care use, death, and readmission following a myocardial infarction. Health Serv Res. 1996;31(5):573-591.
5. Schmitt SK, Phibbs CS, Piette JD. The influence of distance on utilization of outpatient mental health aftercare following inpatient substance abuse treatment. Addictive Behav. 2003;28(6):1183-1192.
6. Fortney JC, Booth BM, Blow FC, Bunn JY. The effects of travel barriers and age on the utilization of alcoholism treatment aftercare. Am J Drug Alcohol Abuse. 1995;21(3):391-406.
7. McCarthy JF, Blow FC, Valenstein M, et al. Veterans Affairs Health System and mental health treatment retention among patients with serious mental illness: evaluating accessibility and availability barriers. Health Serv Res. 2007;42(3):1042-1060.
8. Mooney C, Zwanziger J, Phibbs CS, Schmitt S. Is travel distance a barrier to veterans’ use of VA hospitals for medical surgical care? Soc Sci Med. 2000;50(12):1743-1755.
9. Friedman SA, Frayne SM, Berg E, et al. Travel time and attrition from VHA care among women veterans: how far is too far? Med Care. 2015;53(4)(suppl 1):S15-S22.
10. Buzza C, Ono SS, Turvey C, et al. Distance is relative: unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26(suppl 2):648-654.
11. Goins RT, Williams KA, Carter MW, Spencer SM, Solovieva T. Perceived barriers to health care access among rural older adults: a qualitative study. J Rural Health. 2005;21(3):206-213.
12. Kairy D, Lehoux P, Vincent C, Visintin M. A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disabil Rehabil. 2009;31(6):427-447.
13. McCue M, Fairman A, Pramuka M. Enhancing quality of life through telerehabilitation. Phys Med Rehabil Clin N Am. 2010;21(1):195-205.
14. Cottrell MA, Galea OA, O’Leary SP, Hill AJ, Russell TG. Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis. Clin Rehabil. 2017;31(5):625-638.
15. Pietrzak E, Cotea C, Pullman S, Nasveld P. Self-management and rehabilitation in osteoarthritis: is there a place for internet-based interventions? Telemed J E Health. 2013;19(10):800-805.
16. Agostini M, Moja L, Banzi R, et al. Telerehabilitation and recovery of motor function: a systematic review and meta-analysis. J Telemed Telecare. 2015;21(4):202-213.
17. Kortke H, Stromeyer H, Zittermann A, et al. New East-Westfalian Postoperative Therapy Concept: A telemedicine guide for the study of ambulatory rehabilitation of patients after cardiac surgery. Telemed J E-Health. 2006;12(4):475-483.
18. Tousignant M, Boissy P, Corriveau H, Moffet H. In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of- concept study and costs estimation. Disabil Rehabil Assist Technol. 2006;1(4):209-216.
19. Sanford JA, Griffiths PC, Richardson P, et al. The effects of in-home rehabilitation on task self-efficacy in mobility-impaired adults: a randomized clinical trial. J Am Geriatr Soc. 2006;54(11):1641-1648.
20. Nakamura K, Takano T, Akao C. The effectiveness of videophones in home healthcare for the elderly. Med Care. 1999;37(2):117-125.
21. Levy CE, Silverman E, Jia H, Geiss M, Omura D. Effects of physical therapy delivery via home video telerehabilitation on functional and health-related quality of life outcomes. J Rehabil Res Dev. 2015;52(3):361-370.
22. Guilfoyle C, Wootton R, Hassall S, et al. User satisfaction with allied health services delivered to residential facilities via videoconferencing. J Telemed Telecare. 2003;9(1):S52-S54.23. Mair F, Whitten P. Systematic review of studies of patient satisfaction with telemedicine. BMJ. 2000;320(7248):1517-1520.
24. Williams T L, May C R, Esmail A. Limitations of patient satisfaction studies in telehealthcare: a systematic review of the literature. Telemed J E-Health. 2001;7(4):293-316.
25. US Department of Veterans Affairs, Office of Telehealth Services. http://vaww.telehealth.va.gov/quality/data/index.asp. Accessed June 1, 2018. [Nonpublic document; source not verified.]
26. Jia H, Cowper D, Tang Y, et al. Post-acute stroke rehabilitation utilization: Are there difference between rural-urban patients and taxonomies? J Rural Health. 2012;28(3):242-247.
27. Cho S, Mathiassen L, Gallivan M. Crossing the chasm: from adoption to diffusion of a telehealth innovation. In: León G, Bernardos AM, Casar JR, Kautz K, De Gross JI, eds. Open IT-Based Innovation: Moving Towards Cooperative IT Transfer and Knowledge Diffusion. Boston, MA: Springer; 2008.
28. Broderick A, Lindeman D. Scaling telehealth programs: lessons from early adopters. https://www.commonwealthfund.org/publications/case-study/2013/jan/scaling-telehealth-programs-lessons-early-adopters. Published January 2013. Accessed June 1, 2018.
Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.1 Travel distance and time are often barriers to accessing health care for many veterans.2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.12,13
A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.14 Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I2, 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I2, 96%) in patients with any diagnosed primary musculoskeletal condition.14
Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.
Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).15 User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.
Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.16 Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,17-19 improve treatment adherence,12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.13,21-24
Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.14 In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.2
Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.
In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.
Methods
The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.
It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:
- Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
- Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
- Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.
In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.
Results
Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1).
Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.
Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.
Trends by Rurality
Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4).
The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.
Discussion
Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.
Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.26
It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.
The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations
With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.
In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.
Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.
Conclusion
Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.
Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.1 Travel distance and time are often barriers to accessing health care for many veterans.2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.12,13
A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.14 Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I2, 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I2, 96%) in patients with any diagnosed primary musculoskeletal condition.14
Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.
Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).15 User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.
Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.16 Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,17-19 improve treatment adherence,12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.13,21-24
Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.14 In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.2
Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.
In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.
Methods
The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.
It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:
- Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
- Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
- Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.
In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.
Results
Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1).
Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.
Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.
Trends by Rurality
Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4).
The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.
Discussion
Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.
Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.26
It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.
The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations
With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.
In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.
Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.
Conclusion
Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.
1. Shane L. What’s in the VA secretary’s 10-point plan to reform his department? https://rebootcamp.militarytimes.com/news/pentagon-congress/2017/02/28/what-s-in-the-va-secretary-s-10-point-plan-to-reform-his-department. Published February 28, 2017. Accessed November 21, 2018.
2. Burgess JF, DeFiore DA. The effect of distance to a VA facility on the choice and level of utilization of VA outpatient services. Soc Science Med. 1994;39(1):95-104.
3. LaVela SL, Smith B, Weaver FM, Miskevics SA. Geographical proximity and health care utilization in veterans with SCI&D in the USA. Soc Science Med. 2004;59:2387-2399.
4. Piette JD, Moos RH. The influence of distance on ambulatory care use, death, and readmission following a myocardial infarction. Health Serv Res. 1996;31(5):573-591.
5. Schmitt SK, Phibbs CS, Piette JD. The influence of distance on utilization of outpatient mental health aftercare following inpatient substance abuse treatment. Addictive Behav. 2003;28(6):1183-1192.
6. Fortney JC, Booth BM, Blow FC, Bunn JY. The effects of travel barriers and age on the utilization of alcoholism treatment aftercare. Am J Drug Alcohol Abuse. 1995;21(3):391-406.
7. McCarthy JF, Blow FC, Valenstein M, et al. Veterans Affairs Health System and mental health treatment retention among patients with serious mental illness: evaluating accessibility and availability barriers. Health Serv Res. 2007;42(3):1042-1060.
8. Mooney C, Zwanziger J, Phibbs CS, Schmitt S. Is travel distance a barrier to veterans’ use of VA hospitals for medical surgical care? Soc Sci Med. 2000;50(12):1743-1755.
9. Friedman SA, Frayne SM, Berg E, et al. Travel time and attrition from VHA care among women veterans: how far is too far? Med Care. 2015;53(4)(suppl 1):S15-S22.
10. Buzza C, Ono SS, Turvey C, et al. Distance is relative: unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26(suppl 2):648-654.
11. Goins RT, Williams KA, Carter MW, Spencer SM, Solovieva T. Perceived barriers to health care access among rural older adults: a qualitative study. J Rural Health. 2005;21(3):206-213.
12. Kairy D, Lehoux P, Vincent C, Visintin M. A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disabil Rehabil. 2009;31(6):427-447.
13. McCue M, Fairman A, Pramuka M. Enhancing quality of life through telerehabilitation. Phys Med Rehabil Clin N Am. 2010;21(1):195-205.
14. Cottrell MA, Galea OA, O’Leary SP, Hill AJ, Russell TG. Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis. Clin Rehabil. 2017;31(5):625-638.
15. Pietrzak E, Cotea C, Pullman S, Nasveld P. Self-management and rehabilitation in osteoarthritis: is there a place for internet-based interventions? Telemed J E Health. 2013;19(10):800-805.
16. Agostini M, Moja L, Banzi R, et al. Telerehabilitation and recovery of motor function: a systematic review and meta-analysis. J Telemed Telecare. 2015;21(4):202-213.
17. Kortke H, Stromeyer H, Zittermann A, et al. New East-Westfalian Postoperative Therapy Concept: A telemedicine guide for the study of ambulatory rehabilitation of patients after cardiac surgery. Telemed J E-Health. 2006;12(4):475-483.
18. Tousignant M, Boissy P, Corriveau H, Moffet H. In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of- concept study and costs estimation. Disabil Rehabil Assist Technol. 2006;1(4):209-216.
19. Sanford JA, Griffiths PC, Richardson P, et al. The effects of in-home rehabilitation on task self-efficacy in mobility-impaired adults: a randomized clinical trial. J Am Geriatr Soc. 2006;54(11):1641-1648.
20. Nakamura K, Takano T, Akao C. The effectiveness of videophones in home healthcare for the elderly. Med Care. 1999;37(2):117-125.
21. Levy CE, Silverman E, Jia H, Geiss M, Omura D. Effects of physical therapy delivery via home video telerehabilitation on functional and health-related quality of life outcomes. J Rehabil Res Dev. 2015;52(3):361-370.
22. Guilfoyle C, Wootton R, Hassall S, et al. User satisfaction with allied health services delivered to residential facilities via videoconferencing. J Telemed Telecare. 2003;9(1):S52-S54.23. Mair F, Whitten P. Systematic review of studies of patient satisfaction with telemedicine. BMJ. 2000;320(7248):1517-1520.
24. Williams T L, May C R, Esmail A. Limitations of patient satisfaction studies in telehealthcare: a systematic review of the literature. Telemed J E-Health. 2001;7(4):293-316.
25. US Department of Veterans Affairs, Office of Telehealth Services. http://vaww.telehealth.va.gov/quality/data/index.asp. Accessed June 1, 2018. [Nonpublic document; source not verified.]
26. Jia H, Cowper D, Tang Y, et al. Post-acute stroke rehabilitation utilization: Are there difference between rural-urban patients and taxonomies? J Rural Health. 2012;28(3):242-247.
27. Cho S, Mathiassen L, Gallivan M. Crossing the chasm: from adoption to diffusion of a telehealth innovation. In: León G, Bernardos AM, Casar JR, Kautz K, De Gross JI, eds. Open IT-Based Innovation: Moving Towards Cooperative IT Transfer and Knowledge Diffusion. Boston, MA: Springer; 2008.
28. Broderick A, Lindeman D. Scaling telehealth programs: lessons from early adopters. https://www.commonwealthfund.org/publications/case-study/2013/jan/scaling-telehealth-programs-lessons-early-adopters. Published January 2013. Accessed June 1, 2018.
1. Shane L. What’s in the VA secretary’s 10-point plan to reform his department? https://rebootcamp.militarytimes.com/news/pentagon-congress/2017/02/28/what-s-in-the-va-secretary-s-10-point-plan-to-reform-his-department. Published February 28, 2017. Accessed November 21, 2018.
2. Burgess JF, DeFiore DA. The effect of distance to a VA facility on the choice and level of utilization of VA outpatient services. Soc Science Med. 1994;39(1):95-104.
3. LaVela SL, Smith B, Weaver FM, Miskevics SA. Geographical proximity and health care utilization in veterans with SCI&D in the USA. Soc Science Med. 2004;59:2387-2399.
4. Piette JD, Moos RH. The influence of distance on ambulatory care use, death, and readmission following a myocardial infarction. Health Serv Res. 1996;31(5):573-591.
5. Schmitt SK, Phibbs CS, Piette JD. The influence of distance on utilization of outpatient mental health aftercare following inpatient substance abuse treatment. Addictive Behav. 2003;28(6):1183-1192.
6. Fortney JC, Booth BM, Blow FC, Bunn JY. The effects of travel barriers and age on the utilization of alcoholism treatment aftercare. Am J Drug Alcohol Abuse. 1995;21(3):391-406.
7. McCarthy JF, Blow FC, Valenstein M, et al. Veterans Affairs Health System and mental health treatment retention among patients with serious mental illness: evaluating accessibility and availability barriers. Health Serv Res. 2007;42(3):1042-1060.
8. Mooney C, Zwanziger J, Phibbs CS, Schmitt S. Is travel distance a barrier to veterans’ use of VA hospitals for medical surgical care? Soc Sci Med. 2000;50(12):1743-1755.
9. Friedman SA, Frayne SM, Berg E, et al. Travel time and attrition from VHA care among women veterans: how far is too far? Med Care. 2015;53(4)(suppl 1):S15-S22.
10. Buzza C, Ono SS, Turvey C, et al. Distance is relative: unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26(suppl 2):648-654.
11. Goins RT, Williams KA, Carter MW, Spencer SM, Solovieva T. Perceived barriers to health care access among rural older adults: a qualitative study. J Rural Health. 2005;21(3):206-213.
12. Kairy D, Lehoux P, Vincent C, Visintin M. A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disabil Rehabil. 2009;31(6):427-447.
13. McCue M, Fairman A, Pramuka M. Enhancing quality of life through telerehabilitation. Phys Med Rehabil Clin N Am. 2010;21(1):195-205.
14. Cottrell MA, Galea OA, O’Leary SP, Hill AJ, Russell TG. Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis. Clin Rehabil. 2017;31(5):625-638.
15. Pietrzak E, Cotea C, Pullman S, Nasveld P. Self-management and rehabilitation in osteoarthritis: is there a place for internet-based interventions? Telemed J E Health. 2013;19(10):800-805.
16. Agostini M, Moja L, Banzi R, et al. Telerehabilitation and recovery of motor function: a systematic review and meta-analysis. J Telemed Telecare. 2015;21(4):202-213.
17. Kortke H, Stromeyer H, Zittermann A, et al. New East-Westfalian Postoperative Therapy Concept: A telemedicine guide for the study of ambulatory rehabilitation of patients after cardiac surgery. Telemed J E-Health. 2006;12(4):475-483.
18. Tousignant M, Boissy P, Corriveau H, Moffet H. In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of- concept study and costs estimation. Disabil Rehabil Assist Technol. 2006;1(4):209-216.
19. Sanford JA, Griffiths PC, Richardson P, et al. The effects of in-home rehabilitation on task self-efficacy in mobility-impaired adults: a randomized clinical trial. J Am Geriatr Soc. 2006;54(11):1641-1648.
20. Nakamura K, Takano T, Akao C. The effectiveness of videophones in home healthcare for the elderly. Med Care. 1999;37(2):117-125.
21. Levy CE, Silverman E, Jia H, Geiss M, Omura D. Effects of physical therapy delivery via home video telerehabilitation on functional and health-related quality of life outcomes. J Rehabil Res Dev. 2015;52(3):361-370.
22. Guilfoyle C, Wootton R, Hassall S, et al. User satisfaction with allied health services delivered to residential facilities via videoconferencing. J Telemed Telecare. 2003;9(1):S52-S54.23. Mair F, Whitten P. Systematic review of studies of patient satisfaction with telemedicine. BMJ. 2000;320(7248):1517-1520.
24. Williams T L, May C R, Esmail A. Limitations of patient satisfaction studies in telehealthcare: a systematic review of the literature. Telemed J E-Health. 2001;7(4):293-316.
25. US Department of Veterans Affairs, Office of Telehealth Services. http://vaww.telehealth.va.gov/quality/data/index.asp. Accessed June 1, 2018. [Nonpublic document; source not verified.]
26. Jia H, Cowper D, Tang Y, et al. Post-acute stroke rehabilitation utilization: Are there difference between rural-urban patients and taxonomies? J Rural Health. 2012;28(3):242-247.
27. Cho S, Mathiassen L, Gallivan M. Crossing the chasm: from adoption to diffusion of a telehealth innovation. In: León G, Bernardos AM, Casar JR, Kautz K, De Gross JI, eds. Open IT-Based Innovation: Moving Towards Cooperative IT Transfer and Knowledge Diffusion. Boston, MA: Springer; 2008.
28. Broderick A, Lindeman D. Scaling telehealth programs: lessons from early adopters. https://www.commonwealthfund.org/publications/case-study/2013/jan/scaling-telehealth-programs-lessons-early-adopters. Published January 2013. Accessed June 1, 2018.