Risk of Potentially Preventable Hospitalizations After SARS-CoV-2 Infection.

Importance: Research demonstrates that SARS-CoV-2 infection is associated with increased risk of all-cause hospitalization. However, no prior studies have assessed the association between SARS-CoV-2 and potentially preventable hospitalizations-that is, hospitalizations for conditions that can usually be effectively managed in ambulatory care settings. Objective: To examine whether SARS-CoV-2 is associated with potentially preventable hospitalization in a nationwide cohort of US veterans. Design, Setting, and Participants: This cohort study used an emulated target randomized trial design with monthly sequential trials to compare risk of a potentially preventable hospitalization among veterans with SARS-CoV-2 and matched comparators without SARS-CoV-2. A total of 189 136 US veterans enrolled in the Veterans Health Administration (VHA) who were diagnosed with SARS-CoV-2 between March 1, 2020, and April 30, 2021, and 943 084 matched comparators were included in the analysis. Data were analyzed from May 10, 2023, to January 26, 2024. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: The primary outcome was a first potentially preventable hospitalization in VHA facilities, VHA-purchased community care, or Medicare fee-for-service care. Extended Cox models were used to examine adjusted hazard ratios (AHRs) of potentially preventable hospitalization among veterans with SARS-CoV-2 and comparators during follow-up periods of 0 to 30, 0 to 90, 0 to 180, and 0 to 365 days. The start of follow-up was defined as the date of each veteran's first positive SARS-CoV-2 diagnosis, with the same index date applied to their matched comparators. Results: The 1 132 220 participants were predominantly men (89.06%), with a mean (SD) age of 60.3 (16.4) years. Most veterans were of Black (23.44%) or White (69.37%) race. Veterans with SARS-CoV-2 and comparators were well-balanced (standardized mean differences, all <0.100) on observable baseline clinical and sociodemographic characteristics. Overall, 3.10% of veterans (3.81% of those with SARS-CoV-2 and 2.96% of comparators) had a potentially preventable hospitalization during 1-year follow-up. Risk of a potentially preventable hospitalization was greater among veterans with SARS-CoV-2 than comparators in 4 follow-up periods: 0- to 30-day AHR of 3.26 (95% CI, 3.06-3.46); 0- to 90-day AHR of 2.12 (95% CI, 2.03-2.21); 0- to 180-day AHR of 1.69 (95% CI, 1.63-1.75); and 0- to 365-day AHR of 1.44 (95% CI, 1.40-1.48). Conclusions and Relevance: In this cohort study, an increased risk of preventable hospitalization in veterans with SARS-CoV-2, which persisted for at least 1 year after initial infection, highlights the need for research on ways in which SARS-CoV-2 shapes postinfection care needs and engagement with the health system. Solutions are needed to mitigate preventable hospitalization after SARS-CoV-2.

Impact of SARS-CoV-2 Infection on Long-Term Depression Symptoms among Veterans.

BACKGROUND: Prior research demonstrates that SARS-COV-2 infection can be associated with a broad range of mental health outcomes including depression symptoms. Veterans, in particular, may be at elevated risk of increased depression following SARS-COV-2 infection given their high rates of pre-existing mental and physical health comorbidities. However, few studies have tried to isolate SARS-COV-2 infection associations with long term, patient-reported depression symptoms from other factors (e.g., physical health comorbidities, pandemic-related stress). OBJECTIVE: To evaluate the association between SARS-COV-2 infection and subsequent depression symptoms among United States Military Veterans. DESIGN: Survey-based non-randomized cohort study with matched comparators. PARTICIPANTS: A matched-dyadic sample from a larger, stratified random sample of participants with and without known to SARS-COV-2 infection were invited to participate in a survey evaluating mental health and wellness 18-months after their index infection date. Sampled participants were stratified by infection severity of the participant infected with SARS-COV-2 (hospitalized or not) and by month of index date. A total of 186 participants in each group agreed to participate in the survey and had sufficient data for inclusion in analyses. Those in the uninfected group who were later infected were excluded from analyses. MAIN MEASURES: Participants were administered the Patient Health Questionnaire-9 as part of a phone interview survey. Demographics, physical and mental health comorbidities were extracted from VHA administrative data. KEY RESULTS: Veterans infected with SARS-COV-2 had significantly higher depression symptoms scores compared with those uninfected. In particular, psychological symptoms (e.g., low mood, suicidal ideation) scores were elevated relative to the comparator group (MInfected = 3.16, 95%CI: 2.5, 3.8; MUninfected = 1.96, 95%CI: 1.4, 2.5). Findings were similar regardless of history of depression. CONCLUSION: SARS-COV-2 infection was associated with more depression symptoms among Veterans at 18-months post-infection. Routine evaluation of depression symptoms over time following SARS-COV-2 infection is important to facilitate adequate assessment and treatment.

Risk of Suicide-Related Outcomes After SARS-COV-2 Infection: Results from a Nationwide Observational Matched Cohort of US Veterans.

BACKGROUND: Negative mental health-related effects of SARS-COV-2 infection are increasingly evident. However, the impact on suicide-related outcomes is poorly understood, especially among populations at elevated risk. OBJECTIVE: To determine risk of suicide attempts and other self-directed violence (SDV) after SARS-COV-2 infection in a high-risk population. DESIGN: We employed an observational design supported by comprehensive electronic health records from the Veterans Health Administration (VHA) to examine the association of SARS-COV-2 infection with suicide attempts and other SDV within one year of infection. Veterans with SARS-COV-2 infections were matched 1:5 with non-infected comparators each month. Three periods after index were evaluated: days 1-30, days 31-365, and days 1-365. PARTICIPANTS: VHA patients infected with SARS-COV-2 between March 1, 2020 and March 31, 2021 and matched non-infected Veteran comparators. MAIN MEASURES: Suicide attempt and other SDV events for the COVID-19 and non-infected comparator groups were analyzed using incidence rates per 100,000 person years and hazard ratios from Cox regressions modeling time from matched index date to first event. Subgroups were also examined. KEY RESULTS: 198,938 veterans with SARS-COV-2 (COVID-19 group) and 992,036 comparators were included. Unadjusted one-year incidence per 100,000 for suicide attempt and other SDV was higher among the COVID-19 group: 355 vs 250 and 327 vs 235, respectively. The COVID-19 group had higher risk than comparators for suicide attempts: days 1-30 hazard ratio (HR) = 2.54 (CI:2.05, 3.15), days 31-365 HR = 1.30 (CI:1.19, 1.43) and days 1-365 HR = 1.41 (CI:1.30, 1.54), and for other SDV: days 1-30 HR = 1.94 (CI:1.51, 2.49), days 31-365 HR = 1.32 (CI:1.20, 1.45) and days 1-365 HR = 1.38 (CI:1.26, 1.51). CONCLUSIONS: COVID-19 patients had higher risks of both suicide attempts and other forms of SDV compared to uninfected comparators, which persisted for at least one year after infection. Results support suicide risk screening of those infected with SARS-COV-2 to identify opportunities to prevent self-harm.

Understanding care coordination for Veterans with complex care needs: protocol of a multiple-methods study to build evidence for an effectiveness and implementation study.

Background: For patients with complex health and social needs, care coordination is crucial for improving their access to care, clinical outcomes, care experiences, and controlling their healthcare costs. However, evidence is inconsistent regarding the core elements of care coordination interventions, and lack of standardized processes for assessing patients' needs has made it challenging for providers to optimize care coordination based on patient needs and preferences. Further, ensuring providers have reliable and timely means of communicating about care plans, patients' full spectrum of needs, and transitions in care is important for overcoming potential care fragmentation. In the Veterans Health Administration (VA), several initiatives are underway to implement care coordination processes and services. In this paper, we describe our study underway in the VA aimed at building evidence for designing and implementing care coordination practices that enhance care integration and improve health and care outcomes for Veterans with complex care needs. Methods: In a prospective observational multiple methods study, for Aim 1 we will use existing data to identify Veterans with complex care needs who have and have not received care coordination services. We will examine the relationship between receipt of care coordination services and their health outcomes. In Aim 2, we will adapt the Patient Perceptions of Integrated Veteran Care questionnaire to survey a sample of Veterans about their experiences regarding coordination, integration, and the extent to which their care needs are being met. For Aim 3, we will interview providers and care teams about their perceptions of the innovation attributes of current care coordination needs assessment tools and processes, including their improvement over other approaches (relative advantage), fit with current practices (compatibility and innovation fit), complexity, and ability to visualize how the steps proceed to impact the right care at the right time (observability). The provider interviews will inform design and deployment of a widescale provider survey. Discussion: Taken together, our study will inform development of an enhanced care coordination intervention that seeks to improve care and outcomes for Veterans with complex care needs.

Design and analysis of outcomes following SARS-CoV-2 infection in veterans.

BACKGROUND: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. METHODS: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. RESULTS: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). CONCLUSION: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

Early Impact of VA MISSION Act Implementation on Primary Care Appointment Wait Time.

BACKGROUND: Through Community Care Networks (CCNs) implemented with the VA MISSION Act, VA expanded provider contracting and instituted network adequacy standards for Veterans' community care. OBJECTIVE: To determine whether early CCN implementation impacted community primary care (PC) appointment wait times overall, and by rural/urban and PC shortage area (HPSA) status. DESIGN: Using VA administrative data from February 2019 through February 2020 and a difference-in-differences approach, we compared wait times before and after CCN implementation for appointments scheduled by VA facilities that did (CCN appointments) and did not (comparison appointments) implement CCNs. We ran regression models with all appointments, and stratified by rural/urban and PC HPSA status. All models adjusted for Veteran characteristics and VA facility-level clustering. APPOINTMENTS: 13,720 CCN and 40,638 comparison appointments. MAIN MEASURES: Wait time, measured as number of days from authorization to use community PC to a Veteran's first corresponding appointment. KEY RESULTS: Overall, unadjusted wait times increased by 35.7 days ([34.4, 37.1] 95% CI) after CCN implementation. In adjusted analysis, comparison wait times increased on average 33.7 days ([26.3, 41.2] 95% CI, p < 0.001) after CCN implementation; there was no significant difference for CCN wait times (across-group mean difference: 5.4 days, [-3.8, 14.6] 95% CI, p = 0.25). In stratified analyses, comparison wait time increases ranged from 29.6 days ([20.8, 38.4] 95% CI, p < 0.001) to 42.1 days ([32.9, 51.3] 95% CI, p > 0.001) after CCN implementation, while additional differences for CCN appointments ranged from 13.4 days ([3.5, 23.4] 95% CI, p = 0.008) to -15.1 days ([-30.1, -0.1] 95% CI, p = 0.05) for urban and PC HPSA appointments, respectively. CONCLUSIONS: After early CCN implementation, community PC wait times increased sharply at VA facilities that did and did not implement CCNs, regardless of rural/urban or PC HPSA status, suggesting community care demand likely overwhelmed VA resources such that CCNs had limited impact.

Hospital Readmissions Among Veterans Within 90 Days of Discharge Following Initial Hospitalization for COVID-19.

INTRODUCTION: Some patients experience ongoing sequelae after discharge, including rehospitalization; therefore, outcomes following COVID-19 hospitalization are of continued interest. We examined readmissions within 90 days of hospital discharge for veterans hospitalized with COVID-19 during the first 10 months of the pandemic in the US. METHODS: Veterans hospitalized with COVID-19 at a Veterans Health Administration (VA) hospital from March 1, 2020, through December 31, 2020 were followed for 90 days after discharge to determine readmission rates. RESULTS: Of 20,414 veterans hospitalized with COVID-19 during this time period, 13% (n = 2,643) died in the hospital. Among survivors (n = 17,771), 16% (n = 2,764) were readmitted within 90 days of discharge, with a mean time to readmission of 21.6 days (SD = 21.1). Characteristics of the initial COVID-19 hospitalization associated with readmission included length of stay, mechanical ventilator use, higher comorbidity index score, current smoking, urban residence, discharged against medical advice, and hospitalized from September through December 2020 versus March through August 2020 (all P values <.02). Veterans readmitted from September through December 2020 were more often White, lived in a rural or highly rural area, and had shorter initial hospitalizations than veterans hospitalized earlier in the year. CONCLUSION: Approximately 1 of 6 veterans discharged alive following a COVID-19 hospitalization from March 1 through December 31, 2020, were readmitted within 90 days. The longer the hospital stay, the greater the likelihood of readmission. Readmissions also were more likely when the initial admission required mechanical ventilation, or when the veteran had multiple comorbidities, smoked, or lived in an urban area. COVID-19 hospitalizations were shorter from September through December 2020, suggesting that hospital over-capacity may have resulted in earlier discharges and increased readmissions. Efforts to monitor and provide support for patients discharged in high bed-capacity situations may help avoid readmissions.

Early Adoption of Anti-SARS-CoV-2 Pharmacotherapies Among US Veterans With Mild to Moderate COVID-19, January and February 2022.

Importance: Older adults and individuals with medical comorbidities are at increased risk for severe COVID-19. Several pharmacotherapies demonstrated to reduce the risk of COVID-19-related hospitalization and death have been authorized for use. Objective: To describe factors associated with receipt of outpatient COVID-19 pharmacotherapies in the Veterans Affairs (VA) health care system. Design, Settings, and Participants: This cohort study assessed outpatient veterans with risk factors for severe COVID-19 who tested positive for SARS-CoV-2 during January and February 2022. The setting was the VA health care system, the largest integrated health care system in the US. Exposures: Demographic characteristics, place of residence, underlying medical conditions, and COVID-19 vaccination. Main Outcomes and Measures: The odds of receipt of any COVID-19 pharmacotherapy, including sotrovimab, nirmatrelvir boosted with ritonavir, molnupiravir, or remdesivir were estimated using multivariable logistic regression. Results: Among 111 717 veterans included in this study (median [IQR] age, 60 [46-72] years; 96 482 [86.4%] male, 23 362 [20.9%] Black, 10 740 [9.6%] Hispanic, 75 973 [68.0%] White) who tested positive for SARS-CoV-2 during January to February 2022, 4233 (3.8%) received any COVID-19 pharmacotherapy, including 2870 of 92 396 (3.1%) in January and 1363 of 19 321 (7.1%) in February. Among a subset of 56 285 veterans with documented COVID-19-related symptoms in the 30 days preceding a positive SARS-CoV-2 test, 3079 (5.5%) received any COVID-19 pharmacotherapy. Untreated veterans had a median (IQR) age of 60 (46-71) years and a median (IQR) of 3 (2-5) underlying medical conditions. Veterans receiving any treatment were more likely to be older (aged 65 to 74 years vs 50 to 64 years: adjusted odds ratio [aOR], 1.66 [95% CI, 1.52-1.80]; aged at least 75 years vs 50 to 64 years: aOR, 1.67 [95% CI, 1.53-1.84]) and have a higher number of underlying conditions (at least 5 conditions vs 1 to 2 conditions: aOR, 2.17 [95% CI, 1.98-2.39]). Compared with White veterans, Black veterans (aOR, 0.65 [95% CI, 0.60-0.72]) were less likely to receive treatment; and compared with non-Hispanic veterans, Hispanic veterans (aOR, 0.88 [95% CI, 0.77-0.99]) were less likely to receive treatment. There were 16 546 courses of sotrovimab, nirmatrelvir, and molnupiravir allocated across the VA during this period. Conclusions and Relevance: In this cohort study of veterans who tested positive for SARS-CoV-2 during January and February when supply of outpatient COVID-19 pharmacotherapies was limited, prescription of these pharmacotherapies was underused, and many veterans with risk factors for severe COVID-19 did not receive treatment. Veterans from minority racial and ethnic groups were less likely to receive any pharmacotherapy.

Rates and Factors Associated With Documentation of Diagnostic Codes for Long COVID in the National Veterans Affairs Health Care System.

Importance: Some persons infected with SARS-CoV-2 experience symptoms or impairments many months after acute infection. Objectives: To determine the rates, clinical setting, and factors associated with documented receipt of COVID-19-related care 3 or more months after acute infection. Design, Setting, and Participants: This retrospective cohort study used data from the US Department of Veterans Affairs health care system. Participants included persons with a positive SARS-CoV-2 test between February 1, 2020, and April 30, 2021, who were still alive 3 months after infection and did not have evidence of reinfection. Data analysis was performed from February 2020 to December 2021. Exposures: Positive SARS-CoV-2 test. Main Outcomes and Measures: Rates and factors associated with documentation of COVID-19-related International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes (U07.1, Z86.16, U09.9, and J12.82) 3 or more months after acute infection (hereafter, long-COVID care), with follow-up extending to December 31, 2021. Results: Among 198 601 SARS-CoV-2-positive persons included in the study, the mean (SD) age was 60.4 (17.7) years, 176 942 individuals (89.1%) were male, 133 924 (67.4%) were White, 44 733 (22.5%) were Black, and 19 735 (9.9%) were Hispanic. During a mean (SD) follow-up of 13.5 (3.6) months, long-COVID care was documented in a wide variety of clinics, most commonly primary care and general internal medicine (18 634 of 56 310 encounters [33.1%]), pulmonary (7360 of 56 310 encounters [13.1%]), and geriatrics (5454 of 56 310 encounters [9.7%]). Long-COVID care was documented in 26 745 cohort members (13.5%), with great variability across geographical regions (range, 10.8%-18.1%) and medical centers (range, 3.0%-41.0%). Factors significantly associated with documented long-COVID care included older age, Black or American Indian/Alaska Native race, Hispanic ethnicity, geographical region, high Charlson Comorbidity Index score, having documented symptoms at the time of acute infection (adjusted odds ratio [AOR], 1.71; 95% CI, 1.65-1.78) and requiring hospitalization (AOR, 2.60; 95% CI, 2.51-2.69) or mechanical ventilation (AOR, 2.46; 95% CI, 2.26-2.69). Patients who were fully vaccinated at the time of infection were less likely to receive long-COVID care (AOR, 0.78; 95% CI, 0.68-0.90). Conclusions and Relevance: Long-COVID care was documented in a variety of clinical settings, with great variability across regions and medical centers and was documented more commonly in older persons, those with higher comorbidity burden, those with more severe acute COVID-19 presentation and those who were unvaccinated at the time of infection. These findings provide support and guidance for health care systems to develop systematic approaches to the evaluation and management of patients who may be experiencing long COVID.

Psychiatric disorders newly diagnosed among veterans subsequent to hospitalization for COVID-19.

OBJECTIVE: The goal of our study was to evaluate the development of new mental health diagnoses up to 6-months following COVID-19 hospitalization for in a large, national sample. METHOD: Data were extracted for all Veterans hospitalized at Veterans Health Administration hospitals for COVID-19 from March through August of 2020 utilizing national administrative data. After identifying the cohort, follow-up data were linked through six months post-hospitalization. Data were analyzed using logistic regression. RESULTS: Eight percent of patients developed a new mental health diagnosis following hospitalization. The most common new mental health diagnoses involved depressive, anxiety, and adjustment disorders. Younger and rural patients were more likely to develop new mental health diagnoses. Women and those with more comorbidities were less likely to develop new diagnoses. CONCLUSION: A subpopulation of patients hospitalized for COVID-19 developed new mental health diagnoses. Unique demographics predictors indicate the potential need for additional outreach and screening to groups at elevated risk of post-hospitalization, mental health sequelae.

Veterans' Use of Veterans Health Administration Primary Care in an Era of Expanding Choice.

BACKGROUND: The Veterans Choice Program (VCP), aimed at improving access to care, included expanded options for Veterans to receive primary care through community providers. OBJECTIVES: The objective of this study was to characterize and compare Veterans use of Veterans Health Administration (VA) primary care services at VA facilities and through a VA community care network (VA-CCN) provider. RESEARCH DESIGN: This was a retrospective, observational over fiscal years (FY) 2015-2018. SUBJECTS: Veterans receiving primary care services paid for by the VA. MEASURES: Veteran demographic, socioeconomic and clinical factors and use of VA primary care services under the VCP each year. RESULTS: There were 6.3 million Veterans with >54 million VA primary care visits, predominantly (98.5% of visits) at VA facility. The proportion of VA-CCN visits increased in absolute terms from 0.7% in 2015 to 2.6% in 2018. Among Veterans with any VA-CCN primary care, the proportion of VA-CCN visits increased from 22.6% to 55.3%. Logistic regression indicated that Veterans who were female, lived in rural areas, had a driving distance >40 miles, had health insurance or had a psychiatric/depression condition were more likely to receive VA-CCN primary care. Veterans who were older, identified as Black race, required to pay VA copayments, or had a higher Nosos score, were less likely to receive VA-CCN primary care. CONCLUSION: As the VA transitions from the VCP to MISSION and VA facilities gain experience under the new contracts, attention to factors that impact Veterans' use of primary care services in different settings are important to monitor to identify access barriers and to ensure Veterans' health care needs are met.

Intranasal Oxytocin for Stimulant Use Disorder Among Male Veterans Enrolled in an Opioid Treatment Program: A Randomized Controlled Trial.

The increasing prevalence of illicit stimulant use among those in opioid treatment programs poses a significant risk to public health, stimulant users have the lowest rate of retention and poorest outcomes among those in addiction treatment, and current treatment options are limited. Oxytocin administration has shown promise in reducing addiction-related behavior and enhancing salience to social cues. We conducted a randomized, double-blind, placebo-controlled clinical trial of intranasal oxytocin administered twice daily for 6 weeks to male Veterans with stimulant use disorder who were also receiving opioid agonist therapy and counseling (n = 42). There was no significant effect of oxytocin on stimulant use, stimulant craving, or therapeutic alliance over 6 weeks. However, participants receiving oxytocin (vs. placebo) attended significantly more daily opioid agonist therapy dispensing visits. This replicated previous work suggesting that oxytocin may enhance treatment engagement among individuals with stimulant and opioid use disorders, which would address a significant barrier to effective care.

Does Community Outsourcing Improve Timeliness of Care for Veterans With Obstructive Sleep Apnea?

BACKGROUND: Providing timely access to care has been a long-standing priority for the Veterans Affairs Healthcare System. Recent strategies to reduce long wait times have focused on purchasing community care by a fee-for-service model. Whether outsourcing Veterans Affairs (VA) specialty care to the community improves access is unclear. OBJECTIVES: We compared time from referral to treatment among Veterans whose care was provided by VA versus community care purchased by the VA, using obstructive sleep apnea as an example condition. METHODS: This was a retrospective cohort study of Northern California Veterans seeking sleep apnea care through the San Francisco VA Healthcare System between 2012 and 2018. We used multivariable linear regression with propensity score matching to investigate the relationship between time to care delivery and care setting (VA provided vs. VA-purchased community care). A total of 1347 Northern California Veterans who completed sleep apnea testing within the VA and 88 Veterans who completed sleep apnea testing in the community had complete data for analysis. RESULTS: Among Northern California Veterans with obstructive sleep apnea, outsourcing of care to the community was associated with longer time from referral to therapy (mean±SD, 129.6±82.8 d with VA care vs. 252.0±158.8 d with community care, P<0.001) and greater loss to follow-up. CONCLUSIONS: These findings suggest that purchasing community care may lead to care fragmentation and not improve wait times nor improve access to subspecialty care for Veterans.

Prevalence and management of sleep disorders in the Veterans Health Administration.

The prevalence of diagnosed sleep disorders among Veterans treated at Veterans Affairs (VA) medical facilities increased significantly during fiscal years (FY) 2012 through 2018. Specifically, the prevalence of sleep-related breathing disorders (SRBD) increased from 5.5% in FY2012 to 22.2% in FY2018, and the prevalence of insomnia diagnoses increased from 7.4% in FY2012 to 11.8% in FY2018. Consequently, Veterans' demand for sleep medicine services also increased significantly between FY2012-2018, with steady increases in the annual number of VA sleep clinic appointments during this period (<250,000 in FY 2012; >720,000 in FY2018). Common co-morbid conditions among Veterans diagnosed with sleep disorders include obesity, diabetes, congestive heart failure, depression, post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI). To address this healthcare crisis, the Veterans Health Administration (VHA) developed and/or implemented numerous innovations to improve the quality and accessibility of sleep care services for Veterans. These innovations include a TeleSleep Enterprise-Wide Initiative to improve rural Veterans' access to sleep care; telehealth applications such as the Remote Veteran Apnea Management Platform (REVAMP), Clinical Video Telehealth, and CBT-i Coach; increased use of home sleep apnea testing (HSAT); and programs for Veterans who experience sleep disorders associated with obesity, PTSD, TBI and other conditions.

Comparing VA and Community-Based Care: Trends in Sleep Studies Following the Veterans Choice Act.

BACKGROUND: To address concerns about access to care, the Veterans Access, Choice, and Accountability Act of 2014 was enacted to make care available in the community when Veterans Health Administration (VA) care was unavailable or not timely. This paper examined VA referrals for diagnostic sleep studies from federal fiscal year (FY) 2015-2018. DESIGN: Sleep studies completed between FY2015 and 2018 for Veterans tested within VA facilities (VAF) or referred to VA community care (VACC) providers were identified using VA administrative data files. Sleep studies were divided into laboratory and home studies. KEY RESULTS: The number of sleep studies conducted increased over time; the proportion of home studies increased in VAF (32 to 47%). Veterans were more likely to be referred for a sleep study to VACC if they lived in a rural or highly rural area (ORs = 1.47 and 1.55, respectively), and had public or public and private insurance (ORs = 2.01 and 1.35), and were less likely to be referred to VACC if they were age 65+ (OR = 0.72) and were in the highest utilization risk based on Nosos score (OR = 0.78). Regression analysis of sleep study type revealed that lab studies were much more likely for VACC referrals (OR = 3.16), for persons living in rural areas (OR = 1.21), with higher comorbidity scores (OR = 1.28) and for ages 44-54, 55 to 64, and 65+ (ORs = 1.12, 1.28, 1.45, respectively) compared to younger Veterans. Veterans with some or full VA copayments (ORs = 0.91 and 0.86, respectively), and overweight Veterans (OR = 0.94) were less likely to have lab studies. CONCLUSIONS: The number of sleep studies performed on Veterans increased from 2015 to 2018. Access to sleep studies improved through a combination of providing care through the Veteran Choice Program, predominantly used by rural Veterans, and increased use of home sleep studies by VA.

Psychopathy and Corticostriatal Connectivity: The Link to Criminal Behavior in Methamphetamine Dependence.

Methamphetamine use and psychopathy are associated with criminal behavior; however, it is unclear how methamphetamine use and psychopathy interact to promote violent, economic and drug offenses. Abnormalities in corticostriatal functional connectivity are exhibited in both psychopathic and methamphetamine dependent individuals, which may contribute to criminal behavior through maladaptive and impulsive decision-making processes. This study shows that psychopathic traits contribute to weaker corticostriatal connectivity in methamphetamine dependence and contributes to an increase in criminal behavior. As the propensity to engage in criminal activity is dependent on a number of factors, a hierarchical regression identifies the contribution of the impulsive antisocial domain of psychopathy, anxiety, years of methamphetamine use and corticostriatal connectivity on different types of criminal offenses. Methamphetamine use and psychopathic traits reduce treatment responsiveness and increase the likelihood of recidivism, and it is therefore important to understand the factors underlying the propensity to engage in criminal behavior.