Intensity, Characteristics, and Factors Associated With Receipt of Care Coordination Among High-Risk Veterans in the Veterans Health Administration.

BACKGROUND: The Veterans Health Administration (VHA) has initiatives underway to enhance the provision of care coordination (CC), particularly among high-risk Veterans. Yet, evidence detailing the characteristics of and who receives VHA CC is limited. OBJECTIVES: We examined intensity, timing, setting, and factors associated with VHA CC among high-risk Veterans. RESEARCH DESIGN: We conducted a retrospective observational cohort study, following Veterans for 1 year after being identified as high-risk for hospitalization or mortality, to characterize their CC. Demographic and clinical factors predictive of CC were identified via multivariate logistic regression. SUBJECTS: A total of 1,843,272 VHA-enrolled high-risk Veterans in fiscal years 2019-2021. MEASURES: We measured 5 CC variables during the year after Veterans were identified as high risk: (1) receipt of any service, (2) number of services received, (3) number of days to first service, (4) number of days between services, and (5) type of visit during which services were received. RESULTS: Overall, 31% of high-risk Veterans in the sample received CC during one-year follow-up. Among Veterans who received ≥1 service, a median of 2 [IQR (1, 6)] services were received. Among Veterans who received ≥2 services, there was a median of 26 [IQR (10, 57)] days between services. Most services were received during outpatient psychiatry (46%) or medicine (16%) visits. Veterans' sociodemographic and clinical characteristics were associated with receipt of CC. CONCLUSIONS: A minority of Veterans received CC in the year after being identified as high-risk, and there was variation in intensity, timing, and setting of CC. Research is needed to examine the fit between Veterans' CC needs and preferences and VHA CC delivery.

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.

Application of a comprehensive disability measure: Disability prevalence among US Veterans and non-veterans from the National Health Interview Survey Data from 2015 to 2018.

BACKGROUND: Current measures of condition-specific disabilities or those capturing only severe limitations may underestimate disability prevalence, including among Veterans. OBJECTIVES: To develop a comprehensive measure to characterize and compare disabilities among US Veterans and non-Veterans. METHODS: Using 2015-2018 pooled cross-sectional National Health Interview Survey data, we compared the frequency and survey-weighted prevalence of non-mutually exclusive sensory, social, and physical disabilities by Veteran status. We developed a measure for and examined the frequency and survey-weighted prevalence of eight mutually exclusive disability categories-sensory only; physical only; social only; sensory and physical; social and sensory; physical and social; and sensory, social, and physical. RESULTS: Among 118,818 NHIS respondents, 11,943 were Veterans. Veterans had a greater prevalence than non-Veterans of non-mutually exclusive physical [52.01% vs. 34.68% (p < 0.001)], sensory [44.47% vs. 21.79% (p < 0.001)], and social [17.20% vs. 11.61% (p < 0.001)] disabilities (after survey-weighting). The most frequently reported mutually exclusive disability categories for both Veterans and non-Veterans were sensory and physical (19.20% and 8.02%, p < 0.001) and physical only (16.24% and 15.69%, p = 0.216) (after survey-weighting). The least frequently reported mutually exclusive disability categories for both Veterans and non-Veterans were social only (0.31% and 0.44%, p = 0.136) and sensory and social (0.32% and 0.20%, respectively, 0.026) (after survey-weighting). CONCLUSIONS: Our disability metric demonstrates that Veterans have a higher disability prevalence than non-Veterans, and a higher prevalence than previously reported. Public policy and future research should consider this broader definition of disability to more fully account for the variable needs of people with disabilities.

Prevalence and Correlates of VA-Purchased Community Care Use Among Post-9/11-Era Veterans With Traumatic Brain Injury.

OBJECTIVE: Post-9/11-era veterans with traumatic brain injury (TBI) have greater health-related complexity than veterans overall, and may require coordinated care from TBI specialists such as those within the Department of Veterans Affairs (VA) healthcare system. With passage of the Choice and MISSION Acts, more veterans are using VA-purchased care delivered by community providers who may lack TBI training. We explored prevalence and correlates of VA-purchased care use among post-9/11 veterans with TBI. SETTING: Nationwide VA-purchased care from 2016 through 2019. PARTICIPANTS: Post-9/11-era veterans with clinician-confirmed TBI based on VA's Comprehensive TBI Evaluation (N = 65 144). DESIGN: This was a retrospective, observational study. MAIN MEASURES: Proportions of veterans who used VA-purchased care and both VA-purchased and VA-delivered outpatient care, overall and by study year. We employed multivariable logistic regression to assess associations between veterans' sociodemographic, military history, and clinical characteristics and their likelihood of using VA-purchased care from 2016 through 2019. RESULTS: Overall, 51% of veterans with TBI used VA-purchased care during the study period. Nearly all who used VA-purchased care (99%) also used VA-delivered outpatient care. Veterans' sociodemographic, military, and clinical characteristics were associated with their likelihood of using VA-purchased care. Notably, in adjusted analyses, veterans with moderate/severe TBI (vs mild), those with higher health risk scores, and those diagnosed with posttraumatic stress disorder, depression, anxiety, substance use disorders, or pain-related conditions had increased odds of using VA-purchased care. Additionally, those flagged as high risk for suicide also had higher odds of VA-purchased care use. CONCLUSIONS: Veterans with TBI with greater health-related complexity were more likely to use VA-purchased care than their less complex counterparts. The risks of potential care fragmentation across providers versus the benefits of increased access to care are unknown. Research is needed to examine health and functional outcomes among these veterans.

Financial hardship after COVID-19 infection among US Veterans: a national prospective cohort study.

BACKGROUND: Research suggests an association between COVID-19 infection and certain financial hardships in the shorter term and among single-state and privately insured samples. Whether COVID-19 is associated with financial hardship in the longer-term or among socially vulnerable populations is unknown. Therefore, we examined whether COVID-19 was associated with a range of financial hardships 18 months after initial infection among a national cohort of Veterans enrolled in the Veterans Health Administration (VHA)-the largest national integrated health system in the US. We additionally explored the association between Veteran characteristics and financial hardship during the pandemic, irrespective of COVID-19. METHODS: We conducted a prospective, telephone-based survey. Out of 600 Veterans with COVID-19 from October 2020 through April 2021 who were invited to participate, 194 Veterans with COVID-19 and 194 matched comparators without a history of infection participated. Financial hardship outcomes included overall health-related financial strain, two behavioral financial hardships (e.g., taking less medication than prescribed due to cost), and seven material financial hardships (e.g., using up most or all savings). Weighted generalized estimating equations were used to estimate risk ratios (RR) and 95% confidence intervals (CI) of financial hardship by COVID-19 status, and to assess the relationship between infection and Veteran age, VHA copay status, and comorbidity score, irrespective of COVID-19 status. RESULTS: Among 388 respondents, 67% reported at least one type of financial hardship since March 2020, with 21% reporting behavioral hardships and 64% material hardships; 8% reported severe-to-extreme health-related financial strain. Compared with uninfected matched comparators, Veterans with a history of COVID-19 had greater risks of severe-to-extreme health-related financial strain (RR: 4.0, CI: 1.4-11.2), taking less medication due to cost (RR: 2.9, 95% CI: 1.0-8.6), and having a loved one take time off work to care for them (RR: 1.9, CI: 1.1-3.6). Irrespective of COVID-19 status, Veterans aged < 65 years had a greater risk of most financial hardships compared with Veterans aged ≥ 65 years. CONCLUSIONS: Health-related financial hardships such as taking less medication due to cost and severe-to-extreme health-related financial strain were more common among Veterans with a history of COVID-19 than among matched comparators. Strategies are needed to address health-related financial hardship after COVID-19. TRIAL REGISTRATION: NCT05394025, registered 05-27-2022.

VA-Delivered or VA-Purchased Care: Important Factors for Veterans Navigating Care Decisions.

BACKGROUND/OBJECTIVE: The VA MISSION Act aimed to increase Veterans' access to care by allowing eligible Veterans to use VA-paid care from non-VA providers ("VA-purchased care"). We interviewed Veterans who were eligible for both VA-delivered and VA-purchased care to examine factors they consider when making decisions about whether to use VA-delivered or VA-purchased care. METHODS: We conducted semi-structured interviews with 28 Veterans across the USA who were eligible for VA-delivered and VA-purchased care, using deductive and inductive analysis to develop themes. Participants were recruited from a survey about healthcare access and decision-making. More than half of participants lived in rural areas, 21 were men, and 25 were > 50 years old. KEY RESULTS: Veteran participants identified (1) high-quality relationships with providers based on mutual trust, empathy, authenticity, and continuity of care, and (2) a positive environment or "eco-system of care" characterized by supportive interactions with staff and other Veterans, and exemplary customer service as integral to their decisions about where to receive care. These preferences influenced their engagement with VA and non-VA providers. We discovered corresponding findings related to Veterans' information needs. When making decisions around where to receive care, participants said they would like more information about VA and non-VA providers and services, and about coordination of care and referrals, including understanding processes and implications of utilizing VA-purchased care. DISCUSSION/CONCLUSION: Current VA-purchased care eligibility determinations focus on common access metrics (e.g., wait times, distance to care). Yet, Veterans discussed other important factors for navigating care decisions, including patient-provider relationship quality and the larger healthcare environment (e.g., interactions with staff and other Veterans). Our findings point to the need for health systems to collect and provide information on these aspects of care to ensure care decisions reflect what is important to Veterans when navigating where to receive care.

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.

Differences in access to virtual and in-person primary care by race/ethnicity and community social vulnerability among adults diagnosed with COVID-19 in a large, multi-state health system.

BACKGROUND: Research exploring telehealth expansion during the COVID-19 pandemic has demonstrated that groups disproportionately impacted by COVID-19 also experience worse access to telehealth. However, this research has been cross-sectional or short in duration; geographically limited; has not accounted for pre-existing access disparities; and has not examined COVID-19 patients. We examined virtual primary care use by race/ethnicity and community social vulnerability among adults diagnosed with COVID-19 in a large, multi-state health system. We also assessed use of in-person primary care to understand whether disparities in virtual access may have been offset by improved in-person access. METHODS: Using a cohort design, electronic health records, and Centers for Disease Control and Prevention Social Vulnerability Index, we compared changes in virtual and in-person primary care use by race/ethnicity and community social vulnerability in the year before and after COVID-19 diagnosis. Our study population included 11,326 adult patients diagnosed with COVID-19 between March and July 2020. We estimated logistic regression models to examine likelihood of primary care use. In all regression models we computed robust standard errors; in adjusted models we controlled for demographic and health characteristics of patients. RESULTS: In a patient population of primarily Hispanic/Latino and non-Hispanic White individuals, and in which over half lived in socially vulnerable areas, likelihood of virtual primary care use increased from the year before to the year after COVID-19 diagnosis (3.6 to 10.3%); while in-person use remained stable (21.0 to 20.7%). In unadjusted and adjusted regression models, compared with White patients, Hispanic/Latino and other race/ethnicity patients were significantly less likely to use virtual care before and after COVID-19 diagnosis; Hispanic/Latino, Native Hawaiian/Pacific Islander, and other race/ethnicity patients, and patients living in socially vulnerable areas were also significantly less likely to use in-person care during these time periods. CONCLUSIONS: Newly expanded virtual primary care has not equitably benefited individuals from racialized groups diagnosed with COVID-19, and virtual access disparities have not been offset by improved in-person access. Health systems should employ evidence-based strategies to equitably provide care, including representative provider networks; targeted, empowering outreach; co-developed culturally and linguistically appropriate tools and technologies; and provision of enabling resources and services.

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.

Determinants of Boarding of Patients with Severe Mental Illness in Hospital Emergency Departments.

BACKGROUND: Boarding of patients in hospital emergency departments (EDs) occurs routinely across the U.S. ED patients with behavioral health conditions are more likely to be boarded than other patients. However, the existing literature on ED boarding of psychiatric patients remains largely descriptive and has not empirically related mental health system capacity to psychiatric boarding. Nor does it show how the mental health system could better address the needs of populations at the highest risk of ED boarding. AIMS OF THE STUDY: We examined extent and determinants of "boarding" of patients with severe mental illness (SMI) in hospital emergency departments (ED) and tested whether greater mental health system capacity may mitigate the degree of ED boarding. METHODS: We linked Oregon's ED Information Exchange, hospital discharge, and Medicaid data to analyze encounters in Oregon hospital EDs from October 2014 through September 2015 by 7,103 persons aged 15 to 64 with SMI (N = 34,207). We additionally utilized Medicaid claims for years 2010-2015 to identify Medicaid beneficiaries with SMI. Boarding was defined as an ED stay over six hours. We estimated a recursive simultaneous-equation model to test the pathway that mental health system capacity affects ED boarding via psychiatric visits. RESULTS: Psychiatric visits were more likely to be boarded than non-psychiatric visits (30.2% vs. 7.4%). Severe psychiatric visits were 1.4 times more likely to be boarded than non-severe psychiatric visits. Thirty-four percent of psychiatric visits by children were boarded compared to 29.6% for adults. Statistical analysis found that psychiatric visit, substance abuse, younger age, black race and urban residence corresponded with an elevated risk of boarding. Discharge destinations such as psychiatric facility and acute care hospitals also corresponded with a higher probability of ED boarding. Greater supply of mental health resources in a county, both inpatient and intensive community-based, corresponded with a reduced risk of ED boarding via fewer psychiatric ED visits. DISCUSSION: Psychiatric visit, severity of psychiatric diagnosis, substance abuse, and discharge destinations are among important predictors of psychiatric ED boarding by persons with SMI. A greater capacity of inpatient and intensive community mental health systems may lead to a reduction in psychiatric ED visits by persons with SMI and thereby decrease the extent of psychiatric ED boarding. IMPLICATIONS FOR HEALTH POLICIES: Continued investment in mental health system resources may reduce psychiatric ED visits and mitigate the psychiatric ED boarding problem.

Lifetime Psychotropic Medication Use Among Service Members and Veterans With and Without History of Mild Traumatic Brain Injury: A Pilot Study.

INTRODUCTION: Military Service Members, Veterans, and other patient populations who experience traumatic brain injury (TBI) may have increased risk of early neurodegenerative diseases relative to those without TBI history. Some evidence suggests that exposure to psychotropic medications may play a role in this association. The Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) prospective longitudinal study provides an ideal setting to examine the effects of psychotropic medication exposure on long-term neurological health of those with and without mild TBI history. In this study, we sought to develop and pilot test a self-report electronic survey instrument to measure participants' psychotropic medication histories for use across LIMBIC-CENC study sites. MATERIALS AND METHODS: We developed a new survey instrument measuring psychotropic medication history and fielded it among Service Members and Veterans enrolled in a single site of the LIMBIC-CENC study to evaluate response rates and patterns, and to compare survey responses to prescription data extracted from participants' Veterans Affair (VA) records. Descriptive statistics estimated survey respondents' lifetime psychotropic medication exposures by their TBI history and other demographic and clinical characteristics of interest. We also compared survey responses to participants' VA outpatient prescription records to estimate sensitivity and negative predictive values (NPVs) for participants' self-reported medication exposures relative to this single prescription data source. RESULTS: Among 310 Veterans enrolled at the study site, 249 completed the survey (response rate = 80%), of whom 248 also had VA health records and were included in the analysis. Most (69%) had a history of mild TBI. Over three-fourths of survey respondents (78%) reported ever having used prescription opioids, 26% reported benzodiazepines, 50% reported muscle relaxants, 42% reported antidepressants, 13% reported non-benzodiazepine sedative-hypnotics, 15% reported stimulants, 7% reported mood stabilizers, and 6% reported antipsychotics. Veterans with, versus without, a history of mild TBI were more likely to self-report psychotropic medication history as well as have confirmed receipt of VA prescriptions for each medication class. Using VA records as a criterion standard, the sensitivity of the survey for detecting VA prescriptions ranged from 19% to 84%, while the NPVs ranged from 64% to 97%. Sensitivity and NPVs were similar for participants with, versus without, mild TBI history. CONCLUSIONS: Service Members and Veterans may receive psychotropic medications from multiple sources over their lifetimes. Valid methods to examine and quantify these exposures among those with a history of TBI are important, particularly as we evaluate causes of neurodegenerative disorders in this population over time. The measurement of Veterans' lifetime psychotropic medication exposures using a self-report survey, in combination with health care records, holds promise as a valid approach, but further testing and refinement are needed.

Motivators, Barriers, and Facilitators to Choosing Care in VA Facilities Versus VA-Purchased Care.

Many Veterans receive Department of Veterans Affairs (VA)-purchased care from non-VA facilities but little is known about factors that Veterans consider for this choice. Between May 2020 and August 2021, we surveyed VA-purchased care-eligible VA patients about barriers and facilitators to choosing where to receive care. We examined the association between travel time to their VA facility and their choice of VA-purchased care (VA-paid health care received in non-VA settings) versus VA facility and whether this association was modified by distrust. We received 1,662 responses and 692 (42%) chose a VA facility. Eighty percent reported quality care was in their top three factors that influenced their decision. Respondents with the highest distrust and who lived >1 hr from the nearest VA facility had the lowest predicted probability (PP) of choosing VA (PP 15%; 95% confidence interval: 10%-20%). Veterans value quality of care. VA and other health care systems should consider patient-centered ways to improve and publicize quality and reduce distrust.

Changes in Outpatient Health Care Use After COVID-19 Infection Among Veterans.

Importance: The association of COVID-19 infection with outpatient care utilization is unclear. Many studies reported population surveillance studies rather than comparing outpatient health care use between COVID-19-infected and uninfected cohorts. Objective: To compare outpatient health care use across 6 categories of care (primary care, specialty care, surgery care, mental health, emergency care, and diagnostic and/or other care) between veterans with or without COVID-19 infection. Design, Setting, and Participants: In a retrospective cohort study of Veterans Affairs primary care patients, veterans with COVID-19 infection were matched to a cohort of uninfected veterans. Data were obtained from the Veterans Affairs Corporate Data Warehouse and the Centers for Medicare & Medicaid Services Fee-for-Service Carrier/Physician Supplier file from January 2019 through December 2022. Data analysis was performed from September 2022 to April 2023. Exposure: COVID-19 infection. Main Outcomes and Measures: The primary outcome was the count of outpatient visits after COVID-19 infection. Negative binomial regression models compared outpatient use over a 1-year preinfection period, and peri-infection (0-30 days), intermediate (31-183 days), and long-term (184-365 days) postinfection periods. Results: The infected (202 803 veterans; mean [SD] age, 60.5 [16.2] years; 178 624 men [88.1%]) and uninfected (202 803 veterans; mean [SD] age, 60.4 [16.5] years; 178 624 men [88.1%]) cohorts were well matched across all covariates. Outpatient use in all categories (except surgical care) was significantly elevated during the peri-infection period for veterans with COVID-19 infection compared with the uninfected cohort, with an increase in all visits of 5.12 visits per 30 days (95% CI, 5.09-5.16 visits per 30 days), predominantly owing to primary care visits (increase of 1.86 visits per 30 days; 95% CI, 1.85-1.87 visits per 30 days). Differences in outpatient use attenuated over time but remained statistically significantly higher at 184 to 365 days after infection (increase of 0.25 visit per 30 days; 95% CI, 0.23-0.27 visit per 30 days). One-half of the increased outpatient visits were delivered via telehealth. The utilization increase was greatest for veterans aged 85 years and older (6.1 visits, 95% CI, 5.9-6.3 visits) vs those aged 20 to 44 years (4.8 visits, 95% CI, 4.7-4.8 visits) and unvaccinated veterans (4.5 visits, 95% CI, 4.3-4.6 visits) vs vaccinated veterans (3.2 visits; 95% CI, 3.4-4.8 visits). Conclusions and Relevance: This study found that outpatient use increased significantly in the month after infection, then attenuated but remained greater than the uninfected cohorts' use through 12 months, which suggests that there are sustained impacts of COVID-19 infection.

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.

Regional variation in financial hardship among US veterans during the COVID-19 pandemic.

Geographic variation in hardship, especially health-related hardship, was identified prior to and during the pandemic, but we do not know whether this variation is consistent among Veterans Health Administration (VHA)-enrolled veterans, who reported markedly high rates of financial hardship during the pandemic, despite general and veteran-specific federal policy efforts aimed at reducing hardship. In a nationwide, regionally stratified sample of VHA-enrolled veterans, we examined whether the prevalence of financial hardship during the pandemic varied by US Census region. We found veterans in the South, compared with those in other census regions, reported higher rates of severe-to-extreme financial strain, using up all or most of their savings, being unable to pay for necessities, being contacted by collections, and changing their employment due to the kind of work they could perform. Regional variation in veteran financial hardship demonstrates a need for further research about the role and interaction of federal and state financial-assistance policies in shaping risks for financial hardship as well as potential opportunities to mitigate risks among veterans and reduce variation across regions.

Bias-Based Bullying in California Schools: The Impact of the 2016 Election Cycle.

The purpose of this study is to examine the trends in bias-based bullying between 2013 and 2019 among California youth overall and by type of bias-based bullying and explore the extent to which Trump's announcement of his candidacy for U.S. President in June 2015 impacted these bullying outcomes. We pooled the student-level survey data from multiple waves of the California Healthy Kids Survey. The final study sample included 2,817,487 middle- and high-school students (48.3% female, 47.9% male, and 3.7% not reported). We examined five specific types of bias-based bullying and any bias-based bullying overall. We employed logistic regression and calculated odds ratios to compare differences in the odds of bias-based bullying before and after Trump announced his candidacy for U.S. President. Between 2013 and 2019, approximately one in four students reported experiencing at least one type of bias-based bullying, based on race, ethnicity, or national origin being the most commonly reported. Trump's announcement for candidacy was inconsistently associated with differences in the odds of bias-based bullying. Counties in which a higher proportion of the electorate voted for Trump had slightly higher odds of bullying for any bias-based bullying and for all specific types of bias-based bullying. Findings highlight the need for a commitment to protecting students from bullying regardless of their identity. Public health and education researchers and practitioners should draw on our growing understanding of the different dimensions of bullying in designing, implementing, and evaluating intervention approaches that address bias-based bullying, a particularly important cause given the growing polarization in the United States and the increasing salience of identity in the lead-up to and since the 2016 and 2020 elections.

"The Pain Doesn't Have to Control You." A Qualitative Evaluation of Three Pain Clinics Teaching Nonopioid Pain Management Strategies.

PURPOSE: To explore factors related to effectiveness of nonpharmacological treatment for opioid-dependent patients suffering with chronic pain. APPROACH: A qualitative study incorporating individual interviews and focus group interviews. SETTING: 3 rural Oregon nonopioid pain management clinics. INTERVENTION: A 10-week nonpharmacological educational program incorporating cognitive-behavioral therapy, movement therapy, mindfulness, and other skills. PARTICIPANTS AND METHODS: Across sites, we conducted 9 individual interviews with clinic staff and 3 focus group interviews with 34 patients who had participated in the course. Thematic analysis was used to identify themes within and across respondent groups. RESULTS: Analysis revealed 4 primary themes: program goals; program benefits; characteristics of patients who benefit from the program; coordination of clinic experiences with other care. Several primary findings can be highlighted. The clinics focused on improving patients' quality of life, while opioid use reduction was a potential secondary benefit, driven by patients. Major program benefits included enhanced pain self-management skills, patients' greater assertiveness in communications with healthcare providers, and, in numerous cases, opioid use reduction. Participants were unanimous that predisposition toward active self-management of one's pain was an essential factor for positive outcomes. Patients reported considerable variability in providers' understanding of their clinic participation. CONCLUSION: Nonpharmacological approaches for treating chronic pain can be effective for many patients. Clinics teaching these approaches should be more fully integrated into the healthcare system.

Veterans Health Administration Healthcare Coverage and Medical Financial Hardship in Low-Income Veterans.

INTRODUCTION: The Veterans Health Administration (VA) provides low- to no-cost care to enrolled veterans with low incomes. This study assessed the associations between VA coverage and medical financial hardship among U.S. veterans with low incomes. METHODS: Using 2015-2018 National Health Interview Survey data, veterans aged ≥18 years with incomes <200% of the Federal Poverty Level were identified (crude n=2,468, weighted n=3,872,252). Four types of medical financial hardship were assessed: objective, and subjective material, psychologic, and behavioral medical financial hardship. Survey-weighted proportions of veterans with medical financial hardship were calculated, and adjusted probabilities of medical financial hardship that accounted for Veteran characteristics, year-fixed effects, and survey sampling design were estimated. Analyses were conducted from August through December 2022. RESULTS: Overall, 34.5% of veterans with low incomes had VA coverage. Among veterans without VA coverage, 38.7% had Medicare insurance, 18.2% had Medicaid insurance, 16.5% had private insurance, 13.5% had other public insurance, and 13.1% were uninsured. In adjusted analyses, veterans with VA coverage had lower probabilities of objective (-8.13 percentage point, p=0.008), subjective material (-6.55 percentage point, p=0.034), subjective psychologic (-10.33 percentage point, p=0.003), and subjective behavioral (-6.72 percentage point, p=0.031) medical financial hardship than veterans with Medicare and no VA coverage. CONCLUSIONS: VA coverage was associated with protection against four types of medical financial hardship among veterans with low incomes, yet many are not enrolled. Research is needed to understand reasons these veterans lack VA coverage and to identify strategies to address medical financial hardship.