Factors Associated with Delayed Care Among Women Veterans Actively Engaged in Primary Care.

Background: Delaying needed medical care contributes to greater health risks and higher long-term medical costs. Women Veterans with complex medical and mental health needs face increased barriers to timely care access. Objectives: In a sample of women Veterans with recent engagement in Veterans Administration (VA) primary care, we aimed to compare characteristics of women Veterans who delayed care in the past 6 months with those who did not and examine factors associated with self-reported delayed care. Our study aims to inform interventions focused on eliminating health care access disparities among women Veterans. Materials and Methods: An innovation to improve women Veterans' engagement and retention in evidence-based health care for cardiovascular (CV) risk reduction (CV Toolkit) was implemented across five primary care sites within the VA. Women Veterans who were exposed to at least one CV Toolkit component participated in a mailed survey (n = 253). We used multivariate logistic regression to model factors associated with delaying care, including trust in VA providers, positive mental health screening (i.e., positive screen for either depression or anxiety), traumatic experience, self-rated health, and age. Results: Women with any mental health symptoms (odds ratio [OR] 2.42, 95% confidence interval [CI]: 1.23-4.74) and women who had experienced a traumatic event (OR 2.61, 95%CI: 1.11-6.14) were significantly more likely to report delaying care. Conclusions: Our study identified high rates of delayed care-over one-third of respondents-among women Veterans with recent primary care engagement. Mental health symptoms were the most common reported reason for delay among those who delayed care. Clinical Trial registration: NCT02991534.

Factors Associated with Military Sexual Trauma (MST) Disclosure During VA Screening Among Women Veterans.

BACKGROUND: Capturing military sexual trauma (MST) exposure is critical for Veterans' health equity. For many, it improves access to VA services and allows for appropriate care. OBJECTIVE: Identify factors associated with nondisclosure of MST in VA screening among women. DESIGN: Cross-sectional telephone survey linked with VA electronic health record (EHR) data. PARTICIPANTS: Women Veterans using primary care or women's health services at 12 VA facilities in nine states. MAIN MEASURES: Survey self-reported MST (sexual assault and/or harassment during military service), socio-demographics and experiences with VA care, as well as EHR MST results. Responses were categorized as "no MST" (no survey or EHR MST), "MST captured by EHR and survey," and "MST not captured by EHR" (survey MST but no EHR MST). We used stepped multivariable logistic regression to examine "MST not captured by EHR" as a function of socio-demographics, patient experiences, and screening method (survey vs. EHR). KEY RESULTS: Among 1287 women (mean age 50, SD 15), 35% were positive for MST by EHR and 61% were positive by survey. Approximately 38% had "no MST," 34% "MST captured by EHR and survey," and 26% "MST not captured by EHR". In fully adjusted models, odds of "MST not captured by EHR" were higher among Black and Latina women compared to white women (Black: OR = 1.6, 1.2-2.2; Latina: OR = 1.9, 1.0-3.6). Women who endorsed only sexual harassment in the survey (vs. sexual harassment and sexual assault) had fivefold higher odds of "MST not captured by EHR" (OR = 4.9, 3.2-7.3). Women who were screened for MST in the EHR more than once had lower odds of not being captured (OR = 0.3, 0.2-0.4). CONCLUSIONS: VA screening for MST may disproportionately under capture patients from historically minoritized ethnic/racial groups, creating inequitable access to resources. Efforts to mitigate screening disparities could include re-screening and reinforcing that MST includes sexual harassment.

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.

Amiodarone and risk of death in contemporary patients with atrial fibrillation: Findings from The Retrospective Evaluation and Assessment of Therapies in AF study.

BACKGROUND: There are limited data on mortality outcomes associated with use of amiodarone in atrial fibrillation and flutter (AF). METHODS: We evaluated the association of amiodarone use with mortality in patients with newly diagnosed AF using complete data from the Department of Veterans Affairs national health care system. We included patients seen in an outpatient setting within 90 days of a new diagnosis for nonvalvular AF between Veterans Affairs fiscal years 2004 and 2008. Multivariate analysis and propensity-matched Cox proportional hazards regression were used to evaluate the association of amiodarone use to death. RESULTS: Of 122,465 patients (353,168 person-years of follow-up, age 72.1 ± 10.3 years, 98.4% males), amiodarone was prescribed in 11,655 (9.5%). Cumulative, unadjusted mortality rates were higher for amiodarone recipients than for nonrecipients (87 vs 73 per 1,000 person-years, P < .001). However, in multivariate and propensity-matched survival analyses, there was no significant difference in mortality (multivariate hazard ratio 1.01, 95% CI 0.97-1.05, P = .51, and propensity-matched hazard ratio 1.02, 95% CI 0.97-1.07, P = .45). The hazard of death was not modified by age, sex, heart failure, kidney function, ß-blocker use, or warfarin use, but there was evidence of effect modification among patients diagnosed with AF as an inpatient versus outpatient. CONCLUSION: In a national health care system population of newly diagnosed AF, overall use of amiodarone as an early treatment strategy was not associated with mortality.

Differences and trends in stroke prevention anticoagulation in primary care vs cardiology specialty management of new atrial fibrillation: The Retrospective Evaluation and Assessment of Therapies in AF (TREAT-AF) study.

BACKGROUND: Atrial fibrillation and flutter (AF, collectively) cause stroke. We evaluated whether treating specialty influences warfarin prescription in patients with newly diagnosed AF. METHODS: In the TREAT-AF study, we used Veterans Health Administration health record and claims data to identify patients with newly diagnosed AF between October 2004 and November 2008 and at least 1 internal medicine/primary care or cardiology outpatient encounter within 90 days after diagnosis. The primary outcome was prescription of warfarin. RESULTS: In 141,642 patients meeting the inclusion criteria, the mean age was 72.3 ± 10.2 years, 1.48% were women, and 25.8% had cardiology outpatient care. Cardiology-treated patients had more comorbidities and higher mean CHADS2 scores (1.8 vs 1.6, P < .0001). Warfarin use was higher in cardiology-treated vs primary care only-treated patients (68.6% vs 48.9%, P < .0001). After covariate and site-level adjustment, cardiology care was significantly associated with warfarin use (odds ratio [OR] 2.05, 95% CI 1.99-2.11). These findings were consistent across a series of adjusted models (OR 2.05-2.20), propensity matching (OR 1.98), and subgroup analyses (OR 1.58-2.11). Warfarin use in primary-care-only patients declined from 2004 to 2008 (51.6%-44.0%, P < .0001), whereas the adjusted odds of warfarin receipt with cardiology care (vs primary care) increased from 2004 to 2008 (1.88-2.24, P < .0001). CONCLUSION: In patients with newly diagnosed AF, we found large differences in anticoagulation use by treating specialty. A divergent 5-year trend of risk-adjusted warfarin use was observed. Treating specialty influences stroke prevention care and may impact clinical outcomes.