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.

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.

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.

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.

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.