Trends in Bundled Outpatient Behavioral Health Services in VA-Direct Versus VA-Purchased Care.

The Veterans Health Administration (VA) increasingly purchases community-based care (CC) to improve healthcare access, including behavioral health. In 2018, VA introduced standardized episodes of care (SEOCs) to guide authorization and purchase of CC services for specific indications in a defined timeframe without bundling payment. In this retrospective cross-sectional study, we describe trends in VA and CC behavioral healthcare utilization using the VA Outpatient Psychiatry SEOC definition. Counts of Outpatient Psychiatry SEOC-allowable service and procedure codes during fiscal years 2016-2019 were organized according to four SEOC-defined service types (evaluation and management, laboratory services, psychiatry services, transitional care) and measured as percentages of all included codes. Trends comparing behavioral healthcare utilization between Veterans using any CC versus VA only were analyzed using a linear mixed effects model. We identified nearly 3 million Veterans who registered 60 million qualifying service and procedure codes, with overall utilization increasing 77.8% in CC versus 5.2% in VA. Veterans receiving any CC comprised 3.9% of the cohort and 4.7% of all utilization. When examining service type as a percent of all Outpatient Psychiatry SEOC-allowable care among Veterans using CC, psychiatry services increased 12.2%, while transitional care decreased 8.8%. In regression analysis, shifts in service type utilization reflected descriptive results but with attenuated effect sizes. In sum, Outpatient Psychiatry SEOC-allowable service utilization grew, and service type composition changed, significantly more in CC than in VA. The role of SEOCs and their incentives may be important when evaluating future behavioral healthcare quality and value in bundled services.

Acute hospitalizations and outcomes in Veterans Affairs Hospitals 2011 to 2017.

Hospitals within the Veterans Affairs (VA) health care system exhibited growing use of observation care. It is unknown how this affected VA hospital performance since observation care is not included in acute inpatient measures. To examine changes in VA hospitalization outcomes and whether it was affected by shifting acute inpatient care to observation care. Longitudinal analysis of 986,355 acute hospitalizations and observation stays in 11 states 2011 to 2017. We estimated temporal changes in 30-day mortality, 30-day readmissions, costs, and length of stay (LOS) for all hospitalizations and 6 conditions in adjusted models. Changes in mortality and readmissions were compared including and excluding observation care. A 9% drop in acute hospitalizations was offset by a 157% increase in observation stays 2011 to 2017. A 30-day mortality decreased but readmissions did not when observation stays were included (all P < .05). Mean costs increased modestly; mean LOS was unchanged. There were differences by condition. VA hospital mortality decreased; there was no change in readmissions.

Information and resources VA health system leaders need to manage enrollment and retention for Post-9/11 veterans.

OBJECTIVE: To understand Veterans Health Administration (VA) leaders' information and resource needs for managing post-9/11 Veterans' VA enrollment and retention. DATA SOURCES AND STUDY SETTING: Interviews conducted from March-May 2022 of VA Medical Center (VAMC) leaders (N = 27) across 15 sites, using stratified sampling based on VAMC characteristics: enrollment rates, number of recently separated Veterans in catchment area, and state Medicaid expansion status. STUDY DESIGN: Interview questions were developed using Petersen et al.'s Factors Influencing Choice of Healthcare System framework as a guide. Interviews were transcribed verbatim, and two coders analyzed the interviews using Atlas.ti, a qualitative software program. Coders followed the qualitative coding philosophy developed by Crabtree and Miller, a process of developing codes for salient concepts as they are identified during the analysis process. DATA COLLECTION/EXTRACTION METHODS: Two coders analyzed 22% (N = 6) of the interviews and discussed and adjudicated any discrepancies. One coder independently coded the remainder of the interviews. PRINCIPAL FINDINGS: Several key themes were identified regarding facilitators and barriers for VA enrollment including reputation for high-quality VA care, convenience of VA services, awareness of VA services and benefits, and VA mental health services. Nearly every VA leader actively used tools and data to understand enrollment and retention rates and sought to enroll and retain more Veterans. To improve the management of enrollment and retention, VA leaders would like data shared in an easily understandable format and the capability to share data between the VA and community healthcare systems. CONCLUSIONS: Enrollment and retention information is important for healthcare leaders to guide their health system decisions. Various tools are currently being used to try to understand the data. However, a multifunctional tool is needed to better aggregate the data to provide VA leadership with key information on Veterans' enrollment and retention.

Lower comorbidity scores and severity levels in Veterans Health Administration hospitals: a cross-sectional study.

BACKGROUND: Previous studies found that documentation of comorbidities differed when Veterans received care within versus outside Veterans Health Administration (VHA). Changes to medical center funding, increased attention to performance reporting, and expansion of Clinical Documentation Improvement programs, however, may have caused coding in VHA to change. METHODS: Using repeated cross-sectional data, we compared Elixhauser-van Walraven scores and Medicare Severity Diagnosis Related Group (DRG) severity levels for Veterans' admissions across settings and payers over time, utilizing a linkage of VHA and all-payer discharge data for 2012-2017 in seven US states. To minimize selection bias, we analyzed records for Veterans admitted to both VHA and non-VHA hospitals in the same year. Using generalized linear models, we adjusted for patient and hospital characteristics. RESULTS: Following adjustment, VHA admissions consistently had the lowest predicted mean comorbidity scores (4.44 (95% CI 4.34-4.55)) and lowest probability of using the most severe DRG (22.1% (95% CI 21.4%-22.8%)). In contrast, Medicare-covered admissions had the highest predicted mean comorbidity score (5.71 (95% CI 5.56-5.85)) and highest probability of using the top DRG (35.3% (95% CI 34.2%-36.4%)). CONCLUSIONS: More effective strategies may be needed to improve VHA documentation, and current risk-adjusted comparisons should account for differences in coding intensity.

Racial and Ethnic Differences in Health Care Experiences for Veterans Receiving VA Community Care from 2016 to 2021.

BACKGROUND: Prior research documented racial and ethnic disparities in health care experiences within the Veterans Health Administration (VA). Little is known about such differences in VA-funded community care programs, through which a growing number of Veterans receive health care. Community care is available to Veterans when care is not available through the VA, nearby, or in a timely manner. OBJECTIVE: To examine differences in Veterans' experiences with VA-funded community care by race and ethnicity and assess changes in these experiences from 2016 to 2021. DESIGN: Observational analyses of Veterans' ratings of community care experiences by self-reported race and ethnicity. We used linear and logistic regressions to estimate racial and ethnic differences in community care experiences, sequentially adjusting for demographic, health, insurance, and socioeconomic factors. PARTICIPANTS: Respondents to the 2016-2021 VA Survey of Healthcare Experiences of Patients-Community Care Survey. MEASURES: Care ratings in nine domains. KEY RESULTS: The sample of 231,869 respondents included 24,306 Black Veterans (mean [SD] age 56.5 [12.9] years, 77.5% male) and 16,490 Hispanic Veterans (mean [SD] age 54.6 [15.9] years, 85.3% male). In adjusted analyses pooled across study years, Black and Hispanic Veterans reported significantly lower ratings than their White and non-Hispanic counterparts in five of nine domains (overall rating of community providers, scheduling a recent appointment, provider communication, non-appointment access, and billing), with adjusted differences ranging from - 0.04 to - 0.13 standard deviations (SDs) of domain scores. Black and Hispanic Veterans reported higher ratings with eligibility determination and scheduling initial appointments than their White and non-Hispanic counterparts, and Black Veterans reported higher ratings of care coordination, with adjusted differences of 0.05 to 0.21 SDs. Care ratings improved from 2016 to 2021, but differences between racial and ethnic groups persisted. CONCLUSIONS: This study identified small but persistent racial and ethnic differences in Veterans' experiences with VA-funded community care, with Black and Hispanic Veterans reporting lower ratings in five domains and, respectively, higher ratings in three and two domains. Interventions to improve Black and Hispanic Veterans' patient experience could advance equity in VA community care.