The Impact of Medicaid Enrollment on Veterans Health Administration Enrollees' Behavioral Health Services Use

Contextual factors influencing the association between the Affordable Care Act's Medicaid expansion and Veteran VA-Medicaid dual enrollment

OBJECTIVE

To evaluate changes in dual enrollment after Affordable Care Act Medicaid expansion by VA priority group, (e.g., service connection), sex, and type of state expansion.

STUDY SETTING

Our cohort was all Veterans ages 18-64 enrolled in VA and eligible for benefits due to military service-connection or low income from 2011 to 2016; the unit of analysis was person-year.

STUDY DESIGN

Difference-in-difference and event-study analysis. The outcome was dual VA-Medicaid enrollment for at least 1 month annually. Medicaid expansion, VA priority status, whether a state expanded by a Section 1115 waiver, and sex were independent variables. We controlled for race, ethnicity, age, disease burden, distance to VA facilities, state, and year.

DATA EXTRACTION METHODS

We used data from the VA Corporate Data Warehouse (CDW) regarding age and VA Priority Group to select our cohort of VA-enrolled individuals. We then took the cohort and crossed checked it with Medicaid Analytic Extract (MAX) and T-MSIS Analytic Files (TAF) to determine Medicaid enrollment status.

PRINCIPAL FINDINGS

Service-connected Veterans experienced lower dual-enrollment increases across all sex and state-waiver groups (3.44 percentage points (95% CI: 1.83, 5.05 pp) for women, 3.93 pp (2.98, 4.98) for men, 4.06 pp (2.85, 5.27) for non-waiver states, and 3.00 pp (1.58 to 4.41) for waiver states) than Veterans who enrolled in the VA due to low income (8.19 pp (5.43, 10.95) for women, 9.80 pp (7.06, 12.54) for men, 10.21 pp (7.17, 13.25) for non-waiver states, and 7.39 pp (5.28, 9.50) for waiver states).

CONCLUSIONS

Medicaid expansion is associated with dual enrollment. Dual-enrollment changes are greatest in those enrolled in the VA due to low income, but do not differ by sex or expansion type. Results can help VA identify groups disproportionately likely to have potential care-coordination issues due to usage of multiple health care systems.

Illustration of Continuous Enrollment and Beneficiary Categorization in DoD and VA Infrastructure for Clinical Intelligence

INTRODUCTION

The DoD and VA Infrastructure for Clinical Intelligence (DaVINCI) data-sharing initiative has bridged the gap between DoD and VA data. DaVINCI utilizes the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to map DoD and VA-specific health care codes to a standardized terminology. Although OMOP CDM provides a standardized longitudinal view of health care concepts, it fails in capturing multiple and changing relationships beneficiaries have with DoD and VA as it has a static (vs. yearly) person characteristic table. Furthermore, DoD and VA utilize different policies and terminology to identify their respective beneficiaries, which makes it difficult to track patients longitudinally. The primary purpose of this report is to provide a methodology for categorizing beneficiaries and creating continuous longitudinal patient records to maximize the use of the joint DoD and VA data in DaVINCI.

MATERIALS AND METHODS

For calendar year 2000-2020, we combined DoD and VA OMOP CDM and source databases to uniquely categorize beneficiaries into the following hierarchical groups: Active Duty, Guard, and Reserve Service Members (ADSMs); Separatees; Retirees; Veterans; and Deceased. Once the cohorts were identified, we examined calendar year 2020 health care utilization data using the OMOP VISIT_OCCURRENCE, DRUG_EXPOSURE, MEASUREMENT, and PROCEDURE tables. We also used the Defense Enrollment and Eligibility Reporting System source table to derive enrollment periods for DoD beneficiaries. As VA does not have enrollment plans, we utilized the VA's priority groups (1-5) in the SPATIENT source table to crosswalk the DoD's enrollment concept to the VA. We then assessed lengths of continuous enrollments in DoD and VA and the impact of appending the longitudinal records together.

RESULTS

The majority of the ADSMs utilized the DoD system, but about 60,557 (3%) were seen in the VA for varied types of care. The market share of care provided to ADSMs by the VA varied by specialty and location. For Retirees, the split between DoD (1,625,874 [75%]) and VA (895,992 [41%]) health care utilization was more significant. The value added for utilizing DaVINCI in longitudinal studies was the highest for researchers normally limited to DoD data only. For beneficiaries who had 5 years of continuous enrollment, DaVINCI increased the potential study population by over 202% compared to using DoD data alone and by over 14% compared to VA data alone. Among beneficiaries with 20 years of continuous enrollment, DaVINCI increased the potential study population by over 133% compared to DoD data and by nearly 39% compared to VA data.

CONCLUSIONS

DaVINCI has successfully combined DoD and VA data and utilized OMOP CDM to standardize health care concepts. However, to fully maximize the potential of DaVINCI's DoD and VA OMOP databases, researchers must uniquely categorize the DaVINCI cohort and build longitudinal patient records across DoD and VA. Because of the low other health insurance rates among DoD enrollees and their choice to enroll to a DoD Primary Care Manager, we believe this population to be the least censored in the DoD. Applying a similar concept through VA's priority groups (1-5) would enable researchers to follow ADSMs as they transition from the military.

Differences Between VHA-Delivered and VHA-Purchased Behavioral Health Care in Service and Patient Characteristics

OBJECTIVE

Federal legislation has expanded Veterans Health Administration (VHA) enrollees' access to VHA-purchased "community care." This study examined differences in the amount and type of behavioral health care delivered in VHA and purchased in the community, along with patient characteristics and area supply and demand factors.

METHODS

This retrospective cross-sectional study examined data for 204,094 VHA enrollees with 448,648 inpatient behavioral health stays and 3,467,010 enrollees with 55,043,607 outpatient behavioral health visits from fiscal years 2016 to 2019. Standardized mean differences (SMDs) were calculated for patient and provider characteristics at the outpatient-visit level for VHA and community care. Linear probability models assessed the association between severity of behavioral health condition and site of care.

RESULTS

Twenty percent of inpatient stays were purchased through community care, with severe behavioral health conditions more likely to be treated in VHA inpatient care. In the outpatient setting, community care accounted for 3% of behavioral health care visits, with increasing use over time. For outpatient care, veterans receiving community care were more likely than those receiving VHA care to see clinicians with fewer years of training (SMD=1.06).

CONCLUSIONS

With a large portion of inpatient behavioral health care occurring in the community and increased use of outpatient behavioral health care with less highly trained community providers, coordination between VHA and the community is essential to provide appropriate inpatient follow-up care and address outpatient needs. This is especially critical given VHA's expertise in providing behavioral health care to veterans and its legislative responsibility to ensure integrated care.

Medicaid Expansion and Veterans' Reliance on the VA for Depression Care

Background

In 2001, before the Affordable Care Act (ACA), some states expanded Medicaid coverage to include an array of mental health services, changing veterans' reliance on US Department of Veterans Affairs (VA) services.

Methods

Using Medicaid and VA administrative data from 1999 to 2006, we used a difference-in-difference design to calculate shifts in veterans' reliance on the VA for depression care in New York and Arizona after the 2 states expanded Medicaid coverage to adults in 2001. Demographically matched, neighbor states Pennsylvania and New Mexico/Nevada were used as paired comparisons, respectively. Fractional logit was used to capture the distribution of inpatient and outpatient depression care utilization between the VA and Medicaid, while ordered logit and negative binomial regressions were applied to model Medicaid-VA dual users and per capita utilization of total depression care services, respectively.

Results

Medicaid expansion was associated with a 9.50 percentage point (pp) decrease (95% CI, -14.61 to -4.38) in reliance on the VA for inpatient depression care among service-connected veterans and a 13.37 pp decrease (95% CI, -21.12 to -5.61) among income-eligible veterans. For outpatient depression care, VA reliance decreased by 2.19 pp (95% CI, -3.46 to -0.93) among income-eligible veterans. Changes among service-connected veterans were nonsignificant (-0.60 pp; 95% CI, -1.40 to 0.21).

Conclusions

After Medicaid expansion, veterans shifted depression care away from the VA, with effects varying by health care setting, income- vs service-related eligibility, and state of residence. Issues of overall cost, care coordination, and clinical outcomes deserve further study in the ACA era of Medicaid expansions.

Anticipating VA/non-VA care coordination demand for Veterans at high risk for hospitalization

U.S. Veterans Affairs (VA) patients' multi-system use can create challenges for VA clinicians who are responsible for coordinating Veterans' use of non-VA care, including VA-purchased care ("Community Care") and Medicare.To examine the relationship between drive distance and time-key eligibility criteria for Community Care-and VA reliance (proportion of care received in VA versus Medicare and Community Care) among Veterans at high risk for hospitalization. We used prepolicy data to anticipate the impact of the 2014 Choice Act and 2018 Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION Act), which expanded access to Community Care.Cross-sectional analysis using fractional logistic regressions to examine the relationship between a Veteran's reliance on VA for outpatient primary, mental health, and other specialty care and their drive distance/time to a VA facility.Thirteen thousand seven hundred three Veterans over the age of 65 years enrolled in VA and fee-for-service Medicare in federal fiscal year 2014 who were in the top 10th percentile for hospitalization risk.Key explanatory variables were patients' drive distance to VA > 40 miles (Choice Act criteria) and drive time to VA ≥ 30 minutes for primary and mental health care and ≥60 minutes for specialty care (MISSION Act criteria).Veterans at high risk for hospitalization with drive distance eligibility had increased odds of an outpatient specialty care visit taking place in VA when compared to Veterans who did not meet Choice Act eligibility criteria (odds ratio = 1.10, 95% confidence interval 1.05-1.15). However, drive time eligibility (MISSION Act criteria) was associated with significantly lower odds of an outpatient specialty care visit taking place in VA (odds ratio = 0.69, 95% confidence interval 0.67, 0.71). Neither drive distance nor drive time were associated with reliance for outpatient primary care or mental health care.VA patients who are at high risk for hospitalization may continue to rely on VA for outpatient primary care and mental health care despite access to outside services, but may increase use of outpatient specialty care in the community in the MISSION era, increasing demand for multi-system care coordination.

An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives

BACKGROUND

Hospital performance comparisons for transparency initiatives may be inadequate if peer comparison groups are poorly defined.

OBJECTIVE

The objective of this study was to evaluate a new approach identifying hospital peers for comparison.

DESIGN/SETTING

We used Mahalanobis distance as a new method of developing peer-specific groupings for hospitals to incorporate both external and internal complexity. We compared the overlap in groups with an existing method used by the Veterans' Health Administration's Office for Productivity, Efficiency, and Staffing (OPES).

PARTICIPANTS

One hundred twenty-two acute-care Veterans' Health Administration's Medical Facilities as defined in the OPES fiscal year 2014 report.

MEASURES

Using 15 variables in 9 categories developed from expert input, including both hospital internal measures and community-based external measures, we used principal components analysis and calculated Mahalanobis distance between each hospital pair. This method accounts for correlation between variables and allows for variables having different variances. We identified the 50 closest hospitals, then eliminated any potential peer whose score on the first component was >1 SD from the reference hospital. We compared overlap with OPES measures.

RESULTS

Of 15 variables, 12 have SDs exceeding 25% of their means. The first 2 components of our analysis explain 24.8% and 18.5% of variation among hospitals. Eight of 9 variables scaling positively on the first component measure internal complexity, aligning with OPES groups. Four of 5 variables scaling positively on the second component but not the first are factors from the policy environment; this component reflects a dimension not considered in OPES groups.

CONCLUSION

Individualized peers that incorporate external complexity generate more nuanced comparators to evaluate quality.

Possible Effects on VA Outpatient Care of Expanding Medicaid: Implications of Having Access to Overlapping Publicly Funded Health Care Services

BACKGROUND

Because veterans who use Veterans Health Administration (VA) health care retain VA eligibility while enrolling in Medicaid, increasing Medicaid eligibility may create improved health system access but also create unique challenges for the quality and coordination of health care for veterans. We analyze how pre-Affordable Care Act (ACA) state Medicaid expansions influence VA and Medicaid-funded outpatient care utilization.

MATERIALS AND METHODS

This study uses Difference-in-difference analysis to evaluate association between pre-ACA 2001 Medicaid expansions and VA utilization in a natural experiment. Veterans aged 18-64 years living in a study state during the study period were the participants. Dependent variables included participants' proportion of outpatient care received at the VA, whether a participant recorded care with both Medicaid and the VA, and total outpatient utilization. We analyzed changes between two states that expanded Medicaid in 2001 against three similar states that did not from 1999 to 2006. We adjusted for age, non-White race, gender, disease burden, and distance to VA facilities. This study was approved by the Baylor College of Medicine Institutional Review Board (IRB), protocol number H-40441.

RESULTS

In total, 346,364 VA-enrolled veterans lived in the five study states during the time of our study, 70,987 of whom were enrolled in Medicaid for at least 1 month. For low-income veterans, Medicaid expansion was associated with a 2.88 percentage-point decline in the VA proportion of outpatient services (99% CI -3.26 to -2.49), and a 2.07-point increase (1.80 to 2.35) in the percentage of patients using both VA and Medicaid services. Results also showed small increases in total (VA plus Medicaid) annual per-capita outpatient visits among low-income veterans. We estimate that this corresponds to an annual reduction of 80,338 VA visits across study states (66,155-94,521).

CONCLUSIONS

This study shows usage shifts when Medicaid expansion allows veterans to gain access to non-VA care. It highlights increased potential for care-coordination challenges among VA patients as states implement ACA Medicaid expansion and policymakers consider additional public health insurance options, as well as programs like CHOICE and the MISSION Act that increase veteran choices of traditional VA and community care providers.

Did the Affordable Care Act Decrease Veteran Enrollment in the Veterans Health Administration?

BACKGROUND

Provisions of the Affordable Care Act (ACA) provided nonelderly individuals, including Veterans, with additional health care coverage options. This may impact enrollment for health care through the Veterans Health Administration (VHA). National enrollment data was used to: (1) compare characteristics of enrollees at 3 time points in relation to the implementation of ACA insurance provisions (2012); and (2) examine enrollment trends.

METHODS

The study population included a 10% sample of Veterans under age 65 who were VHA enrollees between January 2012 and September 2015. Demographic and baseline characteristics were compared between 3 enrollment groups: pre-2012, pre-ACA (2012-2013), and post-ACA (2014-2015). Using an interrupted time series approach, we employed pooled logistic regression to assess trends in new VHA enrollment, overall, and by select enrollee characteristics.

RESULTS

A total of 429,833 enrollees were identified. Compared with pre-ACA enrollees, post-ACA enrollees were more likely to be older, have a service-connected disability, live further away from a VHA medical center, but less likely to use primary care within 6 months. The post-ACA quarterly trend in the odds of being a new enrollee was 3% lower (95% confidence interval: 0.96, 0.98) as compared with the pre-ACA trend. This decline was consistent across sex, geography, (all but 1) priority group, and state Medicaid-expansion subgroups.

CONCLUSIONS

The ACA appears to have contributed to a decline in new VHA enrollment. In addition, the profile of newer enrollees differs from that of pre-ACA enrollees. The VHA must continue to monitor trends in demand in order to continue delivering high-quality, efficient care.

HSR Commentary: Linking VA and Non-VA Data to Address Important US Veteran Health Services Research Issues

OBJECTIVE

This commentary summarizes the methods and topics addressed in the special issue of HSR focused on linkage of United States Department of Veterans Affairs (VA) and non-VA datasets. The issue illustrates that researchers are increasingly linking diverse datasets as a valuable method for obtaining outcomes, treatments, and covariates to evaluate and examine health care delivery that includes non-VA services. The issue serves as a reference to VA and non-VA investigators alike who employ data linkage methods to address high-impact clinical and health policy evaluations that span different care systems and different datasets.

Veterans' Reliance on VA Care by Type of Service and Distance to VA for Nonelderly VA-Medicaid Dual Enrollees

BACKGROUND

Not much is known about nonelderly veterans and their reliance on care from the Veterans Affairs (VA) health care system when they have access to non-VA care.

OBJECTIVES

To estimate VA reliance for nonelderly veterans enrolled in VA and Medicaid.

RESEARCH DESIGN

Retrospective, longitudinal analysis of Medicaid claims data and VA administrative data to compare patients' utilization of VA and Medicaid services 12 months before and for up to 12 months after Medicaid enrollment began.

SUBJECTS

Nonelderly veterans (below 65 y) receiving VA care and newly enrolled in Medicaid, calendar years 2006-2010 (N=19,890).

MEASURES

VA reliance (proportion of care received in VA) for major categories of outpatient and inpatient care.

RESULTS

Patients used VA outpatient care at similar levels after enrolling in Medicaid with the exceptions of emergency department (ED) and obstetrics/gynecology care, which decreased. VA inpatient utilization was similar after Medicaid enrollment for most types of care. VA-adjusted outpatient reliance was highest for mental health care (0.99) and lowest for ED care (0.02). VA-adjusted inpatient reliance was highest for respiratory (0.80) and cancer stays (0.80) and lowest for musculoskeletal stays (0.20). Associations between VA reliance and distance to VA providers varied by type of care.

CONCLUSIONS

Veterans dually enrolled in Medicaid received most of their outpatient care from the VA except ED, obstetrics/gynecology, and dental care. Patients received most of their inpatient care from Medicaid except mental health, respiratory, and cancer care. Sensitivity to travel distance to VA providers explained some of these differences.