The effects of the Veterans Health Administration's Referral Coordination Initiative on referral patterns and waiting times for specialty care

OBJECTIVE

To investigate whether the Veterans Health Administration's (VA) 2019 Referral Coordination Initiative (RCI) was associated with changes in the proportion of VA specialty referrals completed by community-based care (CC) providers and mean appointment waiting times for VA and CC providers.

DATA SOURCES/STUDY SETTINGS

Monthly facility level VA data for 3,097,366 specialty care referrals for eight high-volume specialties (cardiology, dermatology, gastroenterology, neurology, ophthalmology, orthopedics, physical therapy, and podiatry) from October 1, 2019 to May 30, 2022.

STUDY DESIGN

We employed a staggered difference-in-differences approach to evaluate RCI's effects on referral patterns and wait times. Our unit of analysis was facility-month. We dichotomized facilities into high and low RCI use based on the proportion of total referrals for a specialty. We stratified our analysis by specialty and the staffing model that high RCI users adopted: centralized, decentralized, and hybrid.

DATA COLLECTION/EXTRACTION METHODS

Administrative data on referrals and waiting times were extracted from the VA's corporate data warehouse. Data on staffing models were provided by the VA's Office of Integrated Veteran Care.

PRINCIPAL FINDINGS

We did not reject the null hypotheses that high RCI use do not change CC referral rates or waiting times in any of the care settings for most specialties. For example, high RCI use for physical therapy-the highest volume specialty studied-was associated with -0.054 (95% confidence interval [CI]: -0.114 to 0.006) and 2.0 days (95% CI: -4.8 to 8.8) change in CC referral rate and waiting time at CC providers, respectively, among centralized staffing model adopters.

CONCLUSIONS

In the initial years of the RCI program, RCI does not have a measurable effect on waiting times or CC referral rates. Our findings do not support concerns that RCI might be impeding Veterans' access to CC providers. Future evaluations should examine whether RCI facilitates Veterans' ability to receive care in their preferred setting.

Growth of community-based immunotherapy treatment in the Veterans Health Administration

BACKGROUND

The MISSION and CHOICE Acts expanded the Veterans Health Administration's (VA) capacity to purchase immunotherapy services for VA patients from community-based providers. Our objective was to identify predictors of community-based immunotherapy treatment, and assess differences in cost and utilization across community treatment settings METHODS: We examined claims for 21,257 patients who started immunotherapy treatment between 2015 and 2020. We assessed growth in VA community-based immunotherapy care, predictors of community-based immunotherapy treatment using multivariable logistic regression based on patients' sociodemographic and clinical characteristics. We compared utilization and costs among those who received community-based immunotherapy services in hospital outpatient departments (HOPDs) versus physician office settings (POs).

RESULTS

The proportion of community-based immunotherapy in the VA increased from 5.3% in 2015 to 32.1% in 2020, with total annual costs of immunotherapy growing from $6.1 million to $187 million. Older, married, and rural patients and those with more comorbidities were more likely than younger, single, or urban patients to be treated in the community. Black patients were more likely to be treated in the VA. Respiratory Cancer was the most common cancer type in both settings. Among community immunotherapy patients, we observed no meaningful differences in the number of units administered, the unit drug costs, or the cost per immunotherapy visit between POs and HOPDs.

CONCLUSION

Drug costs did not differ widely across HOPDs and POs among VA patients who receive community-based immunotherapy.

Achieving transformation to lean management systems in health care

OBJECTIVE

To understand what factors and organizational dynamics enable Lean transformation of health care organizations.

DATA SOURCES

Primary data were collected through two waves of interviews in 2016-2017 with leaders and staff at seven veterans affairs medical centers participating in Lean enterprise transformation.

STUDY DESIGN

Using an observational study design, for each site we coded and rated seven potential enablers of transformation. The outcome measure was the extent of Lean transformation, constructed by coding and rating 11 markers of depth and spread of transformation. Using multivalue coincidence analysis (CNA), we identified enablers that distinguished among sites having different levels of transformation. We identified representative quotes for the enablers.

DATA COLLECTION METHODS

We interviewed 121 executive leaders, middle managers, expert consultants, systems redesign staff, frontline supervisors, and staff.

PRINCIPAL FINDINGS

Two sites achieved high Lean transformation, three medium, and two low. Together leadership support and capability development were sufficient for the three-level Lean transformation outcomes with 100% consistency and 100% coverage. High scores on both corresponded to high Lean transformation; medium on either one corresponded to medium transformation; and low on both corresponded to low transformation. Additionally, low scores in communication and availability of data and very low scores in alignment characterized low-transformation sites. Sites with high leadership support also had a high veteran engagement.

CONCLUSIONS

This multisite study develops a novel measure of the extent of organization-wide Lean transformation and uses CNA to identify enablers linked to transformation. It provides insights into why and how some organizations are more successful at transformation than others. Findings support the applicability of the organization transformation model that guided the study and highlight the roles of executive leadership and capability development in the dynamics of transformation.

Variation in initial and continued use of primary, mental health, and specialty video care among Veterans

OBJECTIVE

To identify which Veteran populations are routinely accessing video-based care.

DATA SOURCES AND STUDY SETTING

National, secondary administrative data from electronic health records at the Veterans Health Administration (VHA), 2019-2021.

STUDY DESIGN

This retrospective cohort analysis identified patient characteristics associated with the odds of using any video care; and then, among those with a previous video visit, the annual rate of video care utilization. Video care use was reported overall and stratified into care type (e.g., primary, mental health, and specialty video care) between March 10, 2020 and February 28, 2021.

DATA COLLECTION

Veterans active in VA health care (>1 outpatient visit between March 11, 2019 and March 10, 2020) were included in this study.

PRINCIPAL FINDINGS

Among 5,389,129 Veterans in this evaluation, approximately 27.4% of Veterans had at least one video visit. We found differences in video care utilization by type of video care: 14.7% of Veterans had at least one primary care video visit, 10.6% a mental health video visit, and 5.9% a specialty care video visit. Veterans with a history of housing instability had a higher overall rate of video care driven by their higher usage of video for mental health care compared with Veterans in stable housing. American Indian/Alaska Native Veterans had reduced odds of video visits, yet similar rates of video care when compared to White Veterans. Low-income Veterans had lower odds of using primary video care yet slightly elevated rates of primary video care among those with at least one video visit when compared to Veterans enrolled at VA without special considerations.

CONCLUSIONS

Variation in video care utilization patterns by type of care identified Veteran populations that might require greater resources and support to initiate and sustain video care use. Our data support service specific outreach to homeless and American Indian/Alaska Native Veterans.

Effect of mental health staffing inputs on suicide-related events

OBJECTIVE

To estimate the effects of changes in Veterans Health Administration (VHA) mental health services staffing levels on suicide-related events among a cohort of Veterans.

DATA SOURCES

Data were obtained from the VHA Corporate Data Warehouse, the Department of Defense and Veterans Administration Infrastructure for Clinical Intelligence, the VHA survey of enrollees, and customized VHA databases tracking suicide-related events. Geographic variables were obtained from the Area Health Resources Files and the Centers for Medicare and Medicaid Services.

STUDY DESIGN

We used an instrumental variables (IV) design with a Heckman correction for non-random partial observability of the use of mental health services. The principal predictor was a measure of provider staffing per 10,000 enrollees. The outcome was the probability of a suicide-related event.

DATA COLLECTION/EXTRACTION METHODS

Data were obtained for a cohort of Veterans who recently separated from active service.

PRINCIPAL FINDINGS

From 2014 to 2018, the per-pay period probability of a suicide-related event among our cohort was 0.05%. We found that a 1% increase in mental health staffing led to a 1.6 percentage point reduction in suicide-related events. This was driven by the first tertile of staffing, suggesting diminishing returns to scale for mental health staffing.

CONCLUSIONS

VHA facilities appear to be staffing-constrained when providing mental health care. Targeted increases in mental health staffing would be likely to reduce suicidality.

Short-term effects of comprehensive caregiver supports on caregiver outcomes

OBJECTIVE

To estimate the association of the Veterans Health Administration (VHA) Program of Comprehensive Assistance for Family Caregivers (PCAFC) implemented in 2011 with caregiver health and health care use.

DATA SOURCES

VHA claims and electronic health records from May 2009 to May 2018.

STUDY DESIGN

Using a retrospective, pre-post study design with inverse probability of treatment weights to address selection into treatment, we examine the association of PCAFC on caregivers who are veterans: (1) outpatient primary, specialty, and mental health care visits; (2) probability of uncontrolled hypertension and anxiety/depression; and (3) VHA health care costs. We compare outcomes for caregivers approved for PCAFC (treatment) to caregivers denied PCAFC (comparison).

DATA COLLECTION/EXTRACTION METHODS

Not applicable.

PRINCIPAL FINDINGS

In the year pre-application, we observe similar probabilities of having any VHA primary care (~36%), VHA specialty care (~24%), and VHA or VHA-purchased mental health care (~22%) for treatment and comparison caregivers. In the year post-application, treated caregivers had a 5.89 percentage point larger probability of any outpatient VHA primary care (p = 0.002) and 4.34 percentage points larger probability of any outpatient mental health care use (p = 0.014). Post-application, probabilities of having uncontrolled hypertension or diagnosed anxiety/depression were higher for both treated and comparison groups. In the second year post-application, treated caregivers had a 1.88 percentage point larger probability of uncontrolled hypertension (p = 0.019) and 4.68 percentage points larger probability of diagnosed anxiety/depression (predicted probabilities: treated = 0.30; comparison = 0.25; p = 0.005). We find no evidence of differences in VHA total costs by PCAFC status.

CONCLUSIONS

Our findings that PCAFC enrollment is associated with increased health care diagnosis and service use may reflect improved access for previously unmet needs in the population of veteran caregivers for veterans in PCAFC. The costs and value of these increases can be weighed against other effects of the program to inform national policies supporting caregivers.