Veterans' Use of Veterans Health Administration Primary Care in an Era of Expanding Choice

Comparing Quality, Costs, and Outcomes of VA and Community Primary Care for Patients with Diabetes

BACKGROUND

The Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act expanded access to independent community providers outside the Veterans Health Administration (VA). Little is known how quality, costs, and outcomes of primary care received in the community compare to that of the VA.

OBJECTIVE

To compare quality, costs, and outcomes of community and VA-provided primary care for patients with diabetes over a 12-month episode.

DESIGN

A cross-sectional study using VA administrative data and community care claims. Adjusted analyses were conducted using inverse probability weighted regression adjustment to balance patient characteristics.

PARTICIPANTS

Veterans with diabetes receiving primary care in the VA or community.

MAIN MEASURES

Quality measures included receipt of hemoglobin A1C tests, eye exams, microalbumin urine tests, and flu shots. Outcomes were measured by hospitalizations for an ambulatory care sensitive condition (ACSC). Costs were measured for VA and community outpatient care, inpatient care, and prescription drugs.

KEY RESULTS

There were 652,648 VA patients and 3650 community care patients. VA patients were less likely to be White, had shorter mean drive time to VA primary care, and were less likely to be rural than community care patients. In adjusted analyses, community care patients had significantly lower probability of receiving a hemoglobin A1C test, eye exam, microalbumin urine test, and flu shot compared to the VA group. There was no difference in probability of an ACSC hospitalization. Community care patients had higher mean total costs ($1741 [95% CI, $431, $3052]), driven by higher inpatient and prescription drug costs but lower emergency care costs than VA patients.

CONCLUSION

Patients receiving community primary care had worse diabetes quality and higher costs than patients receiving VA primary care. There was no difference in health outcomes. Care provided by an integrated delivery system may have advantages in quality and value.

Racial and Ethnic and Rural Variations in Access to Primary Care for Veterans Following the MISSION Act

Importance

The 2018 Veterans Affairs Maintaining Internal Systems and Strengthening Integrated Outside Networks (VA MISSION) Act was implemented to increase timely access to care by expanding veterans' opportunities to receive Veterans Affairs (VA)-purchased care in the community (community care [CC]). Because health equity is a major VA priority, it is important to know whether Black and Hispanic veterans compared with White veterans experienced equitable access to primary care within the VA MISSION Act.

Objective

To examine whether utilization of and wait times for primary care differed between Black and Hispanic veterans compared with White veterans in rural and urban areas after the implementation of the VA MISSION Act.

Design, Setting, and Participants

This cross-sectional study used VA and CC outpatient and consult data from the VA's Corporate Data Warehouse for fiscal years 2021 to 2022 (October 1, 2020, to September 30, 2022). Separate fixed-effects multivariable models were run to predict CC utilization and wait times. Each model was run twice, once comparing Black and White veterans and then comparing Hispanic and White veterans. Adjusted risk ratios (ARRs) were calculated for Black and Hispanic veterans compared with White veterans within rurality status for both outcomes.

Main Outcomes and Measures

VA and CC primary care utilization as measured by primary care visits (utilization cohort); VA and CC primary care access as measured by mean wait times (access cohort).

Results

A total of 5 046 087 veterans (994 517 [19.7%] Black, 390 870 [7.7%] Hispanic, and 3 660 700 [72.6%] White individuals) used primary care from fiscal years 2021 to 2022. Utilization increased for all 3 racial and ethnicity groups, more so in CC than VA primary care. ARRs were significantly less than 1 regardless of rurality status, indicating Black and Hispanic veterans compared with White veterans were less likely to utilize CC for primary care. There were 468 246 primary care consultations during the study period. The overall mean (SD) wait time was 33.3 (32.4) days. Despite decreases in wait times over time, primary care wait times remained longer in CC than in VA. Black veterans compared with White veterans had significantly longer wait times in CC (ARRs >1) but significantly shorter wait times in VA (ARRS <1) regardless of rurality status in VA and CC. CC wait times for Hispanic veterans compared with White veterans were longer in rural areas only and in VA rural and urban areas (ARRs >1).

Conclusion and Relevance

The results of this cross-sectional study suggest that additional research should explore the determinants and implications of utilization differences among Black and Hispanic veterans compared with White veterans. Efforts to promote equitable primary care access for all veterans are needed so that policy changes can be more effective in ensuring timely access to care for all veterans.

The impact of patient-provider relationships on choosing between VA and VA-purchased care: A qualitative study of health care decision-making among rural veterans

PURPOSE

Since the Choice Act in 2014, many Veterans have had greater options for seeking Veteran Affairs (VA)-purchased care in the community. We investigated factors that influence rural Veterans' decisions regarding where to seek care.

METHODS

We utilized semi-structured telephone interviews to query Veterans living in rural or highly rural areas of Midwestern states about their health care options, preferences, and experiences. Interviews were recorded and transcribed, thematically coded, and deductively analyzed using a socioecological approach.

FINDINGS

Forty rural Veterans (20 men/20 women) ages 28-76 years completed interviews in 2019. We found that rural Veterans often spoke about their relationships and interactions with providers as an important factor in deciding where to seek care. They expressed three socioecological qualities of patient-provider relationships that affected their decisions: (1) personal level-rural Veterans traveled longer distances for more compatible patient-provider relationships; (2) interpersonal level-they sought stable patient-provider relationships that encouraged familiarity, trust, and communication; and (3) organizational level-they emphasized shared identities and expertise that fostered a sense of belonging with their provider. Participants also described how impersonal interactions, status differences, and staff turnover impacted their choice of provider and were disruptive to patient-provider relationships.

CONCLUSIONS

Rural Veterans' interview responses suggest exploring innovative ways to measure socioecological dimensions (i.e., personal, interpersonal, and organizational) of access-related decisions and patient-provider relationships to better understand health care barriers and needs. Such measures align with the VA's Whole Health approach that emphasizes person-centered care and the value of social relationships to Veterans' health.

Prevalence and Correlates of VA-Purchased Community Care Use Among Post-9/11-Era Veterans With Traumatic Brain Injury

OBJECTIVE

Post-9/11-era veterans with traumatic brain injury (TBI) have greater health-related complexity than veterans overall, and may require coordinated care from TBI specialists such as those within the Department of Veterans Affairs (VA) healthcare system. With passage of the Choice and MISSION Acts, more veterans are using VA-purchased care delivered by community providers who may lack TBI training. We explored prevalence and correlates of VA-purchased care use among post-9/11 veterans with TBI.

SETTING

Nationwide VA-purchased care from 2016 through 2019.

PARTICIPANTS

Post-9/11-era veterans with clinician-confirmed TBI based on VA's Comprehensive TBI Evaluation (N = 65 144).

DESIGN

This was a retrospective, observational study.

MAIN MEASURES

Proportions of veterans who used VA-purchased care and both VA-purchased and VA-delivered outpatient care, overall and by study year. We employed multivariable logistic regression to assess associations between veterans' sociodemographic, military history, and clinical characteristics and their likelihood of using VA-purchased care from 2016 through 2019.

RESULTS

Overall, 51% of veterans with TBI used VA-purchased care during the study period. Nearly all who used VA-purchased care (99%) also used VA-delivered outpatient care. Veterans' sociodemographic, military, and clinical characteristics were associated with their likelihood of using VA-purchased care. Notably, in adjusted analyses, veterans with moderate/severe TBI (vs mild), those with higher health risk scores, and those diagnosed with posttraumatic stress disorder, depression, anxiety, substance use disorders, or pain-related conditions had increased odds of using VA-purchased care. Additionally, those flagged as high risk for suicide also had higher odds of VA-purchased care use.

CONCLUSIONS

Veterans with TBI with greater health-related complexity were more likely to use VA-purchased care than their less complex counterparts. The risks of potential care fragmentation across providers versus the benefits of increased access to care are unknown. Research is needed to examine health and functional outcomes among these veterans.

"It's Like Finding Your Way Through the Labyrinth": a Qualitative Study of Veterans' Experiences Accessing Healthcare

BACKGROUND

The 2014 Veterans Choice Act and subsequent 2018 Veteran's Affairs (VA) Maintaining Systems and Strengthening Integrated Outside Networks Act (MISSION Act) are legislation which clarified Veteran access to healthcare provided by non-VA clinicians (community care). These policies are of particular importance to Veterans living in rural areas, who tend to live farther from VA medical facilities than urban Veterans.

OBJECTIVE

To understand Veterans' experiences of the MISSION Act and how it impacted their access to primary care to inform future interventions with a focus on reaching rural Veterans.

DESIGN

Qualitative descriptive design.

PARTICIPANTS

United States (US) Veterans in Northwestern states engaged in VA and/or community care.

APPROACH

Semi-structured interviews were conducted with a purposive sample of Veterans between August 2020 and September 2021. Interview domains focused on barriers and facilitators of healthcare access. Transcripts were analyzed using thematic analysis.

KEY RESULTS

We interviewed 28 Veterans; 52% utilized community care as their primary source of care and 36% were from rural or frontier areas. Three main themes emerged: (1) Veterans described their healthcare experiences as positive but also frustrating (billing and prior authorization were noted as top frustrations); (2) Veterans with medical complexities, living far from healthcare services, and/or seeking women's healthcare services experienced additional frustration due to increased touch points with VA systems and processes; and (3) financial resources and/or knowledge of the VA system insulated Veterans from frustration with healthcare navigation.

CONCLUSIONS

Despite provisions in the MISSION Act, Veteran participants described persistent barriers to healthcare access. Patient characteristics that required increased interaction with VA processes exacerbated these barriers, while financial resources and VA system knowledge mitigated them. Interventions to improve care coordination or address access barriers across VA and community care settings could improve access and reduce health inequities for Veterans-especially those with medical complexities, those living far from healthcare services, or those seeking women's healthcare.

Differences in adverse outcomes across race and ethnicity among Veterans with similar predicted risks of an overdose or suicide-related event

OBJECTIVE

To evaluate the degree to which differences in incidence of mortality and serious adverse events exist across patient race and ethnicity among Veterans Health Administration (VHA) patients receiving outpatient opioid prescriptions and who have similar predicted risks of adverse outcomes. Patients were assigned scores via the VHA Stratification Tool for Opioid Risk Mitigation (STORM), a model used to predict the risk of experiencing overdose- or suicide-related health care events or death. Individuals with the highest STORM risk scores are targeted for case review.

DESIGN

Retrospective cohort study of high-risk veterans who received an outpatient prescription opioid between 4/2018-3/2019.

SETTING

All VHA medical centers.

PARTICIPANTS

In total, 84 473 patients whose estimated risk scores were between 0.0420 and 0.0609, the risk scores associated with the top 5%-10% of risk in the STORM development sample.

METHODS

We examined the expected probability of mortality and serious adverse events (SAEs; overdose or suicide-related events) given a patient's risk score and race.

RESULTS

Given a similar risk score, Black patients were less likely than White patients to have a recorded SAE within 6 months of risk score calculation. Black, Hispanic, and Asian patients were less likely than White patients with similar risk scores to die within 6 months of risk score calculation. Some of the mortality differences were driven by age differences in the composition of racial and ethnic groups in our sample.

CONCLUSIONS

Our results suggest that relying on the STORM model to identify patients who may benefit from an interdisciplinary case review may identify patients with clinically meaningful differences in outcome risk across race and ethnicity.

The impact of dual VA-Medicare use on a data-driven clinical management tool for older Veterans with multimorbidity

BACKGROUND

Healthcare systems are increasingly turning to data-driven approaches, such as clustering techniques, to inform interventions for medically complex older adults. However, patients seeking care in multiple healthcare systems may have missing diagnoses across systems, leading to misclassification of resulting groups. We evaluated the impact of multi-system use on the accuracy and composition of multimorbidity groups among older adults in the Veterans Health Administration (VA).

METHODS

Eligible patients were VA primary care users aged ≥65 years and in the top decile of predicted 1-year hospitalization risk in 2018 (n = 558,864). Diagnoses of 26 chronic conditions were coded using a 24-month lookback period and input into latent class analysis (LCA) models. In a random 10% sample (n = 56,008), we compared the resulting model fit, class profiles, and patient assignments from models using only VA system data versus VA with Medicare data.

RESULTS

LCA identified six patient comorbidity groups using VA system data. We labeled groups based on diagnoses with higher within-group prevalence relative to the average: Substance Use Disorders (7% of patients), Mental Health (15%), Heart Disease (22%), Diabetes (16%), Tumor (14%), and High Complexity (10%). VA with Medicare data showed improved model fit and assigned more patients with high accuracy. Over 70% of patients assigned to the Substance, Mental Health, High Complexity, and Tumor groups using VA data were assigned to the same group in VA with Medicare data. However, 41.9% of the Heart Disease group and 14.7% of the Diabetes group were reassigned to a new group characterized by multiple cardiometabolic conditions.

CONCLUSIONS

The addition of Medicare data to VA data for older high-risk adults improved clustering model accuracy and altered the clinical profiles of groups. Accessing or accounting for multi-system data is key to the success of interventions based on empiric grouping in populations with dual-system use.

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.

Travel Burden as a Measure of Healthcare Access and the Impact of Telehealth within the Veterans Health Administration

BACKGROUND

Travel is a major barrier to healthcare access for Veteran Affairs (VA) patients, and disproportionately affects rural Veterans (approximately one quarter of Veterans). The CHOICE/MISSION acts' intent is to increase timeliness of care and decrease travel, although not clearly demonstrated. The impact on outcomes remains unclear. Increased community care increases VA costs and increases care fragmentation. Retaining Veterans within the VA is a high priority, and reduction of travel burdens will help achieve this goal. Sleep medicine is presented as a use case to quantify travel related barriers.

OBJECTIVE

The Observed and Excess Travel Distances are proposed as two measures of healthcare access, allowing for quantification of healthcare delivery related to travel burden. A telehealth initiative that reduced travel burden is presented.

DESIGN

Retrospective, observational, utilizing administrative data.

SUBJECTS

VA patients with sleep related care between 2017 and 2021. In-person encounters: Office visits and polysomnograms; telehealth encounters: virtual visits and home sleep apnea tests (HSAT).

MAIN MEASURES

Observed distance: distance between Veteran's home and treating VA facility. Excess distance: difference between where Veteran received care and nearest VA facility offering the service of interest. Avoided distance: distance between Veteran's home and nearest VA facility offering in-person equivalent of telehealth service.

KEY RESULTS

In-person encounters peaked between 2018 and 2019, and have down trended since, while telehealth encounters have increased. During the 5-year period, Veterans traveled an excess 14.1 million miles, while 10.9 million miles of travel were avoided due to telehealth encounters, and 48.4 million miles were avoided due to HSAT devices.

CONCLUSIONS

Veterans often experience a substantial travel burden when seeking medical care. Observed and excess travel distances are valuable measures to quantify this major healthcare access barrier. These measures allow for assessment of novel healthcare approaches to improve Veteran healthcare access and identify specific regions that may benefit from additional resources.

Jumping Through Hoops: Community Care Clinician and Staff Experiences Providing Primary Care to Rural Veterans

BACKGROUND

The 2019 VA Maintaining Systems and Strengthening Integrated Outside Networks Act, or MISSION Act, aimed to improve rural veteran access to care by expanding coverage for services in the community. Increased access to clinicians outside the US Department of Veterans Affairs (VA) could benefit rural veterans, who often face obstacles obtaining VA care. This solution, however, relies on clinics willing to navigate VA administrative processes.

OBJECTIVE

To investigate the experiences rural, non-VA clinicians and staff have while providing care to rural veterans and inform challenges and opportunities for high-quality, equitable care access and delivery.

DESIGN

Phenomenological qualitative study.

PARTICIPANTS

Non-VA-affiliated primary care clinicians and staff in the Pacific Northwest.

APPROACH

Semi-structured interviews with a purposive sample of eligible clinicians and staff between May and August 2020; data analyzed using thematic analysis.

KEY RESULTS

We interviewed 13 clinicians and staff and identified four themes and multiple challenges related to providing care for rural veterans: (1) Confusion, variability and delays for VA administrative processes, (2) clarifying responsibility for dual-user veteran care, (3) accessing and sharing medical records outside the VA, and (4) negotiating communication pathways between systems and clinicians. Informants reported using workarounds to combat challenges, including using trial and error to gain expertise in VA system navigation, relying on veterans to act as intermediaries to coordinate their care, and depending on individual VA employees to support provider-to-provider communication and share system knowledge. Informants expressed concerns that dual-user veterans were more likely to have duplication or gaps in services.

CONCLUSIONS

Findings highlight the need to reduce the bureaucratic burden of interacting with the VA. Further work is needed to tailor structures to address challenges rural community providers experience and to identify strategies to reduce care fragmentation across VA and non-VA providers and encourage long-term commitment to care for veterans.

VA-Delivered or VA-Purchased Care: Important Factors for Veterans Navigating Care Decisions

BACKGROUND/OBJECTIVE

The VA MISSION Act aimed to increase Veterans' access to care by allowing eligible Veterans to use VA-paid care from non-VA providers ("VA-purchased care"). We interviewed Veterans who were eligible for both VA-delivered and VA-purchased care to examine factors they consider when making decisions about whether to use VA-delivered or VA-purchased care.

METHODS

We conducted semi-structured interviews with 28 Veterans across the USA who were eligible for VA-delivered and VA-purchased care, using deductive and inductive analysis to develop themes. Participants were recruited from a survey about healthcare access and decision-making. More than half of participants lived in rural areas, 21 were men, and 25 were > 50 years old.

KEY RESULTS

Veteran participants identified (1) high-quality relationships with providers based on mutual trust, empathy, authenticity, and continuity of care, and (2) a positive environment or "eco-system of care" characterized by supportive interactions with staff and other Veterans, and exemplary customer service as integral to their decisions about where to receive care. These preferences influenced their engagement with VA and non-VA providers. We discovered corresponding findings related to Veterans' information needs. When making decisions around where to receive care, participants said they would like more information about VA and non-VA providers and services, and about coordination of care and referrals, including understanding processes and implications of utilizing VA-purchased care.

DISCUSSION/CONCLUSION

Current VA-purchased care eligibility determinations focus on common access metrics (e.g., wait times, distance to care). Yet, Veterans discussed other important factors for navigating care decisions, including patient-provider relationship quality and the larger healthcare environment (e.g., interactions with staff and other Veterans). Our findings point to the need for health systems to collect and provide information on these aspects of care to ensure care decisions reflect what is important to Veterans when navigating where to receive care.

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.

Disparities in Wait Times for Care Among US Veterans by Race and Ethnicity

Importance

Prior studies indicate that Black and Hispanic vs White veterans wait longer for care. However, these studies do not capture the COVID-19 pandemic, which caused care access disruptions, nor implementation of the US Department of Veterans Affairs (VA) Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION), which is intended to improve care access by increasing veterans' options to use community clinicians.

Objective

To determine whether wait times increased differentially for Black and Hispanic compared with White veterans from the pre-COVID-19 to COVID-19 periods given concurrent MISSION implementation.

Design, Setting, and Participants

This cross-sectional study used data from the VA's Corporate Data Warehouse for fiscal years 2019 to 2021 (October 1, 2018, to September 30, 2021). Participants included Black, Hispanic, and White veterans with a new consultation for outpatient cardiology and/or orthopedic services during the study period. Multivariable mixed-effects models were used to estimate individual-level adjusted wait times and a likelihood ratio test of the significance of wait time disparity change over time.

Main Outcomes and Measures

Overall mean wait times and facility-level adjusted relative mean wait time ratios.

Results

The study included 1 162 148 veterans (mean [SD] age, 63.4 [14.4] years; 80.8% men). Significant wait time disparities were evident for orthopedic services (eg, Black veterans had wait times 2.09 [95% CI, 1.57-2.61] days longer than those for White veterans) in the pre-COVID-19 period, but not for cardiology services. Mean wait times increased from the pre-COVID-19 to COVID-19 periods for both services for all 3 racial and ethnic groups (eg, Hispanic wait times for cardiology services increased 5.09 [95% CI, 3.62-6.55] days). Wait time disparities for Black veterans (4.10 [95% CI, 2.44-5.19] days) and Hispanic veterans (4.40 [95% CI, 2.76-6.05] days) vs White veterans (3.75 [95% CI, 2.30-5.19] days) increased significantly from the pre-COVID-19 to COVID-19 periods (P < .001). During the COVID-19 period, significant disparities were evident for orthopedic services (eg, mean wait times for Hispanic vs White veterans were 1.98 [95% CI, 1.32-2.64] days longer) but not for cardiology services. Although there was variation in wait time ratios across the 140 facilities, only 6 facility wait time ratios were significant during the pre-COVID-19 period and 26 during the COVID-19 period.

Conclusions and Relevance

These findings suggest that wait time disparities increased from the pre-COVID-19 to COVID-19 periods, especially for orthopedic services for both Black and Hispanic veterans, despite MISSION's goal to improve access. Facility-level analyses identified potential sites that could be targeted to reduce disparities.

Opioid use and opioid use disorder in mono and dual-system users of veteran affairs medical centers

Introduction

Efforts to achieve opioid guideline concordant care may be undermined when patients access multiple opioid prescription sources. Limited data are available on the impact of dual-system sources of care on receipt of opioid medications.

Objective

We examined whether dual-system use was associated with increased rates of new opioid prescriptions, continued opioid prescriptions and diagnoses of opioid use disorder (OUD). We hypothesized that dual-system use would be associated with increased odds for each outcome.

Methods

This retrospective cohort study was conducted using Veterans Administration (VA) data from two facilities from 2015 to 2019, and included active patients, defined as Veterans who had at least one encounter in a calendar year (2015-2019). Dual-system use was defined as receipt of VA care as well as VA payment for community care (non-VA) services. Mono users were defined as those who only received VA services. There were 77,225 dual-system users, and 442,824 mono users. Outcomes were three binary measures: new opioid prescription, continued opioid prescription (i.e., received an additional opioid prescription), and OUD diagnosis (during the calendar year). We conducted a multivariate logistic regression accounting for the repeated observations on patient and intra-class correlations within patients.

Results

Dual-system users were significantly younger than mono users, more likely to be women, and less likely to report white race. In adjusted models, dual-system users were significantly more likely to receive a new opioid prescription during the observation period [Odds ratio (OR) = 1.85, 95% confidence interval (CI) 1.76-1.93], continue prescriptions (OR = 1.24, CI 1.22-1.27), and to receive an OUD diagnosis (OR = 1.20, CI 1.14-1.27).

Discussion

The prevalence of opioid prescriptions has been declining in the US healthcare systems including VA, yet the prevalence of OUD has not been declining at the same rate. One potential problem is that detailed notes from non-VA visits are not immediately available to VA clinicians, and information about VA care is not readily available to non-VA sources. One implication of our findings is that better health system coordination is needed. Even though care was paid for by the VA and presumably closely monitored, dual-system users were more likely to have new and continued opioid prescriptions.

Hospital Readmissions Among Veterans Within 90 Days of Discharge Following Initial Hospitalization for COVID-19

INTRODUCTION

Some patients experience ongoing sequelae after discharge, including rehospitalization; therefore, outcomes following COVID-19 hospitalization are of continued interest. We examined readmissions within 90 days of hospital discharge for veterans hospitalized with COVID-19 during the first 10 months of the pandemic in the US.

METHODS

Veterans hospitalized with COVID-19 at a Veterans Health Administration (VA) hospital from March 1, 2020, through December 31, 2020 were followed for 90 days after discharge to determine readmission rates.

RESULTS

Of 20,414 veterans hospitalized with COVID-19 during this time period, 13% (n = 2,643) died in the hospital. Among survivors (n = 17,771), 16% (n = 2,764) were readmitted within 90 days of discharge, with a mean time to readmission of 21.6 days (SD = 21.1). Characteristics of the initial COVID-19 hospitalization associated with readmission included length of stay, mechanical ventilator use, higher comorbidity index score, current smoking, urban residence, discharged against medical advice, and hospitalized from September through December 2020 versus March through August 2020 (all P values <.02). Veterans readmitted from September through December 2020 were more often White, lived in a rural or highly rural area, and had shorter initial hospitalizations than veterans hospitalized earlier in the year.

CONCLUSION

Approximately 1 of 6 veterans discharged alive following a COVID-19 hospitalization from March 1 through December 31, 2020, were readmitted within 90 days. The longer the hospital stay, the greater the likelihood of readmission. Readmissions also were more likely when the initial admission required mechanical ventilation, or when the veteran had multiple comorbidities, smoked, or lived in an urban area. COVID-19 hospitalizations were shorter from September through December 2020, suggesting that hospital over-capacity may have resulted in earlier discharges and increased readmissions. Efforts to monitor and provide support for patients discharged in high bed-capacity situations may help avoid readmissions.

Expansion of the Veterans Health Administration Network and Surgical Outcomes

Importance

The US Department of Veterans Affairs (VA) Veterans Choice Program (VCP) expanded health care access to community settings outside the VA for eligible patients. Little is known about the effect of VCP on access to surgery and postoperative outcomes. Since its initiation, care coordination issues, which are often associated with adverse postoperative outcomes, have been reported. Research findings on the association of VCP and postoperative outcomes are limited to only a few select procedures and have been mixed, potentially due to bias from unmeasured confounding.

Objective

To investigate the association of the VCP with access to surgery and postoperative outcomes using a nonrandomized controlled regression discontinuity design (RDD) to reduce the impact of unmeasured confounders.

Design, Setting, and Participants

This was a nonrandomized RDD study of the Veterans Health Administration (VHA). Participants included veterans enrolled in the VHA who required surgery between October 1, 2014, and June 1, 2019.

Interventions

The VCP, which expanded access to VA-paid community care for eligible veterans living 40 miles or more from their closest VA hospital.

Main Outcomes and Measures

Postoperative emergency department visits, inpatient readmissions, and mortality at 30 and 90 days.

Results

A total of 615 473 unique surgical procedures among 498 427 patients (mean [SD] age, 63.0 [12.9] years; 450 366 male [90.4%]) were identified. Overall, 94 783 procedures (15.4%) were paid by the VHA, and the proportion of VHA-paid procedures varied by procedure type. Patients who underwent VA-paid procedures were more likely to be women (9209 [12.7%] vs men, 38 771 [9.1%]), White race (VA paid, 54 544 [74.4%] vs VA provided, 310 077 [73.0%]), and younger than 65 years (VA paid, 36 054 [49.1%] vs 229 411 [46.0%] VA provided), with a significantly lower comorbidity burden (mean [SD], 1.8 [2.2] vs 2.6 [2.7]). The nonrandomized RDD revealed that VCP was associated with a slight increase of 0.03 in the proportion of VA-paid surgical procedures among eligible veterans (95% CI, 0.01-0.05; P = .01). However, there was no difference in postoperative mortality, readmissions, or emergency department visits.

Conclusions and Relevance

Expanded access to health care in the VHA was associated with a shift in the performance of surgical procedures in the private sector but had no measurable association with surgical outcomes. These findings may assuage concerns of worsened patient outcomes resulting from care coordination issues when care is expanded outside of a single health care system, although it remains unclear whether these additional procedures were appropriate or improved patient outcomes.

How Did Veterans' Reliance on Veterans Health Administration Outpatient Care Change After Expansion of the Veterans Community Care Program?

BACKGROUND

The Veterans Community Care Program (VCCP) aims to address access constraints in the Veterans Health Administration (VA) by reimbursing care from non-VA community providers. Little existing research explores how veterans' choice of VA versus VCCP providers has evolved as a significant VCCP expansion in 2014 as part of the Veterans Access, Choice, and Accountability Act.

OBJECTIVES

We examined changes in reliance on VA for primary care (PC), mental health (MH), and specialty care (SC) among VCCP-eligible veterans.

RESEARCH DESIGN

We linked VA administrative data with VCCP claims to retrospectively examine utilization during calendar years 2016-2018.

SUBJECTS

1.78 million veterans enrolled in VA before 2013 and VCCP-eligible in 2016 due to limited VA capacity or travel hardship.

MEASURES

We measured reliance as the proportion of total annual outpatient (VA+VCCP) visits occurring in VA for PC, MH, and SC.

RESULTS

Of the 26.1 million total outpatient visits identified, 45.6% were for MH, 29.9% for PC, and 24.4% for SC. Over the 3 years, 83.2% of veterans used any VA services, 23.8% used any VCCP services, and 20.0% were dual VA-VCCP users. Modest but statistically significant declines in reliance were observed from 2016-2018 for PC (94.5%-92.2%), and MH (97.8%-96.9%), and a more significant decline was observed for SC (88.5%-79.8%).

CONCLUSIONS

Veterans who have the option of selecting between VA or VCCP providers continued using VA for most of their outpatient care in the initial years after the 2014 VCCP expansion.

Demographic Differences Among US Department of Veterans Affairs Patients Referred for Genetic Consultation to a Centralized VA Telehealth Program, VA Medical Centers, or the Community

IMPORTANCE

Telehealth enables access to genetics clinicians, but impact on care coordination is unknown.

OBJECTIVE

To assess care coordination and equity of genetic care delivered by centralized telehealth and traditional genetic care models.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included patients referred for genetic consultation from 2010 to 2017 with 2 years of follow-up in the US Department of Veterans Affairs (VA) health care system. Patients were excluded if they were referred for research, cytogenetic, or infectious disease testing, or if their care model could not be determined.

EXPOSURES

Genetic care models, which included VA-telehealth (ie, a centralized team of genetic counselors serving VA facilities nationwide), VA-traditional (ie, a regional service by clinical geneticists and genetic counselors), and non-VA care (ie, community care purchased by the VA).

MAIN OUTCOMES AND MEASURES

Multivariate regression models were used to assess associations between patient and consultation characteristics and the type of genetic care model referral; consultation completion; and having 0, 1, or 2 or more cancer surveillance (eg, colonoscopy) and risk-reducing procedures (eg, bilateral mastectomy) within 2 years following referral.

RESULTS

In this study, 24 778 patients with genetics referrals were identified, including 12 671 women (51.1%), 13 193 patients aged 50 years or older (53.2%), 15 639 White patients (63.1%), and 15 438 patients with cancer-related referrals (62.3%). The VA-telehealth model received 14 580 of the 24 778 consultations (58.8%). Asian patients, American Indian or Alaskan Native patients, and Hawaiian or Pacific Islander patients were less likely to be referred to VA-telehealth than White patients (OR, 0.54; 95% CI, 0.35-0.84) compared with the VA-traditional model. Completing consultations was less likely with non-VA care than the VA-traditional model (OR, 0.45; 95% CI, 0.35-0.57); there were no differences in completing consultations between the VA models. Black patients were less likely to complete consultations than White patients (OR, 0.84; 95% CI, 0.76-0.93), but only if referred to the VA-telehealth model. Patients were more likely to have multiple cancer preventive procedures if they completed their consultations (OR, 1.55; 95% CI, 1.40-1.72) but only if their consultations were completed with the VA-traditional model.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, the VA-telehealth model was associated with improved access to genetics clinicians but also with exacerbated health care disparities and hindered care coordination. Addressing structural barriers and the needs and preferences of vulnerable subpopulations may complement the centralized telehealth approach, improve care coordination, and help mitigate health care disparities.

Regional Economic Conditions and Preventable Hospitalization Among Older Patients With Diabetes

OBJECTIVE

The aim was to explore the relationship between changes in regional economic conditions and quality of care-preventable hospitalization or death among older patients with diabetes at Veterans Health Administration (VHA), safety-net system for veterans.

SUBJECTS

VHA patients aged 65 years and older with a diabetes diagnosis between July 2012 and June 2014, who had at least 1 primary care visit in the past year.

MEASURES

County-level and state-level public data were used to characterize regional health insurance coverage and affluence surrounding the VHA facilities. Each patient was associated with a VHA facility and its corresponding regional market variables, and followed up to 48 months or until they experienced diabetes-related Prevention Quality Indicators or death.

RESULTS

Discrete-time Cox proportional hazards models estimated that changes in regional market variables characterizing regional health insurance coverage and affluence were significant factors associated with preventable hospitalization or death. All regional market variables were combined into a demand index, where 1 SD decrease in the demand index was associated with a 2.0-point increase in predicted survival for an average patient at an average VHA facility. For comparison, a 1 SD increase in primary care capacity was associated with 4.7-point increase.

CONCLUSIONS

Downturns in regional economic conditions could increase demand for VHA care and raise the risk of diabetes-related preventable hospitalization or death among older VHA patients diagnosed with diabetes. Safety-net hospitals may be unfairly penalized for lower quality of care when experiencing higher demand for care because of an economic downturn.