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.

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.

Do Community-level Disadvantages Account for Racial Disparities in the Safety of Spine Surgery? A Large Database Study Based on Medicare Claims.

BACKGROUND: Racial health disparities across orthopaedic surgery subspecialties, including spine surgery, are well established. However, the underlying causes of these disparities, particularly relating to social determinants of health, are not fully understood. QUESTIONS/PURPOSES: (1) Is there a racial difference in 90-day mortality, readmission, and complication rates ("safety outcomes") among Medicare beneficiaries after spine surgery? (2) To what degree does the Centers for Disease Control and Prevention Social Vulnerability Index (SVI), a community-level marker of social determinants of health, account for racial disparities in safety outcomes? METHODS: To examine racial differences in 90-day mortality, readmission, and complications after spine surgery, we retrospectively identified all 419,533 Medicare beneficiaries aged 65 or older who underwent inpatient spine surgery from 2015 to 2019; we excluded 181,588 patients with endstage renal disease or Social Security disability insurance entitlements, who were on Medicare HMO, or who had missing SVI data. Because of the nearly universal coverage of those age 65 or older, Medicare data offer a large cohort that is broadly generalizable, provides improved precision for relatively rare safety outcomes, and is free of confounding from differential insurance access across races. The Master Beneficiary Summary File includes enrollees' self-reported race based on a restrictive list of mutually exclusive options. Even though this does not fully capture the entirety of racial diversity, it is self-reported by patients. Identification of spine surgery was based on five Diagnosis Related Groups labeled "cervical fusion," "fusion, except cervical," "anterior-posterior combined fusion," "complex fusion," and "back or neck, except fusion." Although heterogeneous, these cohorts do not reflect inherently different biology that would lead us to expect differences in safety outcomes by race. We report specific types of complications that did and did not involve readmission. Although complications vary in severity, we report them as composite measures while being cognizant of the inherent limitations of making inferences based on aggregate measures. The SVI was chosen as the mediating variable because it aggregates important social determinants of health and has been shown to be a marker of high risk of poor public health response to external stressors. Patients were categorized into three groups based on a ranking of the four SVI themes: socioeconomic status, household composition, minority status and language, and housing and transportation. We report the "average race effects" among Black patients compared with White patients using nearest-neighbor Mahalanobis matching by age, gender, comorbidities, and spine surgery type. Mahalanobis matching provided the best balance among propensity-type matching methods. Before matching, Black patients in Medicare undergoing spine surgery were disproportionately younger with more comorbidities and were less likely to undergo cervical fusion. To estimate the contribution of the SVI on racial disparities in safety outcomes, we report the average race effect between models with and without the addition of the four SVI themes. RESULTS: After matching on age, gender, comorbidities, and spine surgery type, Black patients were on average more likely than White patients to be readmitted (difference of 1.5% [95% CI 0.9% to 2.1%]; p < 0.001) and have complications with (difference of 1.2% [95% CI 0.5% to 1.9%]; p = 0.002) or without readmission (difference of 3.6% [95% CI 2.9% to 4.3%]; p < 0.001). Adding the SVI to the model attenuated these differences, explaining 17% to 49% of the racial differences in safety, depending on the outcome. An observed higher rate of 90-day mortality among Black patients was explained entirely by matching using non-SVI patient demographics (difference of 0.00% [95% CI -0.3% to 0.3%]; p = 0.99). However, even after adjusting for the SVI, Black patients had more readmissions and complications. CONCLUSION: Social disadvantage explains up to nearly 50% of the disparities in safety outcomes between Black and White Medicare patients after spine surgery. This argument highlights an important contribution of socioeconomic circumstances and societal barriers to achieving equal outcomes. But even after accounting for the SVI, there remained persistently unequal safety outcomes among Black patients compared with White patients, suggesting that other unmeasured factors contribute to the disparities. This is consistent with evidence documenting Black patients' disadvantages within a system of seemingly equal access and resources. Research on racial health disparities in orthopaedics should account for the SVI to avoid suggesting that race causes any observed differences in complications among patients when other factors related to social deprivation are more likely to be determinative. Focused social policies aiming to rectify structural disadvantages faced by disadvantaged communities may lead to a meaningful reduction in racial health disparities. LEVEL OF EVIDENCE: Level III, therapeutic study.

Comparing Postoperative Readmission Rates Between Veterans Receiving Total Knee Arthroplasty in the Veterans Health Administration Versus Community Care.

BACKGROUND: There are growing concerns that Veterans' increased use of Veterans Health Administration (VA)-purchased care in the community may lead to lower quality of care. OBJECTIVE: We compared rates of hospital readmissions following elective total knee arthroplasties (TKAs) that were either performed in VA or purchased by VA through community care (CC) at both the national and facility levels. METHODS: Three-year cohort study using VA and CC administrative data from the VA's Corporate Data Warehouse (October 1, 2016-September 30, 2019). We obtained Medicare data to capture readmissions that were paid by Medicare. We used the Centers for Medicare and Medicaid Services (CMS) methods to identify unplanned, 30-day, all-cause readmissions. A secondary outcome, TKA-related readmissions, identified readmissions resulting from complications of the index surgery. We ran mixed-effects logistic regression models to compare the risk-adjusted odds of all-cause and TKA-related readmissions between TKAs performed in VA versus CC, adjusting for patients' sociodemographic and clinical characteristics. PRINCIPAL FINDINGS: Nationally, the odds of experiencing an all-cause or TKA-related readmission were significantly lower for TKAs performed in VA versus CC (eg, the odds of experiencing an all-cause readmission in VA were 35% of those in CC. At the facility level, most VA facilities performed similarly to their corresponding CC providers, although there were 3 VA facilities that performed worse than their corresponding CC providers. CONCLUSIONS: Given VA's history in providing high-quality surgical care to Veterans, it is important to closely monitor and track whether the shift to CC for surgical care will impact quality in both settings over time.

Association Between Mental Health Conditions and Outpatient Care Fragmentation: a National Study of Older High-Risk Veterans.

BACKGROUND: Healthcare fragmentation may lead to adverse consequences and may be amplified among older, sicker patients with mental health (MH) conditions. OBJECTIVE: To determine whether older Veterans with MH conditions have more fragmented outpatient non-MH care, compared with older Veterans with no MH conditions. DESIGN: Retrospective cohort study using FY2014 Veterans Health Administration (VHA) administrative data linked to Medicare data. PARTICIPANTS: 125,481 VHA patients ≥ 65 years old who were continuously enrolled in Medicare Fee-for-Service Parts A and B and were at high risk for hospitalization. MAIN OUTCOME AND MEASURES: The main outcome was non-MH care fragmentation as measured by (1) non-MH provider count and (2) Usual Provider of Care (UPC), the proportion of care with the most frequently seen non-MH provider. We tested the association between no vs. any MH conditions and outcomes using Poisson regression and fractional regression with logit link, respectively. We also compared Veterans with no MH condition with each MH condition and combinations of MH conditions, adjusting for sociodemographics, comorbidities, and drive-time to VHA specialty care. KEY RESULTS: In total, 47.3% had at least one MH condition. Compared to those without MH conditions, Veterans with MH conditions had less fragmented care, with fewer non-MH providers (IRR = 0.96; 95% CI: 0.96-0.96) and more concentrated care with their usual provider (OR = 1.08 for a higher UPC; 95% CI: 1.07, 1.09) in adjusted models. Secondary analyses showed that those with individual MH conditions (e.g., depression) had fewer non-MH providers (IRR range: 0.86-0.98) and more concentrated care (OR range: 1.04-1.20). A similar pattern was observed when examining combinations of MH conditions (IRR range: 0.80-0.90; OR range: 1.16-1.30). CONCLUSIONS: Contrary to expectations, having a MH condition was associated with less fragmented non-MH care among older, high-risk Veterans. Further research will determine if this is due to different needs, underuse, or appropriate use of healthcare.

Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice.

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.

Criminal legal involvement among recently separated veterans: Findings from the LIMBIC study.

OBJECTIVE: This study investigated individual-level and neighborhood-level predictors of criminal legal involvement of veterans during the critical transition period from military to civilian life. HYPOTHESES: We hypothesized that substance use, mental health, and personality disorders will increase the incidence of criminal legal involvement, which will be highest among veterans living in socioeconomically disadvantaged neighborhoods after military discharge. METHOD: We analyzed data from a longitudinal cohort study of 418,624 veterans who entered Department of Veterans Affairs (VA) health care after leaving the military. Department of Defense (DoD) data on clinical diagnoses, demographics, and military history were linked to VA data on neighborhood of residence and criminal legal involvement. RESULTS: Criminal legal involvement in the 2 years following military discharge was most strongly predicted by younger age, substance use disorder, and being male. Other predictors included the military branch in which veterans served, deployment history, traumatic brain injury, serious mental illness, personality disorder, having fewer physical health conditions, and living in socioeconomically disadvantaged neighborhoods. These factors combined in multivariable analysis yielded a very large effect size for predicting criminal legal involvement after military separation (area under the curve = .82). The incidence of criminal legal involvement was 10 times higher among veterans with co-occurring substance use disorder, serious mental illness, and personality disorder than among veterans with none of these diagnoses, and these rates were highest among veterans residing in more socioeconomically disadvantaged neighborhoods. CONCLUSIONS: To our knowledge, this is the largest longitudinal study of risk factors for criminal legal involvement in veterans following military discharge. The findings supported the hypothesis that veterans with co-occurring mental disorders living in socioeconomically disadvantaged neighborhoods were at higher risk of criminal legal involvement, underscoring the complex interplay of individual-level and neighborhood-level risk factors for criminal legal involvement after veterans leave the military. These results can inform policy and programs, such as the DoD Transition Assistance Program (TAP) and the VA Military to Civilian Readiness Pathway program (M2C Ready), to enhance community reintegration and prevent criminal legal involvement among veterans transitioning from military to civilian life. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Comparing Driving Miles for Department of Veterans Affairs-delivered Versus Department of Veterans Affairs-purchased Cataract Surgery.

BACKGROUND: The Veterans Choice Act of 2014 increased the number of Veterans eligible for Department of Veterans Affairs (VA)-purchased care delivered in non-VA community care (CC) facilities. Driving >40 miles from home to a VA facility is a key eligibility criterion for CC. It remains unclear whether this policy change improved geographical access by reducing drive distance for Veterans. OBJECTIVES: Describe the driving distance for Veterans receiving cataract surgery in VA and CC facilities, and if they visited the closest-to-home facility or if they drove to farther facilities. SUBJECTS: Veterans who had cataract surgery in federal fiscal year 2015. MEASURES: We calculated driving miles to the Closest VA and CC facilities that performed cataract surgeries, and to the location where Veterans received care. RESULTS: A total of 61,746 Veterans received 83,875 cataract surgeries. More than 50% of CC surgeries occurred farther than the Closest CC facility providing cataract surgery (median Closest CC facility 8.7 miles vs. Actual CC facility, 19.7 miles). Most (57%) Veterans receiving cataract surgery at a VA facility used the Closest VA facility (median Closest VA facility 28.1 miles vs. Actual VA facility at 31.2 miles). In all, 26.1% of CC procedures occurred in facilities farther away than the Closest VA facility. CONCLUSIONS: Although many Veterans drove farther than needed to get cataract surgery in CC, this was not true for obtaining care in the VA. Our findings suggest that there may be additional reasons, besides driving distance, that affect whether Veterans choose CC and, if they do, where they seek CC.

County-level Predictors of Growth in Community-based Primary Care Use Among Veterans.

BACKGROUND: The 2014 Choice Act expanded the Veterans Health Administration's (VA) capacity to purchase services for VA enrollees from community providers, yet little is known regarding the growth of Veterans' primary care use in community settings. OBJECTIVES: The aim was to measure county-level growth in VA community-based primary care (CBPC) penetration following the Choice Act and to assess whether CBPC penetration increased in rural counties with limited access to VA facilities. DATA AND SAMPLE: A total of 3132 counties from VA administrative data from 2015 to 2018, Area Health Resources Files, and County Health Rankings. ANALYSIS: We defined the county-level CBPC penetration rate as the proportion of VA-purchased primary care out of all VA-purchased primary care (ie, within and outside VA). We estimated county-level multivariate linear regression models to assess whether rurality and supply of primary care providers and health care facilities were significantly associated with CBPC growth. RESULTS: Nationally, CBPC penetration rates increased from 2.7% in 2015 to 7.3% in 2018. The rurality of the county was associated with a 2-3 percentage point (pp) increase in CBPC penetration growth (P<0.001). The presence of a VA facility was associated with a 1.7 pp decrease in CBPC penetration growth (P<0.001), while lower primary care provider supply was associated with a 0.6 pp increase in CBPC growth (P<0.001). CONCLUSION: CBPC as a proportion of all VA-purchased primary care was small but increased nearly 3-fold between 2015 and 2018. Greater increases in CBPC penetration were concentrated in rural counties and counties without a VA facility, suggesting that community care may enhance primary care access in rural areas with less VA presence.

Identifying patients who access musculoskeletal physical therapy: a retrospective cohort analysis.

BACKGROUND: Musculoskeletal conditions are common and cause high levels of disability and costs. Physical therapy is recommended for many musculoskeletal conditions. Past research suggests that referral rates appear to have increased over time, but the rate of accessing a physical therapist appears unchanged. OBJECTIVE: Our retrospective cohort study describes the rate of physical therapy use after referral for a variety of musculoskeletal diagnoses while comparing users and non-users of physical therapy services after referral. METHODS: The study sample included patients in the University of Utah Health system who received care from a medical provider for a musculoskeletal condition. We included a comprehensive set of variables available in the electronic data warehouse possibly associated with attending physical therapy. Our primary analysis compared differences in patient factors between physical therapy users and non-users using Poisson regression. RESULTS: 15 877 (16%) patients had a referral to physical therapy, and 3812 (24%) of these patients accessed physical therapy after referral. Most of the factors included in the model were associated with physical therapy use except for sex and number of comorbidities. The receiver operating characteristic curve was 0.63 suggesting poor predictability of the model but it is likely related to the heterogeneity of the sample. CONCLUSIONS: We found that obesity, ethnicity, public insurance and urgent care referrals were associated with poor adherence to physical therapy referral. However, the limited predictive power of our model suggests a need for a deeper examination into factors that influence patients access to a physical therapist.

Effect of Patient Use of Physical Therapy After Referral for Musculoskeletal Conditions on Future Medical Utilization: A Retrospective Cohort Analysis.

OBJECTIVE: The purpose of this study was to evaluate whether physical therapy use influenced subsequent use of musculoskeletal-related surgeries, injections, magnetic resonance imaging (MRI), and other imaging. METHODS: We conducted a retrospective cohort study of patients aged 18 to 64 years who had an ambulatory care visit at the University of Utah system, after implementation of the 10th revision of the International Statistical Classification of Diseases and Related Health Problems with adequate data collection in the system at the time of the data pull, between October 1, 2015, and September 30, 2018. We identified patients (n = 85 186) who received care for a musculoskeletal condition (lower back pain, cervical, knee, shoulder, hip, elbow, ankle, wrist/hand, thoracic, and arthritis diagnoses). Regression analyses were used to evaluate the association between physical therapy use and medical care use while controlling for relevant factors. RESULTS: In patients referred to physical therapy (n = 15 870), physical therapy use (n = 3812) was associated with increased MRI use (incidence rate ratio, 1.24; 95% confidence interval, 1.15-1.33; P < .001) and surgery use (incidence rate ratio, 1.11; 95% confidence interval, 1.00-1.23; P < .001). Several other factors were also associated with increased health care use, including being referred by an orthopedic provider, obesity, non-lower back pain diagnoses, and having 1 or more comorbidities. CONCLUSION: Outpatient physical therapy use for musculoskeletal conditions in adult patients younger than 65 years at the University of Utah system, a mountain west United States academic health care system, was associated with increased rates of MRI and surgery. This finding is contrary to prior research suggesting that physical therapy improves outcomes in some diagnosis groups. A referral from an orthopedic provider, non-lower back pain diagnoses, and obesity were also associated with increased medical care utilization.

Provider Practice Competition and Adoption of Medicare's Oncology Care Model.

BACKGROUND: There is a concern that the Oncology Care Model (OCM), a voluntary bundled payment program, may incentivize mergers and acquisitions among physician practices leading to reduced competition and price increases. These concerns are heightened if OCM is preferentially adopted in competitive health care markets because it could result in reduced competition, but little is known about the characteristics of markets where OCM is adopted. OBJECTIVE: To measure the association between regional market competition among medical oncologists with the initial adoption of OCM. RESEARCH DESIGN: The Herfindahl-Hirschman Index (HHI), a measure of competition, was calculated for hospital referral regions (HRRs) using secondary data from the Centers for Medicare and Medicaid Services. The relationship between HHI and OCM adoption was assessed using a 2-part regression model adjusting for the market-level number of practices, physician density, average practice size, sociodemographic characteristics, and medical resources. A count model on all HRRs was also estimated to assess an overall effect. SUBJECTS: A total of 10,788 physicians in 3,537 practices who billed Medicare for oncology services in 2015. RESULTS: OCM was adopted in 114 (37%) of the 306 HRRs. We found that practices in competitive health care markets were more likely to adopt OCM than in noncompetitive markets. Two-part regression analysis indicated a nonlinear relationship between HHI and OCM adoption. Average practice size, number of practices in an HRR, and the hospital bed rate were positively associated with adoption, whereas the rate of full-time equivalent hospital employees to 1000 residents was negatively associated with adoption. CONCLUSIONS: OCM adoption was higher in HRRs with greater competition. Careful monitoring of market-level changes among OCM adopters should be undertaken to ensure that the benefits of the OCM outweigh the negative consequences of possible changes in competition.

A Sequential Multiple-Assignment Randomized Trial (SMART) for Stepped Care Management of Low Back Pain in the Military Health System: A Trial Protocol.

BACKGROUND: The Defense Health Agency has prioritized system-level pain management initiatives within the Military Health System (MHS), with low back pain as one of the key focus areas. A stepped care model focused on nonpharmacologic treatment to promote self-management is recommended. Implementation of stepped care is complicated by lack of information on the most effective nonpharmacologic strategies and how to sequence and tailor the various available options. The Sequential Multiple-Assignment Randomization Trial for Low Back Pain (SMART LBP) is a multisite pragmatic trial using a SMART design to assess the effectiveness of nonpharmacologic treatments for chronic low back pain. DESIGN: This SMART trial has two treatment phases. Participants from three military treatment facilities are randomized to 6 weeks of phase I treatment, receiving either physical therapy (PT) or Army Medicine's holistic Move2Health (M2H) program in a package specific to low back pain. Nonresponders to treatment in phase I are again randomized to phase II treatment of combined M2H + PT or mindfulness-based treatment using the Mindfulness-Oriented Recovery Enhancement (MORE) program. The primary outcome is the Patient-Reported Outcomes Measurement Information System pain interference computer-adapted test score. SUMMARY: This trial is part of an initiative funded by the National Institutes of Health, Veterans Affairs, and the Department of Defense to establish a national infrastructure for effective system-level management of chronic pain with a focus on nonpharmacologic treatments. The results of this study will provide important information on nonpharmacologic care for chronic LBP in the MHS embedded within a stepped care framework.

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.

Recommendations for the Evaluation of Cross-System Care Coordination from the VA State-of-the-art Working Group on VA/Non-VA Care.

In response to widespread concerns regarding Veterans' access to VA care, Congress enacted the Veterans Access, Choice and Accountability Act of 2014, which required VA to establish the Veterans Choice Program (VCP). Since the inception of VCP, more than two million Veterans have received care from community providers, representing approximately 25% of Veterans enrolled in VA care. However, expanded access to non-VA care has created challenges in care coordination between VA and community health systems. In March 2018, the VA Health Services Research & Development Service hosted a VA State of the Art conference (SOTA) focused on care coordination. The SOTA convened VA researchers, program directors, clinicians, and policy makers to identify knowledge gaps regarding care coordination within the VA and between VA and community systems of care. This article provides a summary and synthesis of relevant literature and provides recommendations generated from the SOTA about how to evaluate cross-system care coordination. Care coordination is typically evaluated using health outcomes including hospital readmissions and death; however, in cross-system evaluations of care coordination, measures such as access, cost, Veteran/patient and provider satisfaction (including with cross-system communication), comparable quality metrics, context (urban vs. rural), and patient complexity (medical and mental health conditions) need to be included to fully evaluate care coordination effectiveness. Future research should examine the role of multiple individuals coordinating VA and non-VA care, and how these coordinators work together to optimize coordination.

Veteran Satisfaction with Early Experiences of Health Care Through the Veterans Choice Program: a Concurrent Mixed Methods Study.

BACKGROUND: The 2014 Veterans Access, Choice and Accountability Act (i.e., "Choice") allows eligible Veterans to receive covered health care outside the Veterans Affairs (VA) Healthcare System. The initial implementation of Choice was challenging, and use was limited in the first year. OBJECTIVE: To assess satisfaction with Choice, and identify reasons for satisfaction and dissatisfaction during its early implementation. DESIGN AND PARTICIPANTS: Semi-structured telephone interviews from July to September 2015 with Choice-eligible Veterans from 25 VA facilities across the USA. MAIN MEASURES: Satisfaction was assessed with 5-point Likert scales and open-ended questions. We compared ratings of satisfaction with Choice and VA health care, and identified reasons for satisfaction/dissatisfaction with Choice in a thematic analysis of open-ended qualitative data. RESULTS: Of 195 participants, 35 had not attempted to use Choice; 43 attempted but had not received Choice care (i.e., attempted only); and 117 attempted and received Choice care. Among those who attempted only, a smaller percentage were somewhat/very satisfied with Choice than with VA health care (17.9% and 71.8%, p < 0.001); among participants who received Choice, similar percentages were somewhat/very satisfied with Choice and VA health care (66.6% and 71.1%, p = 0.45). When asked what contributed to Choice ratings, participants who attempted but did not receive Choice care reported poor access (50%), scheduling problems (20%), and care coordination issues (10%); participants who received Choice care reported improved access (27%), good quality of care (19%), and good distance to Choice provider (16%). Regardless of receipt of Choice care, most participants expressed interest in using Choice in the future (70-82%). CONCLUSIONS: Access and scheduling barriers contributed to dissatisfaction for Veterans unsuccessfully attempting to use Choice during its initial implementation, whereas improved access and good care contributed to satisfaction for those receiving Choice care. With Veterans' continued interest in using services outside VA facilities, subsequent policy changes should address Veterans' barriers to care.

Treatment of Low Back Pain With Opioids and Nonpharmacologic Treatment Modalities for Army Veterans.

BACKGROUND: In the Veterans Health Administration (VHA) there is growing interest in the use of nonpharmacologic treatment (NPT) for low back pain (LBP) as pain intensity and interference do not decrease with opioid use. OBJECTIVES: To describe overall and facility-level variation in the extent to which specific NPT modalities are used in VHA for LBP, either alone or as adjuncts to opioid medications, and to understand associations between veterans' clinical and demographic characteristics and type of treatment. RESEARCH DESIGN: This retrospective cohort study examined use of opioids and 21 specific NPT modalities used by veterans. SUBJECTS: VHA-enrolled Iraq and Afghanistan veterans who utilized care in ("linked" to) 130 VHA facilities within 12 months after their separation from the Army between fiscal years 2008-2011, and who were diagnosed with LBP within 12 months after linkage (n=49,885). MEASURES: Measures included per patient: days' supply of opioids, number of visits for NPT modalities, and pain scores within one year after a LBP diagnosis. RESULTS: Thirty-four percent of veterans filled a prescription for opioids, 35% utilized at least 1 NPT modality, and 15% used both within the same year. Most patients with LBP receiving NPT, on average, had moderate pain (36%), followed by low pain (27%), severe pain (15%), and no pain (11%). Eleven percent had no pain scores recorded. CONCLUSIONS: About 65% of VHA patients with a LBP diagnosis did not receive NPT, and about 43% of NPT users also were prescribed an opioid. Understanding utilization patterns and their relationship with patient characteristics can guide pain management decisions and future study.

Medicaid Spending Differences for Child/Youth Community-Based Care in California's Decentralized Public Mental Health System.

This study evaluated spending differences across counties during the decade after California decentralized its public mental health system. Medicaid data for 0-25 year olds using mental health services were collapsed to the county-year level (n = 627). Multivariate models with county fixed effects were used to predict per capita spending for community-based mental health care. While counties increased their spending over time, those with relatively low initial expenditures per user continued to spend less than counties with historically higher spending levels. Spending differences per user were most noticeable in counties with larger racial/ethnic minority populations that also had historically lower spending levels.

Iraq and Afghanistan Veterans' Use of Veterans Health Administration and Purchased Care Before and After Veterans Choice Program Implementation.

BACKGROUND: The Veterans Choice Program (VCP), enacted by Congress after concerns surfaced about access, enables veterans to receive care outside Veterans Health Administration (VHA) facilities. Veterans who face long wait times, large driving distances, or particular hardships are eligible for VCP. Prior purchased care programs were comparatively limited in scope. OBJECTIVES: We sought to describe utilization of VHA-provided and purchased outpatient care by veterans eligible for VCP before and after VCP implementation. We focused on veterans recently eligible for VHA as they are of particular policy relevance and might have less established care patterns. RESEARCH DESIGN: We identified all Iraq and Afghanistan veterans who were eligible for VCP in 2015. We tabulated their use of VHA and purchased outpatient care for 3 years before (FY2012-2014) and 1 year after VCP implementation (FY2015). SUBJECTS: Our study population consisted of 214,449 Iraq and Afghanistan veterans who were eligible for VCP due to wait-time, distance, or hardship issues. RESULTS: In the first year of the program, 3821 (2%) of these Iraq and Afghanistan veterans used non-VHA services through VCP. Per capita VHA utilization tended to decline slightly after VCP implementation, but these changes varied by type of outpatient care. CONCLUSIONS: There was low uptake of VCP services in the first year of the program. Data from additional years are needed to better understand the impact of this policy.

Patient-aligned Care Team Engagement to Connect Veterans Experiencing Homelessness With Appropriate Health Care.

BACKGROUND: Veterans experiencing homelessness frequently use emergency and urgent care (ED). OBJECTIVE: To examine the effect of a Patient-aligned Care Team (PACT) model tailored to the unique needs of Veterans experiencing homelessness (H-PACT) on frequency and type of ED visits in Veterans Health Administration (VHA) medical facilities. RESEARCH DESIGN: During a 12-month period, ED visits for 3981 homeless Veterans enrolled in (1) H-PACT at 20 VHA medical centers (enrolled) were compared with those of (2) 24,363 homeless Veterans not enrolled in H-PACT at the same sites (nonenrolled), and (3) 23,542 homeless Veterans at 12 non-H-PACT sites (usual care) using a difference-in-differences approach. MEASURE(S): The primary outcome was ED and other health care utilization and the secondary outcome was emergent (not preventable/avoidable) ED visits. RESULTS: H-PACT enrollees were predominantly white males with a higher baseline Charlson comorbidity index. In comparing H-PACT enrollees with usual care, there was a significant decrease in ED usage among the highest ED utilizers (difference-in-differences, -4.43; P<0.001). The decrease in ED visits were significant though less intense for H-PACT enrollees versus nonenrolled (-0.29, P<0.001). H-PACT enrollees demonstrated a significant increase in the proportion of ED care visits that were not preventable/avoidable in the 6 months after enrollment, but had stable rates of primary care, mental health, social work, and substance abuse visits over the 12 months. CONCLUSIONS: Primary care treatment engagement can reduce ED visits and increase appropriate use of ED services in VHA for Veterans experiencing homelessness, especially in the highest ED utilizers.