Growth of Community Outpatient Care in the Veterans Affairs System After the MISSION Act.

BACKGROUND: The Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 authorized a major expansion of purchased care in the community for Veterans experiencing access barriers in the Veterans Affairs (VA) health care system. OBJECTIVE: To estimate changes in primary care, mental health, and emergency/urgent care visits in the VA and community fiscal years (FY) 2018-2021 and differences between rural and urban clinics. DESIGN: A national, longitudinal study of VA clinics and outpatient utilization. Clinic-level analysis was conducted to estimate changes in number and proportion of clinic visits provided in the community associated with the MISSION Act adjusting for clinic characteristics and underlying time trends. PARTICIPANTS: In total, 1050 VA clinics and 6.6 million Veterans assigned to primary care. MAIN MEASURES: Number of primary care, mental health, and emergency/urgent care visits provided in the VA and community and the proportion provided in the community. KEY RESULTS: Nationally, community primary care visits increased by 107% (50,611 to 104,923), community mental health visits increased by 167% (100,701 to 268,976), and community emergency/urgent care visits increased by 129% (142,262 to 325,407) from the first quarter of 2018 to last quarter of 2021. In adjusted analysis, after MISSION Act implementation, there was an increase in community visits as a proportion of total clinic visits for emergency/urgent care and mental health but not primary care. Rural clinics had larger increases in the proportion of community visits for primary care and emergency/urgent care than urban clinics. CONCLUSIONS: After the MISSION Act, more outpatient care shifted to the community for emergency/urgent care and mental health care but not primary care. Community care utilization increased more in rural compared to urban clinics for primary care and emergency/urgent care. These findings highlight the challenges and importance of maintaining provider networks in rural areas to ensure access to 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.

Reexamining Differences Between Black and White Veterans in Hospital Mortality and Other Outcomes in Veterans Affairs and Other Hospitals.

OBJECTIVES: To examine Black-White patient differences in mortality and other hospital outcomes among Veterans treated in Veterans Affairs (VA) and non-VA hospitals. BACKGROUND: Lower hospital mortality has been documented in older Black patients relative to White patients, yet the mechanisms have not been determined. Comparing other hospital outcomes and multiple hospital systems may help inform the reasons for these differences. METHODS: Repeated cross-sectional analysis of hospitalization records was conducted for Veterans discharged in VA and non-VA hospitals from January 1, 2013 to December 31, 2017 in 11 states. Hospital outcomes included 30-day mortality, 30-day readmissions, inpatient costs, and length of stay. Hospitalizations were for acute myocardial infarction, coronary artery bypass graft surgery, gastrointestinal bleeding, heart failure, pneumonia, and stroke. Differences in outcomes were estimated between Black and White patients for VA and non-VA hospitals and age groups younger than 65 years or 65 years and older in regression models adjusting for patient and hospital factors. RESULTS: There were a total of 459,574 study patients. Older Black patients had lower adjusted mortality for acute myocardial infarction, gastrointestinal bleeding, heart failure, and pneumonia. Adjusted probability of readmission was higher and adjusted mean length of stay and costs were greater for older Black patients relative to White patients in non-VA hospitals for several conditions. Fewer differences were observed in younger patients and in VA hospitals. CONCLUSION: While older Black patients had lower mortality, other outcomes compared poorly with White patients. Differences were not fully explained by observable patient and hospital factors although social determinants may contribute to these differences.

The Clinical Resource Hub Telehealth Program and Use of Primary Care, Emergency, and Inpatient Care During the COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic disrupted delivery of health care services worldwide. We examined the impact of the pandemic on clinics participating in the Veterans Affairs (VA) Clinical Resource Hub (CRH) program, rolled out nationally in October 2019, to improve access to care at under-resourced VA clinics or "spoke" sites through telehealth services delivered by regional "hub" sites. OBJECTIVE: To assess whether the CRH program was associated with increased access to primary care, we compared use of primary, emergency, and inpatient care at sites that adopted CRH for primary care (CRH-PC) with sites that did not adopt CRH-PC, pre-post pandemic onset. DESIGN: Difference-in-difference and event study analyses, adjusting for site characteristics. STUDY COHORT: A total of 1050 sites (254 CRH-PC sites; 796 comparison sites), fiscal years (FY) 2019-2021. INTERVENTION: CRH Program for Primary Care. MAIN MEASURES: Quarterly number of VA visits per site for primary care (across all and by modality, in-person, video, and phone), emergency care, and inpatient care. RESULTS: In adjusted analyses, CRH-PC sites, compared with non-CRH-PC sites, had on average 221 additional primary care visits (a volume increase of 3.4% compared to pre-pandemic). By modality, CRH-PC sites had 643 fewer in-person visits post-pandemic (- 14.4%) but 723 and 128 more phone and video visits (+ 39.9% and + 159.5%), respectively. CRH-PC sites, compared with non-CRH-PC sites, had fewer VA ED visits (- 4.2%) and hospital stays (- 5.1%) in VA medical centers. Examining visits per patient, we found that CRH-PC sites had 48 additional telephone primary care visits per 1000 primary care patients (an increase of 9.8%), compared to non-program sites. CONCLUSIONS: VA's pre-pandemic rollout of a new primary care telehealth program intended to improve access facilitated primary care visits during the pandemic, a period fraught with care disruptions, and limited in-person health care delivery, indicating the potential for the program to offer health system resilience.

Hospital and Patient Factors Affecting Veterans' Hospital Choice.

Veterans enrolled in the Veterans Affairs (VA) health care system gained greater access to non-VA care beginning in 2014. We examined hospital and Veteran characteristics associated with hospital choice. We conducted a longitudinal study of elective hospitalizations 2011 to 2017 in 11 states and modeled patients' choice of VA hospital, large non-VA hospital, or small non-VA hospital in conditional logit models. Patients had higher odds of choosing a hospital with an academic affiliation, better patient experience rating, location closer to them, and a more common hospital type. Patients who were male, racial/ethnic minorities, had higher VA enrollment priority, and had a mental health comorbidity were more likely than other patients to choose a VA hospital than a non-VA hospital. Our findings suggest that patients respond to certain hospital attributes. VA hospitals may need to maintain or achieve high levels of quality and patient experience to attract or retain patients in the future.

Outcomes of Veterans Treated in Veterans Affairs Hospitals vs Non-Veterans Affairs Hospitals.

Importance: Many veterans enrolled in the Veterans Affairs (VA) health care system have access to non-VA care through insurance and VA-purchased community care. Prior comparisons of VA and non-VA hospital outcomes have been limited to subpopulations. Objective: To compare outcomes for 6 acute conditions in VA and non-VA hospitals for younger and older veterans using VA and all-payer discharge data. Design, Setting, and Participants: This cohort study used a repeated cross-sectional analysis of hospitalization records for acute myocardial infarction (AMI), coronary artery bypass graft (CABG), gastrointestinal (GI) hemorrhage, heart failure (HF), pneumonia, and stroke. Participants included VA enrollees from 11 states at VA and non-VA hospitals from 2012 to 2017. Analysis was conducted from July 1, 2022, to October 18, 2023. Exposures: Treatment in VA or non-VA hospital. Main Outcome and Measures: Thirty-day mortality, 30-day readmission, length of stay (LOS), and costs. Average treatment outcomes of VA hospitals were estimated using inverse probability weighted regression adjustment to account for selection into hospitals. Models were stratified by veterans' age (aged less than 65 years and aged 65 years and older). Results: There was a total of 593 578 hospitalizations and 414 861 patients with mean (SD) age 75 (12) years, 405 602 males (98%), 442 297 hospitalizations of non-Hispanic White individuals (75%) and 73 155 hospitalizations of non-Hispanic Black individuals (12%) overall. VA hospitalizations had a lower probability of 30-day mortality for HF (age ≥65 years, -0.02 [95% CI, -0.03 to -0.01]) and stroke (age <65 years, -0.03 [95% CI, -0.05 to -0.02]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.03]). VA hospitalizations had a lower probability of 30-day readmission for CABG (age <65 years, -0.04 [95% CI, -0.06 to -0.01]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.02]), GI hemorrhage (age <65 years, -0.04 [95% CI, -0.06 to -0.03]), HF (age <65 years, -0.05 [95% CI, -0.07 to -0.03]), pneumonia (age <65 years, -0.04 [95% CI, -0.06 to -0.03]; age ≥65 years, -0.03 [95% CI, -0.04 to -0.02]), and stroke (age <65 years, -0.11 [95% CI, -0.13 to -0.09]; age ≥65 years, -0.13 [95% CI, -0.16 to -0.10]) but higher probability of readmission for AMI (age <65 years, 0.04 [95% CI, 0.01 to 0.06]). VA hospitalizations had a longer mean LOS and higher costs for all conditions, except AMI and stroke in younger patients. Conclusions and Relevance: In this cohort study of veterans, VA hospitalizations had lower mortality for HF and stroke and lower readmissions, longer LOS, and higher costs for most conditions compared with non-VA hospitalizations with differences by condition and age group. There were tradeoffs between better outcomes and higher resource use in VA hospitals for some conditions.

Differences in use of Veterans Health Administration and non-Veterans Health Administration hospitals by rural and urban Veterans after access expansions.

PURPOSE: To examine changes in rural and urban Veterans' utilization of acute inpatient care in Veterans Health Administration (VHA) and non-VHA hospitals following access expansion from the Veterans Choice Act, which expanded eligibility for VHA-paid community hospitalization. METHODS: Using repeated cross-sectional data of VHA enrollees' hospitalizations in 9 states (AZ, CA, CT, FL, LA, MA, NY, PA, and SC) between 2012 and 2017, we compared rural and urban Veterans' probability of admission in VHA and non-VHA hospitals by payer over time for elective and nonelective hospitalizations using multinomial logistic regression to adjust for patient-level sociodemographic features. We also used generalized linear models to compare rural and urban Veterans' travel distances to hospitals. FINDINGS: Over time, the probability of VHA-paid community hospitalization increased more for rural Veterans than urban Veterans. For elective inpatient care, rural Veterans' probability of VHA-paid admission increased from 2.9% (95% CI 2.6%-3.2%) in 2012 to 6.5% (95% CI 5.8%-7.1%) in 2017. These changes were associated with a temporal trend that preceded and continued after the implementation of the Veterans Choice Act. Overall travel distances to hospitalizations were similar over time; however, the mean distance traveled decreased from 39.2 miles (95% CI 35.1-43.3) in 2012 to 32.3 miles (95% CI 30.2-34.4) in 2017 for rural Veterans receiving elective inpatient care in VHA-paid hospitals. CONCLUSIONS: Despite limited access to rural hospitals, these data demonstrate an increase in rural Veterans' use of non-VHA hospitals for acute inpatient care and a small reduction in distance traveled to elective inpatient services.

Learning from national implementation of the Veterans Affairs Clinical Resource Hub (CRH) program for improving access to care: protocol for a six year evaluation.

BACKGROUND: The Veterans Affairs (VA) Clinical Resource Hub (CRH) program aims to improve patient access to care by implementing time-limited, regionally based primary or mental health staffing support to cover local staffing vacancies. VA's Office of Primary Care (OPC) designed CRH to support more than 1000 geographically disparate VA outpatient sites, many of which are in rural areas, by providing virtual contingency clinical staffing for sites experiencing primary care and mental health staffing deficits. The subsequently funded CRH evaluation, carried out by the VA Primary Care Analytics Team (PCAT), partnered with CRH program leaders and evaluation stakeholders to develop a protocol for a six-year CRH evaluation. The objectives for developing the CRH evaluation protocol were to prospectively: 1) identify the outcomes CRH aimed to achieve, and the key program elements designed to achieve them; 2) specify evaluation designs and data collection approaches for assessing CRH progress and success; and 3) guide the activities of five geographically dispersed evaluation teams. METHODS: The protocol documents a multi-method CRH program evaluation design with qualitative and quantitative elements. The evaluation's overall goal is to assess CRH's return on investment to the VA and Veterans at six years through synthesis of findings on program effectiveness. The evaluation includes both observational and quasi-experimental elements reflecting impacts at the national, regional, outpatient site, and patient levels. The protocol is based on program evaluation theory, implementation science frameworks, literature on contingency staffing, and iterative review and revision by both research and clinical operations partners. DISCUSSION: Health systems increasingly seek to use data to guide management and decision-making for newly implemented clinical programs and policies. Approaches for planning evaluations to accomplish this goal, however, are not well-established. By publishing the protocol, we aim to increase the validity and usefulness of subsequent evaluation findings. We also aim to provide an example of a program evaluation protocol developed within a learning health systems partnership.

The Clinical Resource Hub Initiative: First-Year Implementation of the Veterans Health Administration Regional Telehealth Contingency Staffing Program.

Health care systems face challenges providing accessible health care across geographically disparate sites. The Veterans Health Administration (VHA) developed regional telemedicine service focusing initially on primary care and mental health services. The objective of this study is to describe the program and progress during the early implementation. In its first year, the Clinical Resource Hub program provided 244 515 encounters to 95 684 Veterans at 475 sites. All 18 regions met or exceeded minimum implementation requirements. The regionally based telehealth contingency staffing hub met early implementation goals. Further evaluation to review sustainability and impact on provider experience and patient outcomes is needed.

Adherence to Diabetes Medications and Health Care Use During the COVID-19 Pandemic Among High-Risk Patients.

INTRODUCTION: The COVID-19 pandemic caused potentially disruptive shocks to chronic condition care. We examined how diabetes medication adherence, related hospitalizations, and primary care use changed in high-risk veterans prepandemic and postpandemic. METHODS: We conducted longitudinal analyses on a cohort of high-risk diabetes patients in the Veterans Affairs (VA) health care system. Primary care visits by modality, medication adherence, and VA acute hospitalizations and emergency department (ED) visits were measured. We also estimated differences for subgroups of patients by race/ethnicity, age, and rural/urban location. RESULTS: Patients were 95% male with mean age 68 years. Prepandemic patients received a mean per quarter of 1.5 in-person primary care visits and 1.3 virtual visits, 0.10 hospitalizations, and 0.22 ED visits, with mean adherence of 0.82. The early pandemic was associated with fewer in-person primary care visits, more virtual visits, fewer hospitalizations and ED visits per patient, and no change in adherence; there were no midpandemic versus prepandemic differences in hospitalizations or adherence. Black and nonelderly patients had lower adherence during the pandemic. CONCLUSION: Adherence to diabetes medications and primary care use remained high for most patients even though virtual care replaced in-person care. Black and nonelderly patients may require additional intervention to address lower adherence.

Integrating data analytics, peer support, and whole health coaching to improve the health outcomes of homeless veterans: Study protocol for an effectiveness-implementation trial.

BACKGROUND: Homelessness is a strong determinant of acute care service utilization (inpatient hospitalization, emergency department visits) among US adults. Data analytics, peer support, and patient-centered approaches can collectively offer high-quality care for homeless patients who frequently utilize acute care ("super utilizers"). However, few outpatient programs have integrated these components and tested their effectiveness for this patient population. OBJECTIVE: To test the effectiveness and implementation potential of a novel intervention that integrates data analytics with peers trained in whole health coaching ("Peer Whole Health") to reduce use of acute care among homeless adults. METHODS: Using a randomized controlled trial design at two US Veterans Health Administration Medical Centers, we plan to enroll 220 veterans in primary care on VHA's Homeless Registry who are flagged on a super-utilizer clinical dashboard. Participants will complete a baseline interview, be randomized to Enhanced Usual Care (EUC; primary care and data analytics) or EUC plus 18 sessions of Peer Whole Health over 6 months, and be re-interviewed at 3, 6, and 9 months. Qualitative interviews with primary care staff and patients will identify facilitators and barriers to more widespread implementation of the intervention. DISCUSSION: The primary hypothesis is that those who receive the intervention will have fewer total days of all-cause hospitalization. If confirmed, the findings can provide healthcare systems that serve homeless super-utilizers with a high-value approach to care that can be integrated into primary care services and reduce overall costs for these patients. CLINICAL TRIAL REGISTRATION: The study is registered with ClinicalTrials.gov (NCT05176977).

Rural and urban differences in the implementation of Virtual Integrated Patient-Aligned Care Teams.

PURPOSE: Workforce shortages contribute to geographic disparities in accessing primary care services. An innovative, clinic-to-clinic videoconferencing telehealth program in the Veterans Health Administration (VHA) called the Virtual Integrated Patient-Aligned Care Teams (V-IMPACT) was designed to increase veterans' access to primary care and relieve workforce shortages in VA primary care clinics, including in many rural areas. This paper describes trends in clinic sites and veteran uptake of the V-IMPACT program, a model that delivered remote, team-based primary care services, from fiscal years (FY)2013-2018. METHODS: This observational study used VHA administrative data to compare program uptake, measured by the program penetration rate (percent of patients using V-IMPACT services in each site) across sites; and characteristics for V-IMPACT users versus nonusers for 2,155,203 veteran-years in 69 sites across 7 regional networks for FY2013-2018. Regression models assessed the association between V-IMPACT use and veteran characteristics within sites. FINDINGS: Across sites, V-IMPACT had higher penetration in rural sites (8%) and primary care community-based outpatient clinics (7%, P<.001). After adjusting for veteran characteristics, rural veterans (aOR = 1.05; P = .02) and veterans with higher comorbidity risk scores (aOR = 1.08; P<.001) were independently associated with V-IMPACT use. Highly rural veterans (OR = 0.60; P<.001) and veterans who lived ≥40 miles from the closest VHA primary care site (OR = 0.86; P<.001) were less likely to be a V-IMPACT user. CONCLUSIONS: A clinic-to-clinic telehealth program, such as V-IMPACT, was able to reach many rural sites, rural veterans, and veterans in primary care health professional shortage areas. V-IMPACT has the potential to increase access to team-based primary care.

Virtual Management of Chronic Conditions During the COVID-19 Pandemic: Insights From Primary Care Providers and Clinical Pharmacists.

INTRODUCTION: The abrupt change in care delivery caused by the coronavirus disease 2019 pandemic may have left some patients, particularly those with chronic conditions, unable to receive timely and appropriate routine care. Understanding the effect of the pandemic and the switch to virtual care for patients with chronic conditions requires in-depth qualitative feedback from providers who care for these patients. MATERIALS AND METHODS: We interviewed 13 primary care providers and clinical pharmacists from the Veterans Health Administration. Interviews elicited experiences managing patients with chronic conditions, specifically diabetes and hypertension, during the coronavirus disease 2019 pandemic. We employed a rapid analytic approach for data analysis. RESULTS: In general, interview participants maintained that most patients' chronic conditions could be managed remotely without significant disruption. However, patients who lack familiarity with technology and/or reliable broadband access, patients not compliant with recommended self-assessments, and older patients with hearing loss or cognitive disorders may be more difficult to manage virtually. Although providers reported minimal disruptions to care because of the pandemic, they did note that the closure of labs and experiences of social isolation may have negatively impacted patients. Providers suggested optimizing virtual management through more robust patient instruction on virtual care technology, increased use of Veterans Affairs home health services, and removing institutional barriers that may de-incentivize virtual care modalities. CONCLUSIONS: For many patients with chronic conditions, virtual care is a promising approach to provide ongoing management in primary care. However, more tailored strategies may be needed to care for sicker, more vulnerable patients.

Health Care Access Expansions and Use of Veterans Affairs and Other Hospitals by Veterans.

This cohort study examines changes in the use of Veterans Affairs (VA) and non-VA hospitals by VA enrollees and mortality associated with these policies.

Partnered implementation of the veteran sponsorship initiative: protocol for a randomized hybrid type 2 effectiveness-implementation trial.

BACKGROUND: The USA is undergoing a suicide epidemic for its youngest Veterans (18-to-34-years-old) as their suicide rate has almost doubled since 2001. Veterans are at the highest risk during their first-year post-discharge, thus creating a "deadly gap." In response, the nation has developed strategies that emphasize a preventive, universal, and public health approach and embrace the value of community interventions. The three-step theory of suicide suggests that community interventions that reduce reintegration difficulties and promote connectedness for Veterans as they transition to civilian life have the greatest likelihood of reducing suicide. Recent research shows that the effectiveness of community interventions can be enhanced when augmented by volunteer and certified sponsors (1-on-1) who actively engage with Veterans, as part of the Veteran Sponsorship Initiative (VSI). METHOD/DESIGN: The purpose of this randomized hybrid type 2 effectiveness-implementation trial is to evaluate the implementation of the VSI in six cities in Texas in collaboration with the US Departments of Defense, Labor and Veterans Affairs, Texas government, and local stakeholders. Texas is an optimal location for this large-scale implementation as it has the second largest population of these young Veterans and is home to the largest US military installation, Fort Hood. The first aim is to determine the effectiveness of the VSI, as evidenced by measures of reintegration difficulties, health/psychological distress, VA healthcare utilization, connectedness, and suicidal risk. The second aim is to determine the feasibility and potential utility of a stakeholder-engaged plan for implementing the VSI in Texas with the intent of future expansion in more states. The evaluators will use a stepped wedge design with a sequential roll-out to participating cities over time. Participants (n=630) will be enrolled on military installations six months prior to discharge. Implementation efforts will draw upon a bundled implementation strategy that includes strategies such as ongoing training, implementation facilitation, and audit and feedback. Formative and summative evaluations will be guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework and will include interviews with participants and periodic reflections with key stakeholders to longitudinally identify barriers and facilitators to implementation. DISCUSSION: This evaluation will have important implications for the national implementation of community interventions that address the epidemic of Veteran suicide. Aligned with the Evidence Act, it is the first large-scale implementation of an evidence-based practice that conducts a thorough assessment of TSMVs during the "deadly gap." TRIAL REGISTRATION: ClinicalTrials.gov ID number: NCT05224440 . Registered on 04 February 2022.

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

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

Outpatient care fragmentation in Veterans Affairs patients at high-risk for hospitalization.

OBJECTIVE: To examine outpatient care fragmentation and its association with future hospitalization among patients at high risk for hospitalization. DATA SOURCES: Veterans Affairs (VA) and Medicare data. STUDY DESIGN: We conducted a longitudinal study, using logistic regression to examine how outpatient care fragmentation in FY14 (as measured by number of unique providers, Breslau's Usual Provider of Care (UPC), Bice-Boxerman's Continuity of Care Index (COCI), and Modified Modified Continuity Index (MMCI)) was associated with all-cause hospitalizations and hospitalizations related to ambulatory care sensitive conditions (ACSC) in FY15. We also examined how fragmentation varied by patient's age, gender, race, ethnicity, marital status, rural status, history of homelessness, number of chronic conditions, Medicare utilization, and mental health care utilization. DATA EXTRACTION METHODS: We extracted data for 130,704 VA patients ≥65 years old with a hospitalization risk ≥90th percentile and ≥ four outpatient visits in the baseline year. PRINCIPAL FINDINGS: The mean (SD) of FY14 outpatient visits was 13.2 (8.6). Fragmented care (more providers, less care with a usual provider, more dispersed care based on COCI) was more common among patients with more chronic conditions and those receiving mental health care. In adjusted models, most fragmentation measures were not associated with all-cause hospitalization, and patients with low levels of fragmentation (more concentrated care based on UPC, COCI, and MMCI) had a higher likelihood of an ACSC-related hospitalization (AOR, 95% CI = 1.21 (1.09-1.35), 1.27 (1.14-1.42), and 1.28 (1.18-1.40), respectively). CONCLUSIONS: Contrary to expectations, outpatient care fragmentation was not associated with elevated all-cause hospitalization rates among VA patients in the top 10th percentile for risk of admission; in fact, fragmented care was linked to lower rates of hospitalization for ACSCs. In integrated settings such as the VA, multiple providers, and dispersed care might offer access to timely or specialized care that offsets risks of fragmentation, particularly for conditions that are sensitive to ambulatory care.

A Primary Care Telehealth Pilot Program to Improve Access: Associations with Patients' Health Care Utilization and Costs.

Background: The Veterans Health Administration (VHA) piloted an innovative video telehealth program called Virtual Integrated Multisite Patient Aligned Care Teams (V-IMPACT) in fiscal year (FY) 2014. V-IMPACT set up one regional "hub" site where primary care (PC) teams provided regular PC through telehealth services to patients in outlying "spoke" sites that experienced gaps in provider coverage. We evaluated associations between clinic-level adoption of V-IMPACT and patients' utilization and VHA's costs for primary, emergency, and inpatient care. Materials and Methods: This observational study used repeated cross-sections of 208,612 unique veteran patients assigned to a PC team in 22 V-IMPACT spoke sites from FY2013 to FY2018. V-IMPACT adoption in a spoke site was indicated if more than 1% of patients assigned to PC in a site used V-IMPACT services during the year. Association between V-IMPACT adoption and outcomes were assessed using mixed-effects models. Results: V-IMPACT adoption was associated with increased telehealth visits for PC (incidence rate ratio [IRR] = 2.42 [1.29 to 4.55]) and for primary care mental health integration (IRR = 7.25 [2.69 to 19.54]). V-IMPACT adoption was not associated with in-person visits, or with total visits (in-person plus video telehealth). V-IMPACT adoption was also not associated with acute hospital stays, emergency department visits, or VHA costs. Conclusions: Programs such as VHA's V-IMPACT can increase telehealth visits for PC, allowing successful transition across modalities and facilitating continuity of care without impacting total care. Programs should track substitution of in-person visits with telehealth visits and examine its effects on patients' health outcomes, satisfaction, and travel costs.

Outcomes of a randomized quality improvement trial for high-risk Veterans in year two.

OBJECTIVE: The Veterans Health Administration (VHA) conducted a randomized quality improvement evaluation to determine whether augmenting patient-centered medical homes with Primary care Intensive Management (PIM) decreased utilization of acute care and health care costs among patients at high risk for hospitalization. PIM was cost-neutral in the first year; we analyzed changes in utilization and costs in the second year. DATA SOURCES: VHA administrative data for five demonstration sites from August 2013 to March 2019. DATA SOURCES: Administrative data extracted from VHA's Corporate Data Warehouse. STUDY DESIGN: Veterans with a risk of 90-day hospitalization in the top 10th percentile and recent hospitalization or emergency department (ED) visit were randomly assigned to usual primary care vs primary care augmented by PIM. PIM included interdisciplinary teams, comprehensive patient assessment, intensive case management, and care coordination services. We compared the change in mean VHA inpatient and outpatient utilization and costs (including PIM expenses) per patient for the 12-month period before randomization and 13-24 months after randomization for PIM vs usual care using difference-in-differences. PRINCIPAL FINDINGS: Both PIM patients (n = 1902) and usual care patients (n = 1882) had a mean of 5.6 chronic conditions. PIM patients had a greater number of primary care visits compared to those in usual care (mean 4.6 visits/patient/year vs 3.7 visits/patient/year, p < 0.05), but ED visits (p = 0.45) and hospitalizations (p = 0.95) were not significantly different. We found a small relative increase in outpatient costs among PIM patients compared to those in usual care (mean difference + $928/patient/year, p = 0.053), but no significant differences in mean inpatient costs (+$245/patient/year, p = 0.97). Total mean health care costs were similar between the two groups during the second year (mean difference + $1479/patient/year, p = 0.73). CONCLUSIONS: Approaches that target patients solely based on the high risk of hospitalization are unlikely to reduce acute care use or total costs in VHA, which already offers patient-centered medical homes.