Health Services Research最新文献

{"title":"Implementation, intervention, and downstream costs for implementation of a multidisciplinary complex pain clinic in the Veterans Health Administration.","authors":"Sarah I Daniels, Shayna Cave, Todd H Wagner, Taryn A Perez, Sara N Edmond, William C Becker, Amanda M Midboe","doi":"10.1111/1475-6773.14345","DOIUrl":"10.1111/1475-6773.14345","url":null,"abstract":"<p><strong>Objective: </strong>To determine the budget impact of implementing multidisciplinary complex pain clinics (MCPCs) for Veterans Health Administration (VA) patients living with complex chronic pain and substance use disorder comorbidities who are on risky opioid regimens.</p><p><strong>Data sources and study setting: </strong>We measured implementation costs for three MCPCs over 2 years using micro-costing methods. Intervention and downstream costs were obtained from the VA Managerial Cost Accounting System from 2 years prior to 2 years after opening of MCPCs.</p><p><strong>Study design: </strong>Staff at the three VA sites implementing MCPCs were supported by Implementation Facilitation. The intervention cohort was patients at MCPC sites who received treatment based on their history of chronic pain and risky opioid use. Intervention costs and downstream costs were estimated with a quasi-experimental study design using a propensity score-weighted difference-in-difference approach. The healthcare utilization costs of treated patients were compared with a control group having clinically similar characteristics and undergoing the standard route of care at neighboring VA medical centers. Cancer and hospice patients were excluded.</p><p><strong>Data collection/extraction methods: </strong>Activity-based costing data acquired from MCPC sites were used to estimate implementation costs. Intervention and downstream costs were extracted from VA administrative data.</p><p><strong>Principal findings: </strong>Average Implementation Facilitation costs ranged from $380 to $640 per month for each site. Upon opening of three MCPCs, average intervention costs per patient were significantly higher than the control group at two intervention sites. Downstream costs were significantly higher at only one of three intervention sites. Site-level differences were due to variation in inpatient costs, with some confounding likely due to the COVID-19 pandemic. This evidence suggests that necessary start-up investments are required to initiate MCPCs, with allocations of funds needed for implementation, intervention, and downstream costs.</p><p><strong>Conclusions: </strong>Incorporating implementation, intervention, and downstream costs in this evaluation provides a thorough budget impact analysis, which decision-makers may use when considering whether to expand effective programming.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of mental health staffing inputs on initiation of care among recently separated Veterans.","authors":"Paul R Shafer, Yingzhe Yuan, Yevgeniy Feyman, Megan E Price, Aigerim Kabdiyeva, Stuart M Figueroa, Yi-Jung Shen, Jonathan R Nebeker, Merry C Ward, Kiersten L Strombotne, Steven D Pizer","doi":"10.1111/1475-6773.14333","DOIUrl":"10.1111/1475-6773.14333","url":null,"abstract":"<p><strong>Objective: </strong>To estimate a causal relationship between mental health staffing and time to initiation of mental health care for new patients.</p><p><strong>Data sources and study setting: </strong>As the largest integrated health care delivery system in the United States, the Veterans Health Administration (VHA) provides a unique setting for isolating the effects of staffing on initiation of mental health care where demand is high and out-of-pocket costs are not a relevant confounder. We use data from the Department of Defense and VHA to obtain patient and facility characteristics and health care use.</p><p><strong>Study design: </strong>To isolate exogenous variation in mental health staffing, we used an instrumental variables approach-two-stage residual inclusion with a discrete time hazard model. Our outcome is time to initiation of mental health care after separation from active duty (first appointment) and our exposure is mental health staffing (standardized clinic time per 1000 VHA enrollees per pay period).</p><p><strong>Data collection/extraction methods: </strong>Our cohort consists of all Veterans separating from active duty between July 2014 and September 2017, who were enrolled in the VHA, and had at least one diagnosis of post-traumatic stress disorder, major depressive disorder, and/or substance use disorder in the year prior to separation from active duty (N = 54,209).</p><p><strong>Principal findings: </strong>An increase of 1 standard deviation in mental health staffing results in a higher likelihood of initiating mental health care (adjusted hazard ratio: 3.17, 95% confidence interval: 2.62, 3.84, p < 0.001). Models stratified by tertile of mental health staffing exhibit decreasing returns to scale.</p><p><strong>Conclusions: </strong>Increases in mental health staffing led to faster initiation of care and are especially beneficial in facilities where staffing is lower, although initiation of care appears capacity-limited everywhere.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141201556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving access to buprenorphine for rural veterans in a learning health care system.","authors":"Jessica J Wyse, Katherine Mackey, Kim A Kauzlarich, Benjamin J Morasco, Kathleen F Carlson, Adam J Gordon, P Todd Korthuis, Alison Eckhardt, Summer Newell, Sarah S Ono, Travis I Lovejoy","doi":"10.1111/1475-6773.14346","DOIUrl":"10.1111/1475-6773.14346","url":null,"abstract":"<p><strong>Objective: </strong>To describe a learning health care system research process designed to increase buprenorphine prescribing for the treatment of opioid use disorder (OUD) in rural primary care settings within U.S. Department of Veterans Affairs (VA) treatment facilities.</p><p><strong>Data sources and study setting: </strong>Using national administrative data from the VA Corporate Data Warehouse, we identified six rural VA health care systems that had improved their rate of buprenorphine prescribing within primary care from 2015 to 2020 (positive deviants). We conducted qualitative interviews with leaders, clinicians, and staff involved in buprenorphine prescribing within primary care from these sites to inform the design of an implementation strategy.</p><p><strong>Study design: </strong>Qualitative interviews to inform implementation strategy development.</p><p><strong>Data collection/extraction methods: </strong>Interviews were audio-recorded, transcribed verbatim, and coded by a primary coder and secondary reviewer. Analysis utilized a mixed inductive/deductive approach. To develop an implementation strategy, we matched clinical needs identified within interviews with resources and strategies participants had utilized to address these needs in their own sites.</p><p><strong>Principal findings: </strong>Interview participants (n = 30) identified key clinical needs and strategies for implementing buprenorphine in rural, primary care settings. Common suggestions included the need for clinical mentorship or a consult service, buprenorphine training, and educational resources. Building upon interview findings and in partnership with a clinical team, we developed an implementation strategy composed of an engaging case-based training, an audit and feedback process, and educational resources (e.g., Buprenorphine Frequently Asked Questions, Rural Care Model Infographic).</p><p><strong>Conclusions: </strong>We describe a learning health care system research process that leveraged national administrative data, health care provider interviews, and clinical partnership to develop an implementation strategy to encourage buprenorphine prescribing in rural primary care settings.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540581/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking implementation science and policy: Process and tools for congressionally mandated implementation, evaluation, and reporting.","authors":"Monica M Matthieu, David A Adkins, LaCinda Jones, Ciara M Oliver, Jack H Suarez, Barbara Johnson, Mona J Ritchie","doi":"10.1111/1475-6773.14357","DOIUrl":"10.1111/1475-6773.14357","url":null,"abstract":"<p><strong>Objective: </strong>To describe a process model for assisting partners in addressing requirements of legislation and review policy analysis, planning, and evaluation design processes and tools. Throughout its 25-year history, the United States Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) program has been a forerunner in partnering with organizational leaders to improve health care. The Foundations of Evidence-based Policymaking Act of 2018 provided new opportunities for QUERI and other implementation scientists to support federal agency leaders in implementing, evaluating, and reporting on congressionally mandated programs. Although implementation scientists have the skills to support partnered implementation and evaluation, these skills must be adapted for congressionally mandated projects as many scientists have limited experience in policy analysis and the intersection of data informing organizational policy, programs, and practices (i.e., evidence-based policy).</p><p><strong>Data sources and study setting: </strong>During the conduct of four congressionally mandated projects, our national VA QUERI team developed processes and tools to achieve the goals and aims of our VHA partners and to ensure our collective work and reporting met legislative requirements.</p><p><strong>Study design: </strong>Our process model, program planning, and analysis tools were informed by an iterative process of refining and adapting the tools over a period of six years, spanning the years 2017 to 2023.</p><p><strong>Principal findings: </strong>Work to support our partners was conducted across three phases: preparation and planning, conducting implementation and evaluation, and developing the congressionally mandated report. The processes and tools we developed within the context of mutually respectful and honest partnerships have been critical to our QUERI center's success in this area.</p><p><strong>Conclusions: </strong>Lessons we learned may help other scientists partnering in VA or other federal agencies to plan, conduct, and report on congressionally mandated projects.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141753352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of the Veterans Health Administration Learning Health System: 25 years of QUERI.","authors":"Melissa M Garrido, Amy M Kilbourne","doi":"10.1111/1475-6773.14372","DOIUrl":"10.1111/1475-6773.14372","url":null,"abstract":"","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142019634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of regional variation in racial and ethnic differences in patient experience among Veterans Health Administration primary care users.","authors":"Evan Michael Shannon, Kenneth T Jones, Ernest Moy, W Neil Steers, Joy Toyama, Donna L Washington","doi":"10.1111/1475-6773.14328","DOIUrl":"10.1111/1475-6773.14328","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate racial and ethnic differences in patient experience among VA primary care users at the Veterans Integrated Service Network (VISN) level.</p><p><strong>Data source and study setting: </strong>We performed a secondary analysis of the VA Survey of Healthcare Experiences of Patients-Patient Centered Medical Home for fiscal years 2016-2019.</p><p><strong>Study design: </strong>We compared 28 patient experience measures (six each in the domains of access and care coordination, 16 in the domain of person-centered care) between minoritized racial and ethnic groups (American Indian or Alaska Native [AIAN], Asian, Black, Hispanic, Multi-Race, Native Hawaiian or Other Pacific Islander [NHOPI]) and White Veterans. We used weighted logistic regression to test differences between minoritized and White Veterans, controlling for age and gender.</p><p><strong>Data collection/extraction methods: </strong>We defined meaningful difference as both statistically significant at two-tailed p < 0.05 with a relative difference ≥10% or ≤-10%. Within VISNs, we included tests of group differences with adequate power to detect meaningful relative differences from a minimum of five comparisons (domain agnostic) per VISN, and separately for a minimum of two for access and care coordination and four for person-centered care domains. We report differences as disparities/large disparities (relative difference ≥10%/≥ 25%), advantages (experience worse or better, respectively, than White patients), or equivalence.</p><p><strong>Principal findings: </strong>Our analytic sample included 1,038,212 Veterans (0.6% AIAN, 1.4% Asian, 16.9% Black, 7.4% Hispanic, 0.8% Multi-Race, 0.8% NHOPI, 67.7% White). Across VISNs, the greatest proportion of comparisons indicated disparities for three of seven eligible VISNs for AIAN, 6/10 for Asian, 3/4 for Multi-Race, and 2/6 for NHOPI Veterans. The plurality of comparisons indicated advantages or equivalence for 17/18 eligible VISNs for Black and 12/14 for Hispanic Veterans. AIAN, Asian, Multi-Race, and NHOPI groups had more comparisons indicating disparities by VISN in the access domain than person-centered care and care coordination.</p><p><strong>Conclusions: </strong>We found meaningful differences in patient experience measures across VISNs for minoritized compared to White groups, especially for groups with lower population representation.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540589/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141162978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential effects of a social work staffing intervention on social work access among rural and highly rural Veterans: A cohort study.","authors":"Andrew N Honken, Christopher W Halladay, Lisa E Wootton, Alita R Harmon, Cassandra L Hua, James L Rudolph, Portia Y Cornell","doi":"10.1111/1475-6773.14327","DOIUrl":"10.1111/1475-6773.14327","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the impact on rural Veterans' access to social work services of a Department of Veterans Affairs (VA) national program to increase social work staffing, by Veterans' rurality, race, and complex care needs.</p><p><strong>Data sources and study setting: </strong>Data obtained from VA Corporate Data Warehouse, including sites that participated in the social work program between October 1, 2016 and September 30, 2021.</p><p><strong>Study design: </strong>The study outcome was monthly number of Veterans per 1000 individuals with 1+ social work encounters. We used difference-in-differences to estimate the program effect on urban, rural, and highly rural Veterans. Among rural and highly rural Veterans, we stratified by race (American Indian or Alaskan Native, Asian, Black, Native Hawaiian or Other Pacific Islander, and White) and complex care needs (homelessness, high hospitalization risk, and dementia).</p><p><strong>Data collection: </strong>We defined a cohort of 740,669 Veterans (32,434,001 monthly observations) who received primary care at a participating site.</p><p><strong>Principal findings: </strong>Average monthly social work use was 8.7 Veterans per 1000 individuals. The program increased access by 49% (4.3 per 1000; 95% confidence interval, 2.2-6.3). Rural Veterans' social work access increased by 57% (5.0; 3.6-6.3). Among rural/highly rural Veterans, the program increased social work access for those with high hospitalization risk by 63% (24.5; 18.2-30.9), and for Veterans experiencing homelessness, 35% (13.4; 5.2-21.7). By race, the program increased access for Black Veterans by 53% (6.1; 2.1-10.2) and for Asian Veterans by 82% (5.1; 2.2-7.9).</p><p><strong>Conclusions: </strong>At rural VA primary care sites with social work staffing below recommended levels, Black and Asian Veterans and those experiencing homelessness and high hospitalization risk may have unmet needs warranting social work services.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141421912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variation in batch ordering of imaging tests in the emergency department and the impact on care delivery.","authors":"Jacob C Jameson, Soroush Saghafian, Robert S Huckman, Nicole Hodgson","doi":"10.1111/1475-6773.14406","DOIUrl":"https://doi.org/10.1111/1475-6773.14406","url":null,"abstract":"<p><strong>Objectives: </strong>To examine heterogeneity in physician batch ordering practices and measure the associations between a physician's tendency to batch order imaging tests on patient outcomes and resource utilization.</p><p><strong>Study setting and design: </strong>In this retrospective study, we used comprehensive EMR data from patients who visited the Mayo Clinic of Arizona Emergency Department (ED) between October 6, 2018 and December 31, 2019. Primary outcomes are patient length of stay (LOS) in the ED, number of diagnostic imaging tests ordered during a patient encounter, and patients' return with admission to the ED within 72 h. The association between outcomes and physician batch tendency was measured using a multivariable linear regression controlling for various covariates.</p><p><strong>Data sources and analytic sample: </strong>The Mayo Clinic of Arizona Emergency Department recorded approximately 50,836 visits, all randomly assigned to physicians during the study period. After excluding rare complaints, we were left with an analytical sample of 43,299 patient encounters.</p><p><strong>Principal findings: </strong>Findings show that having a physician with a batch tendency 1 standard deviation (SD) greater than the average physician was associated with a 4.5% increase in ED LOS (p < 0.001). It was also associated with a 14.8% (0.2 percentage points) decrease in the probability of a 72-h return with admission (p < 0.001), implying that batching may lead to more comprehensive evaluations, reducing the need for short-term revisits. A batch tendency 1SD greater than that of the average physician was also associated with an additional 8 imaging tests ordered per 100 patient encounters (p < 0.001), suggesting that batch ordering may be leading to tests that would not have been otherwise ordered had the physician waited for the results from one test before placing their next order.</p><p><strong>Conclusions: </strong>This study highlights the considerable impact of physicians' diagnostic test ordering strategies on ED efficiency and patient care. The results also highlight the need to develop guidelines to optimize ED test ordering practices.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing imputation approaches for immigration status in ED visits: Implications for using electronic medical records.","authors":"Sarah Axeen, Anna Gorman, Todd Schneberk, Annie Ro","doi":"10.1111/1475-6773.14397","DOIUrl":"https://doi.org/10.1111/1475-6773.14397","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to compare imputation approaches to identify the likely undocumented patient population in electronic health record (EHRs). EHR are a promising source of information on undocumented immigrants' medical needs and care utilization, but there is no verified way to identify immigration status in the data. Different approaches to approximating immigration status in EHR introduce unique biases, which in turn has major implications on our understanding of undocumented immigrant patients.</p><p><strong>Study setting and design: </strong>We used a dataset of all emergency department (ED) visits from 2016 to 2019 in the Los Angeles Department of Health Services (LADHS) merged across patient medical records, demographic data, and claims data. We included all ED visits from our patient groups of interest and limited to patients at or over the age of 18 years at the time of their ED visit and excluded empty encounter records (n = 1,106,086 ED encounters).</p><p><strong>Data sources and analytic sample: </strong>We created three patient groups: (1) US-born, (2) foreign-born documented, and (3) undocumented using two different imputation approaches: a logical approach versus statistical assignment. We compared predicted probabilities for two outcomes: an ED visit related to a behavioral health (BH) disorder and inpatient admission/transfer to another facility.</p><p><strong>Principal findings: </strong>Both approaches provide comparable estimates among the three patient groups for ED encounters for a BH disorder and inpatient admission/transfer to another facility. Undocumented immigrants are less likely to have a BH diagnosis in the ED and are less likely to be admitted or transferred compared to the US-born.</p><p><strong>Conclusions: </strong>Researchers should consider expanding EHR with administrative data when studying the undocumented patient population and may prefer a logical approach to estimate immigration status. Researchers who rely on payer status alone (i.e., restricted Medicaid) as a proxy for undocumented immigrants in EHR should consider how this may bias their results. As Medicaid expands for undocumented immigrants, statistical assignment may become the preferred method.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of a payer-provider joint venture on healthcare value.","authors":"Laura F Garabedian, J Frank Wharam, Joseph P Newhouse, Matthew Lakoma, Stephanie Argetsinger, Fang Zhang, Alison A Galbraith","doi":"10.1111/1475-6773.14400","DOIUrl":"https://doi.org/10.1111/1475-6773.14400","url":null,"abstract":"<p><strong>Objective: </strong>To examine how a novel payer-provider joint venture (JV) between one payer and multiple competitive delivery systems in New Hampshire (NH), which included value-based payment, care management, and non-financial supports, impacted healthcare value and payer and provider group experiences.</p><p><strong>Study setting and design: </strong>We conducted a mixed-methods study. We used a quasi-experimental longitudinal difference-in-differences design to examine the impact of the JV (which started in January 2016 and ended in December 2020) on healthcare utilization, quality, and spending, using members in Maine (ME) as a control group. We also analyzed patient uptake of the JV's care management program using routinely collected administrative data and assessed payer and provider group leaders' perspectives about the JV via semi-structured interviews.</p><p><strong>Data sources and analytic sample: </strong>We used administrative and claims data from 2013 to 2019 in a commercially insured population under 65 years in NH and ME. We also used administrative data on care management eligibility and uptake and conducted semi-structured interviews with payer and provider group leaders affiliated with the JV.</p><p><strong>Principal findings: </strong>The JV was associated with no sustained change in medical utilization, quality, and spending throughout the study period. In the first year of the JV, there was a $142 (95% confidence interval: $41, $243) increase in pharmaceutical spending per member and a 13% (4.4%, 25%) relative increase in days covered for diabetes medications. Only 15% of eligible members engaged in care management, which was a key component of the JV's multi-pronged approach. In a disconnect from the empirical findings, payer and provider group leaders believed that the JV reduced healthcare costs and improved quality.</p><p><strong>Conclusions: </strong>Our findings provide evidence for future payer-provider JVs and demonstrate the importance of having a valid control group when evaluating JVs and value-based payment arrangements.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}