Health Services Research最新文献

{"title":"Restrictiveness of Medicare Advantage provider networks across physician specialties","authors":"Yevgeniy Feyman PhD,&nbsp;Jose Figueroa MD, MPH,&nbsp;Melissa Garrido PhD,&nbsp;Gretchen Jacobson PhD,&nbsp;Michael Adelberg MA, MPP,&nbsp;Austin Frakt PhD","doi":"10.1111/1475-6773.14308","DOIUrl":"10.1111/1475-6773.14308","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective was to measure specialty provider networks in Medicare Advantage (MA) and examine associations with market factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources and Study Setting</h3>\u0000 \u0000 <p>We relied on traditional Medicare (TM) and MA prescription drug event data from 2011 to 2017 for all Medicare beneficiaries in the United States as well as data from the Area Health Resources File.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Relying on a recently developed and validated prediction model, we calculated the provider network restrictiveness of MA contracts for nine high-prescribing specialties. We characterized network restrictiveness through an observed-to-expected ratio, calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based on the prediction model. We assessed the relationship between network restrictiveness and market factors across specialties with multivariable linear regression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Prescription drug event data for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Provider networks in MA varied in restrictiveness. OB-Gynecology was the most restrictive with enrollees seeing 34.5% (95% CI: 34.3%–34.7%) as many providers as they would absent network restrictions; cardiology was the least restrictive with enrollees seeing 58.6% (95% CI: 58.4%–58.8%) as many providers as they otherwise would. Factors associated with less restrictive networks included the county-level TM average hierarchical condition category score (0.06; 95% CI: 0.04–0.07), the county-level number of doctors per 1000 population (0.04; 95% CI: 0.02–0.05), the natural log of local median household income (0.03; 95% CI: 0.007–0.05), and the parent company's market share in the county (0.16; 95% CI: 0.13–0.18). Rurality was a major predictor of more restrictive networks (−0.28; 95% CI: −0.32 to −0.24).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings suggest that rural beneficiaries may face disproportionately reduced access in these networks and that efforts to improve access should vary by specialty.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592408","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":"Suicide risk screening and evaluation among patients accessing VHA services and identified as being newly homeless","authors":"Ryan Holliday PhD,&nbsp;Trisha Hostetter MPH,&nbsp;Lisa A. Brenner PhD,&nbsp;Nazanin Bahraini PhD,&nbsp;Jack Tsai PhD","doi":"10.1111/1475-6773.14301","DOIUrl":"10.1111/1475-6773.14301","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To evaluate universal suicide risk screening and evaluation processes among newly homeless Veterans.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Setting</h3>\u0000 \u0000 <p>Not applicable.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Examination of Veterans Health Administration (VHA) using newly homeless patients' health record data in Calendar Year 2021.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection</h3>\u0000 \u0000 <p>Not applicable.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Source</h3>\u0000 \u0000 <p>Health record data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Most patients received suicide risk screening and/or evaluation in the year prior to and/or following homeless identification (<i>n</i> = 49,505; 87.4%). Smaller percentages of patients were screened and/or evaluated in close proximity to identification (<i>n</i> = 7358; 16.0%), 1–30 days prior to identification (<i>n</i> = 12,840; 39.6%), or 1–30 days following identification (<i>n</i> = 14,263; 34.3%). Common settings for screening included primary care, emergency and urgent care, and mental health services. Of positive screens (i.e., potentially elevated risk for suicide), 72.6% had a Comprehensive Suicide Risk Evaluation (CSRE) completed in a timely manner (i.e., same day or within 24 h). Age, race, and sex were largely unrelated to screening and/or evaluation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although many newly identified homeless patients were screened and/or evaluated for suicide risk, approximately 13% were not screened; and 27% of positive screens did not receive a timely CSRE. Continued efforts are warranted to facilitate suicide risk identification to ensure homeless patients have access to evidence-based interventions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592507","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":"HSR's outstanding reviewers in 2023","authors":"Austin Frakt PhD,&nbsp;Chris Tachibana PhD","doi":"10.1111/1475-6773.14306","DOIUrl":"10.1111/1475-6773.14306","url":null,"abstract":"","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-6773.14306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592264","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":"Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA)","authors":"Angela T. Chen MA,&nbsp;Richard S. Kuzma MPP,&nbsp;Ari B. Friedman MD, PhD","doi":"10.1111/1475-6773.14305","DOIUrl":"10.1111/1475-6773.14305","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources</h3>\u0000 \u0000 <p>We used secondary data on ED visits from the National Hospital Ambulatory Medical Survey (NHAMCS), from 2016 to 2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>We established baseline performance metrics with seven published algorithms consisting of International Classification of Disease, Tenth Revision codes used to identify low acuity ED visits. We then trained logistic regression, random forest, and gradient boosting (XGBoost) models to predict low acuity ED visits. Each model was trained on five different covariate sets of demographic and clinical data. Model performance was compared using a separate validation dataset. The primary performance metric was the probability that a visit identified by an algorithm as low acuity did not experience significant testing, treatment, or disposition (positive predictive value, PPV). Subgroup analyses assessed model performance across age, sex, and race/ethnicity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection</h3>\u0000 \u0000 <p>We used 2016–2019 NHAMCS data as the training set and 2020 NHAMCS data for validation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>The training and validation data consisted of 53,074 and 9542 observations, respectively. Among seven rule-based algorithms, the highest-performing had a PPV of 0.35 (95% CI [0.33, 0.36]). All model-based algorithms outperformed existing algorithms, with the least effective—random forest using only age and sex—improving PPV by 26% (up to 0.44; 95% CI [0.40, 0.48]). Logistic regression and XGBoost trained on all variables improved PPV by 83% (to 0.64; 95% CI [0.62, 0.66]). Multivariable models also demonstrated higher PPV across all three demographic subgroups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Machine learning models substantially outperform existing algorithms based on ICD codes in predicting low acuity ED visits. Variations in model performance across demographic groups highlight the need for further research to ensure their applicability and fairness across diverse populations.</p>\u0000 </section>\u0000 ","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-6773.14305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140327330","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":"The effects of the Veterans Health Administration's Referral Coordination Initiative on referral patterns and waiting times for specialty care","authors":"Daniel A. Asfaw PhD,&nbsp;Megan E. Price MS,&nbsp;Kristina M. Carvalho MSW,&nbsp;Steven D. Pizer PhD,&nbsp;Melissa M. Garrido PhD","doi":"10.1111/1475-6773.14303","DOIUrl":"10.1111/1475-6773.14303","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To investigate whether the Veterans Health Administration's (VA) 2019 Referral Coordination Initiative (RCI) was associated with changes in the proportion of VA specialty referrals completed by community-based care (CC) providers and mean appointment waiting times for VA and CC providers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources/Study Settings</h3>\u0000 \u0000 <p>Monthly facility level VA data for 3,097,366 specialty care referrals for eight high-volume specialties (cardiology, dermatology, gastroenterology, neurology, ophthalmology, orthopedics, physical therapy, and podiatry) from October 1, 2019 to May 30, 2022.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>We employed a staggered difference-in-differences approach to evaluate RCI's effects on referral patterns and wait times. Our unit of analysis was facility-month. We dichotomized facilities into high and low RCI use based on the proportion of total referrals for a specialty. We stratified our analysis by specialty and the staffing model that high RCI users adopted: centralized, decentralized, and hybrid.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Administrative data on referrals and waiting times were extracted from the VA's corporate data warehouse. Data on staffing models were provided by the VA's Office of Integrated Veteran Care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>We did not reject the null hypotheses that high RCI use do not change CC referral rates or waiting times in any of the care settings for most specialties. For example, high RCI use for physical therapy—the highest volume specialty studied—was associated with −0.054 (95% confidence interval [CI]: −0.114 to 0.006) and 2.0 days (95% CI: −4.8 to 8.8) change in CC referral rate and waiting time at CC providers, respectively, among centralized staffing model adopters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In the initial years of the RCI program, RCI does not have a measurable effect on waiting times or CC referral rates. Our findings do not support concerns that RCI might be impeding Veterans' access to CC providers. Future evaluations should examine whether RCI facilitates Veterans' ability to receive care in their preferred setting.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140327331","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":"Association of Hospitals' Experience with Bundled Payment for Care Improvement Model with the Diffusion of Acute Hospital Care at Home","authors":"So-Yeon Kang PhD, MBA, MPH","doi":"10.1111/1475-6773.14302","DOIUrl":"10.1111/1475-6773.14302","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To examine whether hospitals' experience in a prior payment model incentivizing care coordination is associated with their decision to adopt a new payment program for a care delivery innovation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Source<b>s</b></h3>\u0000 \u0000 <p>Data were sourced from Medicare fee-for-service claims in 2017, the list of participants in Bundled Payment for Care Improvement initiatives (BPCI and BPCI-Advanced), the list of hospitals approved for Acute Hospital Care at Home (AHCaH) between November 2020 and August 2022, and the American Hospital Association Survey.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Retrospective cohort study. Hospitals' adoption of AHCaH was measured as a function of hospitals' BPCI experiences. Hospitals' BPCI experiences were categorized into five mutually exclusive groups: (1) direct BPCI participation, (2) indirect participation through physician group practices (PGPs) after dropout, (3) indirect participation through PGPs only, (4) dropout only, and (5) no BPCI exposure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>All data are derived from pre-existing sources. General acute hospitals eligible for both BPCI initiatives and AHCaH are included.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Of 3248 hospitals included in the sample, 7% adopted AHCaH as of August 2022. Hospitals with direct BPCI experience had the highest adoption rate (17.7%), followed by those with indirect participation through BPCI physicians after dropout (11.8%), while those with no exposure to BPCI were least likely to participate (3.2%). Hospitals that adopted AHCaH were more likely to be located in communities where more peer hospitals participated in the program (median 10.8% vs. 0%). After controlling for covariates, the association of the adoption of AHCaH with indirect participation through physicians after dropout was as strong as with early BPCI adopter hospitals (average marginal effect: 5.9 vs. 6.2 pp, <i>p</i> &lt; 0.05), but the other categories were not.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Hospitals that participated in the bundled payment model either directly or indirectly PGPs were more likely to adopt a care delivery innovation requiring similar competence in the next period.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140327329","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":"Who do freestanding emergency departments treat? Comparing Texas hospitals to satellite and independent freestanding departments in 2021 and 2022","authors":"Daniel Marthey PhD,&nbsp;Maya Ramy MS, MPH,&nbsp;Benjamin Ukert PhD","doi":"10.1111/1475-6773.14304","DOIUrl":"10.1111/1475-6773.14304","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective was to describe characteristics of emergency department visits to Texas satellite and independent freestanding emergency departments (FrEDs) relative to hospital emergency departments (EDs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources and Study Setting</h3>\u0000 \u0000 <p>The study used all 2021–2022 hospital and FrED discharges from the publicly available Texas Emergency Department Public Use Data Files (PUDF).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>We conducted a descriptive analysis, comparing patient and visit characteristics at satellite and independent FrEDs and hospital EDs using chi-square tests. We characterized the top 20 diagnoses and procedures ranked by volume, treatment intensity, and potentially avoidable ED use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Discharge data from 2021 to 2022 were combined for the analysis, and ED data at critical access hospitals were excluded.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Our sample consisted of 21,605,421 ED visits, 76% occurring at hospitals, 12% at satellite FrEDs, and 12% at independent FrEDs. Compared with hospitals and satellite FrEDs, patients to independent FrEDs were younger, healthier, more likely covered by private insurance, and less likely to be identified as non-Hispanic Black or Hispanic. Visits at satellite and independent FrEDs were more likely to be of moderate and low intensity and potentially avoidable.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our results underscore the need to address potentially avoidable utilization of emergency services.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-6773.14304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140186375","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":"Postpartum long-acting reversible contraceptive adoption after a statewide initiative","authors":"Katie Gifford MS, PhD,&nbsp;Rebecca McColl MA,&nbsp;Mary Joan McDuffie MA,&nbsp;Michel Boudreaux MS, PhD","doi":"10.1111/1475-6773.14300","DOIUrl":"10.1111/1475-6773.14300","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To examine the effects of a comprehensive, multiyear (2015–2020) statewide contraceptive access intervention in Delaware on the contraceptive initiation of postpartum Medicaid patients. The program aimed to increase access to all contraceptives, including long-acting reversible contraceptives (LARC). The program included interventions specifically targeting postpartum patients (Medicaid payment reform and hospital-based immediate postpartum (IPP) LARC training) and interventions in outpatient settings (provider training and operational supports).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources and Study Setting</h3>\u0000 \u0000 <p>We used Medicaid claims data between 2012 and 2019, from Delaware and Maryland (a comparison state), to identify births and postpartum contraceptive methods up to 60 days postpartum among patients aged 15–44 years who were covered in a full-benefit eligibility category.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Using difference-in-differences, we assessed changes in LARC, tubal ligation, and short-acting methods (oral contraceptive, injectable, patch/ring). LARC rates were assessed at 60 days after delivery and on an immediate postpartum basis. Other methods were only assessed at 60 days. Analyses were conducted separately for an early-adopting high-capacity hospital (that delivers approximately half of all Medicaid financed births) and for all other later-adopting hospitals in the state.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Data were extracted from administrative claims.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>The program increased postpartum LARC insertions by 60 days after delivery by 11.7 percentage points (95% CI: 10.7, 12.8) in the early-adopting hospital and 6.9 percentage points (95% CI: 4.8, 5.9) in later-adopting hospitals. Increases in IPP versus outpatient LARC drove the change, but we did not find evidence that IPP crowded-out outpatient LARC services. We observed decreases in short-acting methods, suggesting substitution between methods, but the share of patients with any method increased at the early-adopting hospital (5.2 percentage points; 95% CI: 3.5, 6.9) and was not statistically significantly different at the later-adopting hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Direct reimbursement for IPP LARC, in combination with provider training, had a meaningful impact on the share of Medicaid-enrolled postpartum women with LARC c","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140141172","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":"Travel distance and outcomes after surgical aortic valve among veterans","authors":"Brendin R. Beaulieu-Jones MD, MBA, MBI,&nbsp;Noah Siegel BS,&nbsp;Loreski Collado MD,&nbsp;Hillary J. Mull PhD, MPP,&nbsp;Jacquelyn A. Quin MD, MPH","doi":"10.1111/1475-6773.14296","DOIUrl":"10.1111/1475-6773.14296","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To investigate the association between travel distance and postoperative length of stay (LOS) and discharge disposition among veterans undergoing surgical aortic valve replacement (SAVR).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources/Study Setting</h3>\u0000 \u0000 <p>We performed a retrospective cohort study of patients undergoing SAVR, with or without coronary artery bypass grafting (CABG) at VA Boston Healthcare (January 1, 2005–December 31, 2015).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>Postoperative LOS and discharge disposition were compared for SAVR patients based on travel distance to the facility: &lt;100 miles or ≥100 miles. Multivariable regression was performed to ascertain factors associated with LOS and home discharge.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Data were collected via chart review. All patients undergoing SAVR at our institution who primarily resided within the defined region were included.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Of 597 patients studied, 327 patients underwent isolated SAVR; 270 patients underwent SAVR/CABG. Overall median (IQR) distance between the patient's residence and the hospital was 49.95 miles (27.41–129.94 miles); 190 patients (32%) resided further than 100 miles away. There were no differences in the proportion of patients with diabetes, hypertension, chronic obstructive pulmonary disease (COPD), cerebrovascular disease, atrial fibrillation, or prior myocardial infarction between groups. Overall LOS (IQR) was 9 (7–13) days and did not differ between groups (<i>p</i> = 0.18). The proportion of patients discharged home was higher among patients who resided more than 100 miles from the hospital (71% vs. 58%, <i>p</i> = 0.01). On multivariable analysis, residing further than 100 miles from the hospital was independently associated with home discharge (OR = 1.64, 95% CI: 1.09–2.48). Travel distance was not associated with LOS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Based on our institutional experience, potential concerns of longer hospital stay or discharge to other inpatient facilities for geographically distanced patients undergoing SAVR do not appear supported. Continued examination of the drivers underlying the marked shift of veterans to the private sector appears warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140112258","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":"Unfulfilled and method-specific contraceptive preferences among reproductive-aged contraceptive users in Arizona, Iowa, New Jersey, and Wisconsin","authors":"Megan L. Kavanaugh DrPH, MPH,&nbsp;Rubina Hussain MPH,&nbsp;Ashley C. Little BS","doi":"10.1111/1475-6773.14297","DOIUrl":"10.1111/1475-6773.14297","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To identify characteristics associated with unfulfilled contraceptive preferences, document reasons for these unfulfilled preferences, and examine how these unfulfilled preferences vary across specific method users.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Sources and Study Setting</h3>\u0000 \u0000 <p>We draw on secondary baseline data from 4660 reproductive-aged contraceptive users in the Arizona, Iowa, New Jersey, and Wisconsin Surveys of Women (SoWs), state-representative surveys fielded between October 2018 and August 2020 across the four states.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study Design</h3>\u0000 \u0000 <p>This is an observational cross-sectional study, which examined associations between individuals' reproductive health-related experiences and contraceptive preferences, adjusting for sociodemographic characteristics. Our primary outcome of interest is having an unfulfilled contraceptive preference, and a key independent variable is experience of high-quality contraceptive care. We also examine specific contraceptive method preferences according to current method used, as well as reasons for not using a preferred method.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Data Collection/Extraction Methods</h3>\u0000 \u0000 <p>Survey respondents who indicated use of any contraceptive method within the last 3 months prior to the survey were eligible for inclusion in this analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Principal Findings</h3>\u0000 \u0000 <p>Overall, 23% reported preferring to use a method other than their current method, ranging from 17% in Iowa to 26% in New Jersey. Young age (18–24), using methods not requiring provider involvement, and not receiving quality contraceptive care were key attributes associated with unfulfilled contraceptive preferences. Those using emergency contraception and fertility awareness-based methods had some of the highest levels of unfulfilled contraceptive preferences, while pills, condoms, partner vasectomy, and IUDs were identified as the most preferred methods. Reasons for not using preferred contraceptive methods fell largely into one of two buckets: system-level or interpersonal/individual reasons.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings highlight that avenues for decreasing the gap between contraceptive methods used and those preferred to be used may lie with healthcare providers and funding streams that support the ","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-6773.14297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140061285","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}