Health Services Research最新文献

{"title":"HIV Clinic Visit Attendance Among People With HIV Aged 50+ Years: Exploring the Role of Increasing Age, Comorbidity Burden, and the COVID-19 Pandemic.","authors":"Rohini Dasan, Elisabeth Andersen, Morgan Byrne, Jessica Helm, Alan E Greenberg, Amanda D Castel, Anne K Monroe","doi":"10.1111/1475-6773.14659","DOIUrl":"10.1111/1475-6773.14659","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the impact of advancing age, comorbidity burden, and the COVID-19 pandemic on HIV clinic visit attendance.</p><p><strong>Study setting and design: </strong>We implemented a repeated cross-sectional study using an ongoing longitudinal cohort of people with HIV (PWH) receiving care in Washington, DC.</p><p><strong>Data sources and analytic sample: </strong>Our primary exposures of interest were older age categories (60-69 and 70+ compared with 50-59 years), Veterans Aging Cohort Study (VACS) Index (surrogate for comorbidity burden), calendar year (with the three time points of 2018, 2020, and 2022 representing pre-, peri- and post-COVID). Our outcome was the number of HIV clinic visits (including telehealth) in 2018, 2020, and 2022. Associations were assessed using zero-inflated negative binomial modeling.</p><p><strong>Principal findings: </strong>4041 (72.7% men, 59.3% ages 50-59; 78.8% Black) DC Cohort participants aged 50+ years were included. In 2018, mean VACS indices for participants aged 50-59, 60-69, and 70+ years were 27.5 (standard deviation [SD] 15.8), 36.9 (SD 17.8), and 50.7 (SD 15.5) respectively. Increase in VACS Index was associated with increase in HIV clinic visits (Rate ratio: 1.03, 95% CI 1.01, 1.05). A VACS Index-calendar year interaction term was significant, indicating the relationship between VACS Index and visits was attenuated in the post-COVID time period. All age groups experienced a decrease in visits from 2018 to 2022. HIV RNA suppression remained stable.</p><p><strong>Conclusions: </strong>These findings underscore the pandemic's impact on accessing healthcare among the most vulnerable, that is, the oldest participants with the most comorbidities. Developing differential care models for PWH to target services to their local context, clinical status, and preferences may point to a broader public health approach to mitigate post-pandemic changes in HIV care utilization.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14659"},"PeriodicalIF":3.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318766","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":"Insulin Out-of-Pocket Spending Caps and Employer-Sponsored Insurance: Changes in Out-of-Pocket and Total Costs for Insulin and Healthcare.","authors":"Khrysta A Baig, Carrie E Fry, Melinda B Buntin, Alvin C Powers, Stacie B Dusetzina","doi":"10.1111/1475-6773.14656","DOIUrl":"https://doi.org/10.1111/1475-6773.14656","url":null,"abstract":"<p><strong>Objective: </strong>To estimate the impact of state-level insulin out-of-pocket caps on changes in out-of-pocket and total costs of insulin and healthcare for insulin users with employer-sponsored insurance.</p><p><strong>Study setting and design: </strong>We evaluated changes in costs using a quasi-experimental (triple difference-in-differences; \"DDD\") design to analyze multi-carrier claims from insulin users enrolled in fully insured (state-regulated) and self-funded (generally exempt) employer-sponsored plans in 10 states with caps by January 2021 compared to no-cap states pre-/post-cap implementation. Primary outcomes were changes in insulin out-of-pocket spending, total (plan + member) paid for insulin, and total healthcare costs. Secondary outcomes were intermediary (e.g., pharmaceutical) changes in out-of-pocket and total costs.</p><p><strong>Data sources and analytic sample: </strong>In the policy year (no-cap states: 2021), we identified 218,441 insulin-users in the Health Care Cost Institute 2.0 Dataset (cap states: 27,834 in fully insured and 22,131 in self-funded plans; no-cap states: 97,239 in fully insured and 71,237 in self-funded plans) and 215,635 in the year prior.</p><p><strong>Principal findings: </strong>We found evidence of modest decreases in 30-day standardized (DDD: -$5 [95% CI: -$6 to -$4]; p < 0.001) and annual (DDD: -$67 [95% CI: -$82 to -$51]; p < 0.001) insulin out-of-pocket spending. Savings increased by spending quantile (e.g., 95th-percentile change:-$347 [95% CI: -$460 to $233]). Difference-in-differences (DiD) comparing fully insured to self-funded plans within cap-states showed larger changes (e.g., 95th-percentile annual insulin out-of-pocket:-$484 [95% CI: -$651 to -$318]), likely due to policy spillover effects (i.e., fully insured plans decreased out-of-pocket in no-cap states). Change in annual total paid for healthcare was not statistically significant (DDD:-$1082 [95% CI: -$2918 to $755]; p < 0.25). We saw no evidence of caps increasing out-of-pocket or total spending on insulin, prescriptions, or healthcare.</p><p><strong>Conclusions: </strong>Our findings suggest early caps had modest effects on out-of-pocket spending among fully insured insulin users, with larger savings for those at the top of the spending distribution and no total cost increases. Policy effects may be greater than observed; they likely lag implementation and develop over time.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14656"},"PeriodicalIF":3.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318767","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":"COVID-19-Related Financial Hardship and Adherence to Adjuvant Endocrine Therapy Among Women With Early-Stage Breast Cancer.","authors":"Sara Arshad, Xin Hu, Rebecca A Krukowski, Teresa M Waters, Gregory A Vidal, Lee Schwartzberg, Joseph Lipscomb, Ilana Graetz","doi":"10.1111/1475-6773.14658","DOIUrl":"10.1111/1475-6773.14658","url":null,"abstract":"<p><strong>Objective: </strong>To examine the association between COVID-19-related hardship and 1-year adjuvant endocrine therapy (AET) adherence among women with early-stage hormone-receptor-positive breast cancer.</p><p><strong>Study setting and design: </strong>This post hoc analysis utilized data from the THRIVE trial, which tested a 6-month remote monitoring intervention on 1-year AET adherence, measured using an electronic pillbox. The 1-year follow-up survey included questions about pandemic-related hardship, including financial loss, changes/gaps in health insurance, and difficulty accessing basic needs. Participants reporting any of these were categorized as experiencing pandemic-related hardship. Logistic regressions estimated the association between patient characteristics and pandemic-related hardship, and between hardship and AET adherence (≥ 80% proportion of days covered), controlling for patient characteristics and randomization group.</p><p><strong>Data sources and analytic sample: </strong>We included 217 women diagnosed with early-stage breast cancer prescribed AET at a large cancer center who enrolled in THRIVE between April 2019 and June 2021.</p><p><strong>Principal findings: </strong>Overall, 39.6% of participants reported any pandemic-related hardship: 34.6% reported financial loss, 10.6% reported changes/gaps in insurance, and 11.1% reported difficulty accessing basic needs. In adjusted analyses, having an income ≤ 100% of federal poverty level or prior chemotherapy or radiation was associated with a 41.4 (95% CI: 9.8-73.0) and 13.8 (95% CI: 0.3-27.2) percentage-point higher likelihood, respectively, of having any pandemic-related hardship. Over half (52%) of participants were AET adherent. In adjusted analyses, 40.1% of those with any pandemic-related hardship were AET adherent, compared with 59.5% of those without hardship, a 19.3 percentage-point lower likelihood (95% CI: -33.0 to -5.7).</p><p><strong>Conclusions: </strong>Pandemic-related hardship was more common among individuals with lower income or prior radiation or chemotherapy, and was associated with lower AET adherence, with possible impacts on cancer progression and survival. These findings highlight the need for routine financial screening and targeted support, particularly among lower-income patients on long-term AET.</p><p><strong>Trial registration: </strong>NCT03592771.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14658"},"PeriodicalIF":3.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318765","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":"Importance of Prior Patient Interactions With the Healthcare System to Engaging With Pretest Cancer Genetic Services via Digital Health Tools Among Unaffected Primary Care Patients: Findings From the BRIDGE Trial.","authors":"Lingzi Zhong, Jemar R Bather, Melody S Goodman, Lauren Kaiser-Jackson, Molly Volkmar, Richard L Bradshaw, Rachelle Lorenz Chambers, Daniel Chavez-Yenter, Sarah V Colonna, Whitney Maxwell, Michael Flynn, Amanda Gammon, Rachel Hess, Devin M Mann, Rachel Monahan, Yang Yi, Meenakshi Sigireddi, David W Wetter, Kensaku Kawamoto, Guilherme Del Fiol, Saundra S Buys, Kimberly A Kaphingst","doi":"10.1111/1475-6773.14652","DOIUrl":"10.1111/1475-6773.14652","url":null,"abstract":"<p><strong>Objective: </strong>To examine whether patient sociodemographic and clinical characteristics and prior interactions with the healthcare system were associated with opening patient portal messages related to cancer genetic services and beginning services.</p><p><strong>Study setting and design: </strong>The trial was conducted in the University of Utah Health (UHealth) and NYU Langone Health (NYULH) systems. Between 2020 and 2023, 3073 eligible primary care patients aged 25-60 years meeting family history-based criteria for cancer genetic evaluation were randomized 1:1 to receive a patient portal message with a hyperlink to a pretest genetics education chatbot or information about scheduling a pretest standard of care (SOC) appointment.</p><p><strong>Data sources and analytic sample: </strong>Primary data were collected. Eligible patients had a primary care visit in the previous 3 years, a patient portal account, no prior cancer diagnosis except nonmelanoma skin cancer, no prior cancer genetic services, and English or Spanish as their preferred language. Multivariable models identified predictors of opening patient portal messages by site and beginning pretest genetic services by site and experimental condition.</p><p><strong>Principal findings: </strong>Number of previous patient portal logins (UHealth average marginal effect [AME]: 0.32; 95% CI: 0.27, 0.38; NYULH AME: 0.33; 95% CI: 0.27, 0.39), having a recorded primary care provider (NYULH AME: 0.15; 95% CI: 0.08, 0.22), and more primary care visits in the previous 3 years (NYULH AME: 0.09; 95% CI: 0.02, 0.16) were associated with opening patient portal messages about genetic services. Number of previous patient portal logins (UHealth AME: 0.14; 95% CI: 0.08, 0.21; NYULH AME: 0.18; 95% CI: 0.12, 0.23), having a recorded primary care provider (NYULH AME: 0.08; 95% CI: 0.01, 0.14), and more primary care visits in the previous 3 years (NYULH AME: 0.07; 95% CI: 0.01, 0.13) were associated with beginning pretest genetic services. Patient sociodemographic and clinical characteristics were not significantly associated with either outcome.</p><p><strong>Conclusions: </strong>As system-level initiatives aim to reach patients eligible for cancer genetic services, patients already interacting with the healthcare system may be most likely to respond. Addressing barriers to accessing healthcare and technology may increase engagement with genetic services.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14652"},"PeriodicalIF":3.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144267915","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":"Staff Experiences With Implementation of the Referral Coordination Initiative.","authors":"Ashley C Mog, Anna Woolery, Kelty Fehling, Makkawi Makkawi, Colin I O'Donnell, Edward O'Brien, Paul L Hebert, Brian N Palen, David H Au, Lisa M Arfons, David Winchester, Lucas M Donovan","doi":"10.1111/1475-6773.14654","DOIUrl":"10.1111/1475-6773.14654","url":null,"abstract":"<p><strong>Objective: </strong>To understand VHA staff experiences with the referral coordination initiative (RCI) following nationwide dissemination.</p><p><strong>Study setting and design: </strong>RCI uses a team-based approach to improve the timeliness, efficiency, and patient-centeredness of specialty care referrals, while redistributing the time-intensive triage tasks from specialist providers to nurses. To assess frontline experiences with RCI, we purposively sampled four VHA sites for qualitative interviews, ensuring variability around the use of nurses in triage and the organization of scheduling staff within three high-volume specialties: cardiology, gastroenterology, and pulmonary. From May to December 2023, we conducted semi-structured interviews with 68 VHA staff members who engaged in various aspects of referral coordination, including interviews with nurses, schedulers, specialists, and referring providers.</p><p><strong>Data sources and analytic sample: </strong>We asked staff about challenges and facilitators to RCI implementation and maintenance. If certain RCI elements (e.g., nurse triage) were not implemented, we asked about anticipated challenges and facilitators. We analyzed qualitative data concurrently with data collection using a rapid matrix analysis approach.</p><p><strong>Principal findings: </strong>Staff expressed varying perceptions around the effects of RCI and its impacts on specialist burden and clinic staffing. We identified challenges to RCI, including (1) inconsistent staff perceptions around program goals, (2) mixed perceptions around the appropriateness of nurse triage, (3) lack of clear specialty-specific triage guidelines, and (4) limited coordination with schedulers. Key facilitators of RCI included (1) leveraging existing relationships and nurses with existing specialty-specific expertise, and (2) building relationships and clear triage guidelines with specialties.</p><p><strong>Conclusions: </strong>To streamline patient-centered referrals, health systems should foster working relationships between referral management teams and specialties. While nurse-led triage can improve efficiency, concerted efforts are necessary to train nurses and develop clear triage criteria.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14654"},"PeriodicalIF":3.1,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250881","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":"Where Can Artificial Intelligence Assist Cancer Care?: Examining Patient-Centered Communication Dimension Effects.","authors":"Qiwei Luna Wu, Yue Liao, Grace Ellen Brannon","doi":"10.1111/1475-6773.14653","DOIUrl":"https://doi.org/10.1111/1475-6773.14653","url":null,"abstract":"<p><strong>Objective: </strong>To explore how aspects of patient-centered communication (PCC) may directly or indirectly predict patients' preferences for artificial intelligences (AIs) versus human medical professionals, based on the stimulus-organism-response model.</p><p><strong>Study setting and design: </strong>As AI gains popularity and researchers explore its application in the medical context, it is important to understand how current patient-provider dynamics involving high technology (e.g., telehealth communication) may shape patients' perceptions of future use of AI, especially in the context of cancer care where patient satisfaction and sense of care continuity are important. Participants were recruited from an online panel in China (June 2024). Structural equation modeling analyzed the relationships among variables, including six PCC dimensions (i.e., exchanging information, fostering healing relationships, making decisions, managing uncertainty, responding to emotions, and enabling patient self-management), communication outcomes (i.e., patient satisfaction, sense of care continuity), and patients' preference of AIs vs. human medical professionals.</p><p><strong>Data sources and analytic sample: </strong>Primary data were collected from an online panel of 495 Chinese cancer patients in China, representative of the gender and age distribution of the overall Chinese population due to quota sampling.</p><p><strong>Principal findings: </strong>Direct predictors of preference for replacing human medical professionals with AIs included lower patient satisfaction (β = -11, p < 0.05), lower ease of use (β = -0.1, p < 0.05), better care continuity (β = 0.15, p < 0.01), providers' attending to emotions (β = 0.17, p < 0.05), and less enablement in self-management (β = -0.17, p < 0.01). Patient satisfaction, ease of use, and care continuity mediated the relationships between different PCC dimensions and patients' preferences for AI use.</p><p><strong>Conclusions: </strong>PCC and communication outcomes are associated with cancer patients' preferences in future AI use. Our study sheds light on how clinicians may improve their communication to educate patients on navigating the cancer care continuum using AI technology.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14653"},"PeriodicalIF":3.1,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235980","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":"Hospital Accreditation and Geographic Disparities in Timely Cancer Care.","authors":"Jason T Semprini, Joshua W Devine, Ingrid M Lizarraga, Mary E Charlton","doi":"10.1111/1475-6773.14655","DOIUrl":"https://doi.org/10.1111/1475-6773.14655","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate whether the association between receiving care at an accredited hospital and timely treatment initiation varies by county income level.</p><p><strong>Study setting and design: </strong>This cross-sectional study compared days from diagnosis to treatment initiation among patients receiving care at CoC-accredited hospitals with patients receiving care at non-accredited hospitals. We estimated distributional effects with a quantile regression model. We stratified patients into low (median household-income < 80k) and high-income (median household-income ≥ 80k) counties.</p><p><strong>Data sources and analytic sample: </strong>We analyzed population-based Surveillance, Epidemiological, and End Results case data (2018-2021). We excluded cancer cases that did not receive treatment. All analyses were adjusted for tumor and patient characteristics, treatment received, and geographic factors.</p><p><strong>Principal findings: </strong>Among 2,107,188 patients receiving cancer treatment, 73.65% received care at an accredited hospital. Median time-to-treatment was 27 days (interquartile range = 1-52). Care at an accredited hospital was associated with longer median time-to-treatment (+2.6 days) in low-income counties but not high-income counties. Similarly, care at an accredited hospital was associated with widening the time-to-treatment interquartile range (+1.8 days) in low-income but not high-income counties. The magnitude of these associations was highest in patients aged 65+, unmarried, diagnosed at an early stage, and in less common cancers. Only among patients diagnosed with distant-stage cancer was accreditation associated with reduced median time-to-treatment in both low and high-income counties.</p><p><strong>Conclusions: </strong>Treatment at an accredited hospital appeared to increase time-to-treatment differences between high-and low-income counties and low-income counties. This heterogeneity may reflect access challenges facing low-income cancer patients. Health systems seeking to provide high quality, timely care must overcome these access challenges as they navigate patients through the cancer care continuum. While a 2.6-day delay in treatment may not impact outcomes, future research should understand why patients from lower-resource communities wait longer than patients in affluent communities.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14655"},"PeriodicalIF":3.1,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235978","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":"Veteran Mental Health Emergency Care Utilization Following SARS-CoV-2 Infection.","authors":"Jason I Chen, Meike Niederhausen, David P Bui, Diana J Govier, Mazhgan Rowneki, Alex Hickok, Troy A Shahoumian, Megan Shepherd-Banigan, Anna Korpak, Eric Hawkins, Alan R Teo, Jennifer Naylor, Thomas F Osborne, Valerie A Smith, C Barrett Bowling, Edward J Boyko, George N Ioannou, Matthew L Maciejewski, Ann M O'Hare, Elizabeth M Viglianti, Theodore J Iwashyna, Amy S B Bohnert, Denise M Hynes","doi":"10.1111/1475-6773.14622","DOIUrl":"10.1111/1475-6773.14622","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate whether Veterans infected with SARS-CoV-2 have an elevated risk for needing mental health emergency care (MHEC) relative to uninfected comparators, as measured by emergency department or urgent care clinic utilization for a mental health diagnosis.</p><p><strong>Data sources/extraction: </strong>Data from Veterans Health Administration (VHA), VHA-paid, and Centers for Medicare & Medicaid-paid services were used to identify incident MHEC use within 1 year of infection for Veterans with a SARS-CoV-2 infection and matched comparators.</p><p><strong>Study design: </strong>This was a national, retrospective cohort study that leveraged a target trial emulation framework to examine long-term outcomes of SARS-CoV-2 infection among Veterans enrolled in VHA care. Uninfected comparators were matched based on month of infection, demographic, clinical, and health care utilization characteristics. We calculated cumulative incidence rates per 10,000 persons and utilized Cox regression models to estimate hazard ratios (HR) for MHEC up to one year post-infection.</p><p><strong>Principal findings: </strong>The cohort included 207,968 Veterans with SARS-CoV-2 and 1,036,944 comparators. The 365-day incidence of MHEC use was greater among SARS-CoV-2 patients than comparators (HR = 1.48; 95% CI: [1.44, 1.52]). Patients with SARS-CoV-2 had a higher hazard for MHEC use than comparators in all timeframes analyzed.</p><p><strong>Conclusions: </strong>SARS-CoV-2 infection was associated with increased MHEC use. Active care coordination with existing mental health treatment providers may help mitigate post-infection mental health distress. Future research should explore specific contextual factors contributing to MHEC, such as gaps in continuity of care.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14622"},"PeriodicalIF":3.2,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235979","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":"Completeness and Quality of Data for Children in Medicaid Comprehensive Managed Care Compared to Fee-for-Service, 2001-2019.","authors":"Kristen Lloyd, Sanika Rege, Stephen Crystal, Mark Olfson, Daniel B Horton, Hillary Samples","doi":"10.1111/1475-6773.14651","DOIUrl":"https://doi.org/10.1111/1475-6773.14651","url":null,"abstract":"<p><strong>Objective: </strong>To compare the data in national Medicaid research files for children enrolled in comprehensive managed care (CMC) vs. fee-for-service (FFS).</p><p><strong>Study setting and design: </strong>This observational study utilized inpatient, other services, and pharmacy files in national Medicaid data from 2001 to 2019. CMC-enrolled children in state-years with ≥ 10% CMC enrollment were compared on several measures to yearly FFS data across all available states. Completeness measures were the proportion with any claim and mean claims per enrollee. Quality measures were the proportion of inpatient and other services claims with primary diagnosis and procedure codes and the proportion of prescription claims with fill dates, National Drug Codes, days supplied, and quantity dispensed. The range of acceptable values for each measure was defined as overall FFS mean ± 2 standard deviations.</p><p><strong>Data sources and analytic sample: </strong>We analyzed secondary MAX/TAF data on 45 states from 2001 to 2013 and 50 states and DC from 2014 to 2019. The sample included children ages 0-17 with continuous calendar-year enrollment in Medicaid and/or Medicaid-expansion CHIP with full Medicaid benefits and not dually enrolled in Medicare.</p><p><strong>Principal findings: </strong>The sample included 368.7 million person-years across 888 state-years. Three hundred thirty-eight state-years (38.1%) had < 10% CMC enrollment. Of 550 remaining state-years, 70%, representing ~59% of all enrolled children, met criteria for both completeness and quality in all three files, increasing from 35.7% of states in 2001 to 83.8% of states in 2019. The percentages of state-years with comparable CMC/FFS data for completeness measures were 92.7% inpatient, 86.0% other services, and 87.3% prescription. For quality measures, these proportions were 88.5% inpatient, 95.6% other services, and 96.9% prescription.</p><p><strong>Conclusions: </strong>Growth in Medicaid-managed care over the last two decades, coupled with observed improvements in CMC data quality, presents opportunities to increase the sample size and scope of epidemiologic and health services research on publicly insured children.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14651"},"PeriodicalIF":3.1,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217628","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":"Employment, Income, the ACA, and Health Insurance Coverage of Working-Age Adults During the First Year of the COVID-19 Pandemic: A Reassessment.","authors":"José J Escarce, Dennis Rünger, James M Campbell, Peter J Huckfeldt","doi":"10.1111/1475-6773.14646","DOIUrl":"https://doi.org/10.1111/1475-6773.14646","url":null,"abstract":"<p><strong>Objective: </strong>To examine the effects of income, income transitions, and the Affordable Care Act (ACA) Medicaid expansion on health insurance coverage for working-age adults who became unemployed during the first year of the COVID-19 pandemic and for those who remained employed.</p><p><strong>Study setting and design: </strong>We estimated panel-data regression models to assess the effects of employment, income and income transitions, and the Medicaid expansion on the type of insurance coverage and uninsurance among working-age adults in the United States during 2019 and 2020.</p><p><strong>Data sources and analytic sample: </strong>Longitudinal data from the 2019-2020 Medical Expenditure Panel Survey and data on states' Medicaid expansion status. The study participants were 6435 adults aged 26-64.</p><p><strong>Principal findings: </strong>Participants in all income groups who suffered spells of unemployment during the pandemic lost employer-sponsored insurance. In expansion states, the Medicaid expansion played a key role in preventing declines in insurance coverage for disadvantaged participants. The expansion was especially beneficial for participants with low pre-pandemic incomes who had unemployment spells during the pandemic (7.5% point increase in Medicaid coverage [95% CI, 1.2 to 13.8]) and for participants who transitioned from high pre-pandemic incomes to low pandemic incomes whether or not they lost their jobs (23.9% point increase in Medicaid coverage [95% CI, 7.8 to 40.0] during unemployment spells; 12.0% point increase [95% CI, 7.2 to 16.9] for those who remained employed). We found weaker evidence that private exchange coverage blunted increases in uninsurance in non-expansion states.</p><p><strong>Conclusion: </strong>Our findings clarify findings from earlier research by demonstrating that not only employment status and pre-pandemic income, but also income transitions, played a key role in determining who received Medicaid coverage during the pandemic in Medicaid expansion states. All in all, the ACA acquitted itself relatively well during a very stressful period for the United States' system of health insurance.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e14646"},"PeriodicalIF":3.1,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217629","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}