Patrick N O'Mahen, Chase S Eck, Suja S Rajan, Cheng Rebecca Jiang, Christine Yang, Laura A Petersen
{"title":"医疗补助双登记退伍军人风险调整诊断信息的数量和重叠比较。","authors":"Patrick N O'Mahen, Chase S Eck, Suja S Rajan, Cheng Rebecca Jiang, Christine Yang, Laura A Petersen","doi":"10.1111/1475-6773.70031","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To measure discrepancies in risk adjustment scores using only Medicaid or Veterans Health Administration (VA) diagnoses for Veterans dually enrolled in VA and Medicaid.</p><p><strong>Study setting and design: </strong>Veterans aged 18-64 enrolled in the VA and Medicaid for at least one full calendar year during 2017-2020. We compared the number and overlap of annual diagnoses derived from VA and Medicaid data. We also calculated Charlson, Elixhauser, and Centers for Medicare and Medicaid Hierarchical Condition Categories Version 21 (CMS-V21) risk scores using VA-only, Medicaid-only, and combined VA-Medicaid data for each person-year. We used intraclass correlations within risk measures to compare scores across risk measures.</p><p><strong>Data sources and analytic sample: </strong>We used data from the VA's Assistant Deputy Undersecretary for Health's (ADUSH) enrollment files regarding age and VA Priority Group to select our cohort of VA enrollees. We used T-MSIS Analytic Files (TAF) and the Demographics and Enrollment (DE) file to determine Medicaid enrollment.</p><p><strong>Principal findings: </strong>Our study cohort contained 183,018 dual-enrollees with service-connected disabilities representing 405,318 person years and 219,977 dual enrollees without service-connected disabilities (531,948 person years). On average, service-connected individuals had 9.1 fewer diagnoses from Medicaid-only data than from VA-only data (95% Confidence Interval (CI): [9.0, 9.1]) and 5.0 fewer for non-service-connected Veterans (95% CI: [4.9, 5.1]). Intraclass correlations between VA-only data and combined VA-Medicaid scores had higher correlations for Charlson (0.816 vs. 0.591 for service connected, 0.722 vs. 0.638 for non-service connected) and Elixhauser (0.818 vs. 0.609 for service-connected, 0.723 to 0.702 non-service-connected) scores, while Medicaid-only scores had higher correlations for CMS V21 (0.756 vs. 0.666 for service-connected, 0.795 to 0.542 for non service-connected).</p><p><strong>Conclusions: </strong>Medicaid and VA data represent non-overlapping diagnoses data in three common risk scores. Researchers should consider combining records to calculate disease burden for dual-enrolled Veterans to ensure complete capture of risk.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":" ","pages":"e70031"},"PeriodicalIF":3.2000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Number and Overlap of Diagnostic Information for Risk Adjustment for Dually Enrolled Veterans in Medicaid.\",\"authors\":\"Patrick N O'Mahen, Chase S Eck, Suja S Rajan, Cheng Rebecca Jiang, Christine Yang, Laura A Petersen\",\"doi\":\"10.1111/1475-6773.70031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To measure discrepancies in risk adjustment scores using only Medicaid or Veterans Health Administration (VA) diagnoses for Veterans dually enrolled in VA and Medicaid.</p><p><strong>Study setting and design: </strong>Veterans aged 18-64 enrolled in the VA and Medicaid for at least one full calendar year during 2017-2020. We compared the number and overlap of annual diagnoses derived from VA and Medicaid data. We also calculated Charlson, Elixhauser, and Centers for Medicare and Medicaid Hierarchical Condition Categories Version 21 (CMS-V21) risk scores using VA-only, Medicaid-only, and combined VA-Medicaid data for each person-year. We used intraclass correlations within risk measures to compare scores across risk measures.</p><p><strong>Data sources and analytic sample: </strong>We used data from the VA's Assistant Deputy Undersecretary for Health's (ADUSH) enrollment files regarding age and VA Priority Group to select our cohort of VA enrollees. We used T-MSIS Analytic Files (TAF) and the Demographics and Enrollment (DE) file to determine Medicaid enrollment.</p><p><strong>Principal findings: </strong>Our study cohort contained 183,018 dual-enrollees with service-connected disabilities representing 405,318 person years and 219,977 dual enrollees without service-connected disabilities (531,948 person years). On average, service-connected individuals had 9.1 fewer diagnoses from Medicaid-only data than from VA-only data (95% Confidence Interval (CI): [9.0, 9.1]) and 5.0 fewer for non-service-connected Veterans (95% CI: [4.9, 5.1]). Intraclass correlations between VA-only data and combined VA-Medicaid scores had higher correlations for Charlson (0.816 vs. 0.591 for service connected, 0.722 vs. 0.638 for non-service connected) and Elixhauser (0.818 vs. 0.609 for service-connected, 0.723 to 0.702 non-service-connected) scores, while Medicaid-only scores had higher correlations for CMS V21 (0.756 vs. 0.666 for service-connected, 0.795 to 0.542 for non service-connected).</p><p><strong>Conclusions: </strong>Medicaid and VA data represent non-overlapping diagnoses data in three common risk scores. Researchers should consider combining records to calculate disease burden for dual-enrolled Veterans to ensure complete capture of risk.</p>\",\"PeriodicalId\":55065,\"journal\":{\"name\":\"Health Services Research\",\"volume\":\" \",\"pages\":\"e70031\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Services Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/1475-6773.70031\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/1475-6773.70031","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Comparison of Number and Overlap of Diagnostic Information for Risk Adjustment for Dually Enrolled Veterans in Medicaid.
Objective: To measure discrepancies in risk adjustment scores using only Medicaid or Veterans Health Administration (VA) diagnoses for Veterans dually enrolled in VA and Medicaid.
Study setting and design: Veterans aged 18-64 enrolled in the VA and Medicaid for at least one full calendar year during 2017-2020. We compared the number and overlap of annual diagnoses derived from VA and Medicaid data. We also calculated Charlson, Elixhauser, and Centers for Medicare and Medicaid Hierarchical Condition Categories Version 21 (CMS-V21) risk scores using VA-only, Medicaid-only, and combined VA-Medicaid data for each person-year. We used intraclass correlations within risk measures to compare scores across risk measures.
Data sources and analytic sample: We used data from the VA's Assistant Deputy Undersecretary for Health's (ADUSH) enrollment files regarding age and VA Priority Group to select our cohort of VA enrollees. We used T-MSIS Analytic Files (TAF) and the Demographics and Enrollment (DE) file to determine Medicaid enrollment.
Principal findings: Our study cohort contained 183,018 dual-enrollees with service-connected disabilities representing 405,318 person years and 219,977 dual enrollees without service-connected disabilities (531,948 person years). On average, service-connected individuals had 9.1 fewer diagnoses from Medicaid-only data than from VA-only data (95% Confidence Interval (CI): [9.0, 9.1]) and 5.0 fewer for non-service-connected Veterans (95% CI: [4.9, 5.1]). Intraclass correlations between VA-only data and combined VA-Medicaid scores had higher correlations for Charlson (0.816 vs. 0.591 for service connected, 0.722 vs. 0.638 for non-service connected) and Elixhauser (0.818 vs. 0.609 for service-connected, 0.723 to 0.702 non-service-connected) scores, while Medicaid-only scores had higher correlations for CMS V21 (0.756 vs. 0.666 for service-connected, 0.795 to 0.542 for non service-connected).
Conclusions: Medicaid and VA data represent non-overlapping diagnoses data in three common risk scores. Researchers should consider combining records to calculate disease burden for dual-enrolled Veterans to ensure complete capture of risk.
期刊介绍:
Health Services Research (HSR) is a peer-reviewed scholarly journal that provides researchers and public and private policymakers with the latest research findings, methods, and concepts related to the financing, organization, delivery, evaluation, and outcomes of health services. Rated as one of the top journals in the fields of health policy and services and health care administration, HSR publishes outstanding articles reporting the findings of original investigations that expand knowledge and understanding of the wide-ranging field of health care and that will help to improve the health of individuals and communities.