{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T04:43:07Z","timestamp":1766983387408,"version":"3.35.0"},"reference-count":27,"publisher":"American Medical Association (AMA)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"Importance<\/jats:title>In 2023, the Massachusetts Medicaid and Children\u2019s Health Insurance Program (MassHealth) required accountable care organizations (ACOs) to increase payments to primary care practices and shift to monthly payments, currently calibrated to historical revenues and enhanced practice capabilities, such as being staffed to address behavioral health needs. To prevent rewarding practices for avoiding difficult patients, future payments to primary care practices should reflect their patients\u2019 apparent need.<\/jats:p><\/jats:sec>Objective<\/jats:title>To describe MassHealth\u2019s initiative and a complexity-adjusted payment model.<\/jats:p><\/jats:sec>Design, Setting, and Participants<\/jats:title>This cross-sectional study of payment model development and performance was conducted between February 2022 and November 2024. Participants included all 2019 Massachusetts Medicaid managed-care eligible members who were enrolled for 183 days or longer.<\/jats:p><\/jats:sec>Exposures<\/jats:title>Medical and social complexity.<\/jats:p><\/jats:sec>Main Outcomes and Measures<\/jats:title>For each member, the primary care activity level (PCAL) outcome proxies the resources that primary care clinicians need to provide comprehensive, coordinated care. Models were evaluated via R<\/jats:italic>2<\/jats:sup> and through ratios of observed-to-expected (ie, estimated by the model) outcomes for selected subgroups, which will be approximately 1.0 when payments and expected costs are well matched. The implications of paying practices using PCAL (vs a model based only on age and sex) were explored by examining financial and practice-level characteristics in high and low deciles of practice-level estimated mean.<\/jats:p><\/jats:sec>Results<\/jats:title>Among 1 092 742 MassHealth members enrolled in 3602 primary care practices (1 014 252 person-years; mean [SD] age, 25.9 [18.4] years; 538\u202f065 [53.1%] female), the PCAL model achieved R<\/jats:italic>2<\/jats:sup>\u2009=\u200969.6% and estimates within 10% of observed PCAL spending for high-risk populations (mental health disorders, substance use disorders, complex chronic conditions, and disabilities) and across racial and ethnic groups. Age-adjusted and sex-adjusted payments would overpay practices in the lowest-need decile by 10% and underpay those in the highest-need decile by 34%, while the PCAL model would match payment to estimated need almost exactly in the lowest decile and underpay by just 6% in the highest decile.<\/jats:p><\/jats:sec>Conclusions and Relevance<\/jats:title>MassHealth\u2019s 2023 reform invests in primary care. This cross-sectional study developed a risk model that can adjust primary care payments to patient needs. Neither age and sex adjustments nor inflated historical payments would provide adequate resources to primary care practices caring for the most complex patients.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2024.58170","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T16:01:04Z","timestamp":1738598464000},"page":"e2458170","source":"Crossref","is-referenced-by-count":2,"title":["Supporting Primary Care for Medically and Socially Complex Patients in Medicaid Managed Care"],"prefix":"10.1001","volume":"8","author":[{"given":"Arlene S.","family":"Ash","sequence":"first","affiliation":[{"name":"Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew J.","family":"Alcusky","sequence":"additional","affiliation":[{"name":"Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Randall P.","family":"Ellis","sequence":"additional","affiliation":[{"name":"Department of Economics, Boston University, Boston, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meagan J.","family":"Sabatino","sequence":"additional","affiliation":[{"name":"Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frances E.","family":"Eanet","sequence":"additional","affiliation":[{"name":"Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric O.","family":"Mick","sequence":"additional","affiliation":[{"name":"Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, 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