{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T15:28:19Z","timestamp":1786375699476,"version":"build-2736575974"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000133","name":"Agency for Healthcare Research and Quality","doi-asserted-by":"publisher","award":["R01HS028985"],"award-info":[{"award-number":["R01HS028985"]}],"id":[{"id":"10.13039\/100000133","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Attributing patients to physicians using claims data is a key design feature of most payment and delivery models. However, claims-based attribution makes model participants less representative by excluding beneficiaries who use less care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used the attribution methodology from the largest completed primary care model, Comprehensive Primary Care Plus (CPC+), to describe differences in attributable and unattributable Medicare beneficiaries living in CPC + regions from 2016 to 2021.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Unattributed beneficiaries were more male (56% vs 43%), eligible for the low-income drug subsidy (15% vs 12%), dual eligible (13% vs 10%), and non-White (22% vs 15%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Tests of models that use claims-based attribution may fail to generate evidence relevant to underserved groups. Policymakers should consider attribution designs that could improve representativeness of model test populations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/haschl\/qxag198","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T11:42:19Z","timestamp":1785498139000},"source":"Crossref","is-referenced-by-count":0,"title":["Unattributed Medicare beneficiaries have greater social disadvantage than those linked to primary care physicians"],"prefix":"10.1093","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5224-6497","authenticated-orcid":false,"given":"Katherine M","family":"Ianni","sequence":"first","affiliation":[{"name":"Division of Health Policy and Economics, Department of Population Health Sciences, Weill Cornell Medical College , New York, NY 10022 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0366-3929","authenticated-orcid":false,"given":"Laura A","family":"Hatfield","sequence":"additional","affiliation":[{"name":"Statistics & Data Science Department, NORC at the University of Chicago , Chicago, IL ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,1]]},"reference":[{"issue":"6","key":"2026081010364576900_qxag198-B1","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1177\/1077558719856775","article-title":"Value-based provider payment initiatives combining global payments with explicit quality incentives: a systematic review","volume":"77","author":"Cattel","year":"2020","journal-title":"Med Care Res Rev"},{"issue":"S2","key":"2026081010364576900_qxag198-B2","doi-asserted-by":"publisher","first-page":"e14419","DOI":"10.1111\/1475-6773.14419","article-title":"Transporting 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