{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T14:12:26Z","timestamp":1785247946013,"version":"3.55.0"},"reference-count":52,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100009826","name":"Harvey L. Neiman Health Policy Institute","doi-asserted-by":"publisher","award":["For partial support for Joshua A. Hirsch"],"award-info":[{"award-number":["For partial support for Joshua A. 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Care utilization was compared between subgroups: metropolitan versus small\/rural communities, high-income versus low-income communities, and least-deprived versus most-deprived (Area Deprivation Index [ADI]) communities. Care-utilization rates were normalized to account for within and between year differences in subgroup characteristics using multivariable logistic regression. Care-utilization gaps were computed as the difference in normalized utilization values between subgroups. The temporal association between gap size and the inflation-adjusted conversion factor was assessed with linear regression. There were 32,764,305 beneficiary years (4,662,729 unique beneficiaries) that met the selection criteria. Over the 2005-2023 period, the care-utilization gaps for any physician care increased 1.76, 5.89, and 3.82 percentage points for the urbanicity, community-income, and ADI gaps, respectively. Gap growth was significantly associated with the inflation-adjusted conversion factor, which decreased 48.3% between 2005 and 2025. This inflation-adjusted conversion factor decrease was associated with care-utilization gap increases of 2.46 (urbanicity), 7.00 (community-income), and 5.31 (ADI) percentage points across all physicians. Percentage-point gap increases varied by specialty and were largest for family practice physicians: 21.31 (urbanicity), 14.02 (community-income), and 19.55 (ADI) percentage points. Hence, decreased reimbursement resulting from the Medicare budget neutrality mandate may exacerbate disparities in access to care for traditionally underserved Americans.<\/jats:p>","DOI":"10.1177\/00469580261473400","type":"journal-article","created":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T13:50:00Z","timestamp":1784987400000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Association Between the Declining Conversion Factor and Access to Care for Medicare Beneficiaries"],"prefix":"10.1177","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1377-0787","authenticated-orcid":false,"given":"Eric W.","family":"Christensen","sequence":"first","affiliation":[{"name":"Harvey L. Neiman Health Policy Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandra R.","family":"Drake","sequence":"additional","affiliation":[{"name":"Harvey L. 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