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Objective Data Sources and Study Setting Study Design Data Collection/Extraction Methods Principal Findings Conclusions To determine the feasibility of integrating Medicare Advantage (MA) admissions into the Centers for Medicare & Medicaid Services (CMS) hospital outcome measures through combining Medicare Advantage Organization (MAO) encounter‐ and hospital‐submitted inpatient claims.Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges.We examined timeliness of MA claims, compared diagnosis and procedure codes for admissions with claims submitted both by the hospital and the MAO (overlapping claims), and compared demographic characteristics and principal diagnosis codes for admissions with overlapping claims versus admissions with a single claim.We combined hospital‐ and MAO‐submitted claims to capture MA admissions from all hospitals and identified overlapping claims. For admissions with only an MAO‐submitted claim, we used provider history data to match the National Provider Identifier on the claim to the CMS Certification Number used for reporting purposes in CMS outcome measures.After removing void and duplicate claims, identifying overlapped claims between the hospital‐ and MAO‐submitted datasets, restricting claims to acute care and critical access hospitals, and bundling same admission claims, we identified 5,078,611 MA admissions. Of these, 76.1% were submitted by both the hospital and MAO, 14.2% were submitted only by MAOs, and 9.7% were submitted only by hospitals. Nearly all (96.6%) hospital‐submitted claims were submitted within 3 months after a one‐year performance period, versus 85.2% of MAO‐submitted claims. Among the 3,864,524 admissions with overlapping claims, 98.9% shared the same principal diagnosis code between the two datasets, and 97.5% shared the same first procedure code.Inpatient MA data are feasible for use in CMS claims‐based hospital outcome measures. We recommend prioritizing hospital‐submitted over MAO‐submitted claims for analyses. Monitoring, data audits, and ongoing policies to improve the quality of MA data are important approaches to address potential missing data and errors. [ABSTRACT FROM AUTHOR]