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Processing and validation of inpatient Medicare Advantage data for use in hospital outcome measures.
Kyanko, Kelly A; Sahay, Kashika M; Wang, Yongfei; Schreiber, Michelle; Hager, Melissa; Myers, Raquel; Johnson, Wanda; Zhang, Jing; Yen, Bing-Jie; Suter, Lisa G; Triche, Elizabeth W; Li, Shu-Xia.
Afiliación
  • Kyanko KA; Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA.
  • Sahay KM; Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
  • Wang Y; Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation (YNHHSC/CORE), Yale School of Medicine, New Haven, Connecticut, USA.
  • Schreiber M; Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
  • Hager M; Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation (YNHHSC/CORE), Yale School of Medicine, New Haven, Connecticut, USA.
  • Myers R; Centers for Medicare & Medicaid Services (CMS), Center for Clinical Standards & Quality (CCSQ), Baltimore, Maryland, USA.
  • Johnson W; Centers for Medicare & Medicaid Services (CMS), Center for Clinical Standards & Quality (CCSQ), Baltimore, Maryland, USA.
  • Zhang J; Centers for Medicare & Medicaid Services (CMS), Center for Clinical Standards & Quality (CCSQ), Baltimore, Maryland, USA.
  • Yen BJ; Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation (YNHHSC/CORE), Yale School of Medicine, New Haven, Connecticut, USA.
  • Suter LG; Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
  • Triche EW; Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation (YNHHSC/CORE), Yale School of Medicine, New Haven, Connecticut, USA.
  • Li SX; Department of Applied Health Science, Indiana University Bloomington School of Public Health, Bloomington, Indiana, USA.
Health Serv Res ; 2024 Jul 03.
Article en En | MEDLINE | ID: mdl-38961668
ABSTRACT

OBJECTIVE:

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. DATA SOURCES AND STUDY

SETTING:

Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges. STUDY

DESIGN:

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. DATA COLLECTION/EXTRACTION

METHODS:

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. PRINCIPAL

FINDINGS:

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.

CONCLUSIONS:

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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Health Serv Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Health Serv Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos