Assessing the accuracy of race‐and‐ethnicity data in the Outcome and Assessment Information Set

• DOI: 10.1111/jgs.18889
• Publication Date: 2024-03-21T11:58:07Z
• Authors: Steven C. Martino; Marc N. Elliott; Ann Haas; Alon Peltz; Debra Saliba; Sapha Hassan; Eve Rothenberg; Amena Keshawarz; Megan Rushkin; Jennifer Gildner; Nathan Orr; Melissa Hager; Raquel Myers; Randall Kiser; Susannah Bernheim
• Keywords: Geocoding; Minimum Data Set

Limitations in the quality of race-and-ethnicity information Medicare's data systems constrain efforts to assess disparities care among older Americans. Using demographic from standardized patient assessments may be an efficient way enhance accuracy and completeness systems, but it is critical first establish these as they prone inaccurate observer-reported or third-party-based information. This study evaluates patient-level included Outcome Assessment Information Set (OASIS) submitted by home health agencies.