Literature DB >> 26077950

Improving Hospital Reporting of Patient Race and Ethnicity--Approaches to Data Auditing.

David S Zingmond1, Punam Parikh1, Rachel Louie1, Daphne Y Lichtensztajn2, Ninez Ponce3, Romana Hasnain-Wynia4, Scarlett Lin Gomez2.   

Abstract

OBJECTIVE: To investigate new metrics to improve the reporting of patient race and ethnicity (R/E) by hospitals. DATA SOURCES: California Patient Discharge Database (PDD) and birth registry, 2008-2009, Healthcare and Cost Utilization Project's State Inpatient Database, 2008-2011, cancer registry 2000-2008, and 2010 US Census Summary File 2. STUDY
DESIGN: We examined agreement between hospital reported R/E versus self-report among mothers delivering babies and a cancer cohort in California. Metrics were created to measure root mean squared differences (RMSD) by hospital between reported R/E distribution and R/E estimates using R/E distribution within each patient's zip code of residence. RMSD comparisons were made to corresponding "gold standard" facility-level measures within the maternal cohort for California and six comparison states. DATA COLLECTION: Maternal birth hospitalization (linked to the state birth registry) and cancer cohort records linked to preceding and subsequent hospitalizations. Hospital discharges were linked to the corresponding Census zip code tabulation area using patient zip code. PRINCIPAL
FINDINGS: Overall agreement between the PDD and the gold standard for the maternal cohort was 86 percent for the combined R/E measure and 71 percent for race alone. The RMSD measure is modestly correlated with the summary level gold standard measure for R/E (r = 0.44). The RMSD metric revealed general improvement in data agreement and completeness across states. "Other" and "unknown" categories were inconsistently applied within inpatient databases.
CONCLUSIONS: Comparison between reported R/E and R/E estimates using zip code level data may be a reasonable first approach to evaluate and track hospital R/E reporting. Further work should focus on using more granular geocoded data for estimates and tracking data to improve hospital collection of R/E data. © Health Research and Educational Trust.

Entities:  

Keywords:  Data auditing; gold standard comparisons; race/ethnicity

Mesh:

Year:  2015        PMID: 26077950      PMCID: PMC4545337          DOI: 10.1111/1475-6773.12324

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  16 in total

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  10 in total

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