title: Improving Hospital Reporting of Patient Race and Ethnicity--Approaches to Data Auditing.
abstract: OBJECTIVE
  To investigate new metrics to improve the reporting of patient race and ethnicity (R/E) by hospitals.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
authors.affiliation: UCLA School of Medicine, Division of General Internal Medicine and Health Services Research, Los Angeles, CA.
authors.forename: David S
authors.initials: DS
authors.lastname: Zingmond
authors.affiliation: UCLA School of Medicine, Division of General Internal Medicine and Health Services Research, Los Angeles, CA.
authors.forename: Punam
authors.initials: P
authors.lastname: Parikh
authors.affiliation: UCLA School of Medicine, Division of General Internal Medicine and Health Services Research, Los Angeles, CA.
authors.forename: Rachel
authors.initials: R
authors.lastname: Louie
authors.affiliation: Cancer Prevention Institute of California, Fremont, CA.
authors.forename: Daphne Y
authors.initials: DY
authors.lastname: Lichtensztajn
authors.affiliation: UCLA Fielding School of Public Health, Department of Health Services, Los Angeles, CA.
authors.forename: Ninez
authors.initials: N
authors.lastname: Ponce
authors.affiliation: Patient-Centered Outcomes Research Institute, Washington, DC.
authors.forename: Romana
authors.initials: R
authors.lastname: Hasnain-Wynia
authors.affiliation: Cancer Prevention Institute of California, Fremont, CA.
authors.forename: Scarlett Lin
authors.initials: SL
authors.lastname: Gomez
mesh_terms: D000328:Adult; D001723:Birth Rate; D002140:California / Q000453:epidemiology; D019352:Censuses; D003625:Data Collection / Q000592:standards*; D016208:Databases, Factual; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D006302:Health Services Research; D006751:Hospital Information Systems; D006801:Humans; D007231:Infant, Newborn; D008498:Medical Record Linkage; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology; D010351:Patient Discharge; D011247:Pregnancy; D058996:Quality Improvement; D044469:Racial Groups / Q000706:statistics & numerical data*; D012042:Registries
keywords: Data auditing; gold standard comparisons; race/ethnicity