title: Assessing race and ethnicity data quality across cancer registries and EMRs in two hospitals.
abstract: Measurement of patient race/ethnicity in electronic health records is mandated and important for tracking health disparities.
  
  
  
  Characterize the quality of race/ethnicity data collection efforts.
  
  
  
  For all cancer patients diagnosed (2007-2010) at two hospitals, we extracted demographic data from five sources: 1) a university hospital cancer registry, 2) a university electronic medical record (EMR), 3) a community hospital cancer registry, 4) a community EMR, and 5) a joint clinical research registry. The patients whose data we examined (N = 17 834) contributed 41 025 entries (range: 2-5 per patient across sources), and the source comparisons generated 1-10 unique pairs per patient. We used generalized estimating equations, chi-squares tests, and kappas estimates to assess data availability and agreement.
  
  
  
  Compared to sex and insurance status, race/ethnicity information was significantly less likely to be available (χ(2 )> 8043, P < .001), with variation across sources (χ(2 )> 10 589, P < .001). The university EMR had a high prevalence of "Unknown" values. Aggregate kappa estimates across the sources was 0.45 (95% confidence interval, 0.45-0.45; N = 31 276 unique pairs), but improved in sensitivity analyses that excluded the university EMR source (κ = 0.89). Race/ethnicity data were in complete agreement for only 6988 patients (39.2%). Pairs with a "Black" data value in one of the sources had the highest agreement (95.3%), whereas pairs with an "Other" value exhibited the lowest agreement across sources (11.1%).
  
  
  
  Our findings suggest that high-quality race/ethnicity data are attainable. Many of the "errors" in race/ethnicity data are caused by missing or "Unknown" data values.
  
  
  
  To facilitate transparent reporting of healthcare delivery outcomes by race/ethnicity, healthcare systems need to monitor and enforce race/ethnicity data collection standards.
authors.affiliation: Department of Clinical Sciences, University of Texas, Southwestern Medical Center, Dallas, TX, USA Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA simoncraddock.lee@utsouthwestern.edu.
authors.forename: Simon J Craddock
authors.initials: SJ
authors.lastname: Lee
authors.affiliation: Department of Clinical Sciences, University of Texas, Southwestern Medical Center, Dallas, TX, USA.
authors.forename: James E
authors.initials: JE
authors.lastname: Grobe
authors.affiliation: Department of Clinical Sciences, University of Texas, Southwestern Medical Center, Dallas, TX, USA Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA.
authors.forename: Jasmin A
authors.initials: JA
authors.lastname: Tiro
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000068598:Data Accuracy; D057286:Electronic Health Records; D005006:Ethnicity; D005260:Female; D006764:Hospitals, Community; D006785:Hospitals, University; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000208:ethnology*; D044469:Racial Groups; D012042:Registries; D014481:United States; D055815:Young Adult
keywords: cancer registry; data quality; electronic medical record; race and ethnicity