title: The mismeasurement of quality by readmission rate: how blunt is too blunt an instrument?: a quantitative bias analysis.
abstract: BACKGROUND
  The rate of readmission is widely used as a measure of hospital quality of care, often with funding implications for outlying facilities.
  
  
  OBJECTIVE
  This study explored the plausibility of readmission as a proxy for health care quality with quantitative bias analysis and the application of a structural Directed Acyclic Graph framework. It applies this paradigm to observed ethnic differences in the odds of readmission in a sample of New Zealand hospital patients.
  
  
  METHODS
  Ethnicity was defined as the exposure, readmission rate as the proxy outcome, and quality of care as a missing mediator. Using data from 89,090 surgical patients from New Zealand, and estimates from the literature of the prevalence of "poor quality" and the strength of the quality-of-care readmission association, a series of sensitivity analyses were performed to calculate an odds ratio of the ethnicity-readmission association corrected for the missing mediator "quality."
  
  
  RESULTS
  Given the assumptions applied, potentially only 29% of the excess odds of readmission for Māori compared with Europeans were due to poor quality of care.
  
  
  CONCLUSIONS
  This investigation finds substantial error when using readmission as a marker of quality, and suggests that differences in readmission between populations are more likely to be due to factors other than quality of care.
authors.affiliation: Institute for Health and Social Policy, University of McGill, Montreal, QC, Canada.
authors.forename: Juliet
authors.initials: J
authors.lastname: Rumball-Smith
authors.forename: Tony
authors.initials: T
authors.lastname: Blakely
authors.forename: Diana
authors.initials: D
authors.lastname: Sarfati
authors.forename: Phil
authors.initials: P
authors.lastname: Hider
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015897:Comorbidity; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D006302:Health Services Research; D006801:Humans; D008297:Male; D008875:Middle Aged; D009520:New Zealand / Q000208:ethnology; D010359:Patient Readmission / Q000706:statistics & numerical data*; D019984:Quality Indicators, Health Care; D012107:Research Design; D012923:Social Class; D013997:Time Factors