title: Variation in practice for discretionary admissions. Impact on estimates of quality of hospital care.
abstract: OBJECTIVE
  To demonstrate theoretically and empirically the existence of systematic bias in commonly reported standardized hospital mortality ratios when variation in hospital admission practice is not adjusted for in the analysis. The underlying analytic model used in hospital mortality analyses is specified and the confounding effect of selection bias arising from variation in admission practice is shown.
  
  
  METHODS
  An empirical example is presented using state-level data from the Health Care Financing Administration's Medicare Hospital Information Report for 1988 to 1990.
  
  
  METHODS
  The Medicare Hospital Information data are used to demonstrate the effects of the bias because they contain population-based admission rates and mortality rates.
  
  
  RESULTS
  Selection bias arising from variation in admission practice causes the expected mortality rate to be overestimated for all hospitals, but especially for hospitals with more lenient admission practices. Using the Medicare Hospital Information Report, the resulting standardized hospital mortality ratios are shown to be significantly inversely correlated with higher relative risks of hospitalization (P < .01).
  
  
  CONCLUSIONS
  Standardized hospital mortality ratios based on analyses that do not account for variation in admission practice among hospitals are biased. Variation in admission practice will cause any outcome measure based solely on hospitalized patients to be similarly biased. Correction for selection bias is required to produce valid measures of hospital quality.
authors.affiliation: Department of Quality and Utilization, Kaiser Permanente Medical Care Program, Oakland, CA 94612.
authors.forename: M G
authors.initials: MG
authors.lastname: Miller
authors.forename: L S
authors.initials: LS
authors.lastname: Miller
authors.forename: B
authors.initials: B
authors.lastname: Fireman
authors.forename: S B
authors.initials: SB
authors.lastname: Black
mesh_terms: D015982:Bias; D014487:Centers for Medicare and Medicaid Services, U.S.; D005251:Fees, Medical; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D017052:Hospital Mortality; D006801:Humans; D006278:Medicare; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000592:standards* / Q000706:statistics & numerical data; D010343:Patient Admission / Q000592:standards / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology