title: Effect of Present-on-Admission (POA) Reporting Accuracy on Hospital Performance Assessments Using Risk-Adjusted Mortality.
abstract: OBJECTIVE
  To evaluate how the accuracy of present-on-admission (POA) reporting affects hospital 30-day acute myocardial infarction (AMI) mortality assessments.
  
  
  METHODS
  A total of 2005 California patient discharge data (PDD) and vital statistics death files.
  
  
  METHODS
  We compared hospital performance rankings using an established model assessing hospital performance for AMI with (1) a model incorporating POA indicators of whether a secondary condition was a comorbidity or a complication of care, and (2) a simulation analysis that factored POA indicator accuracy into the hospital performance assessment. For each simulation, we changed POA indicators for six major acute risk factors of AMI mortality. The probability of POA being changed depended on patient and hospital characteristics.
  
  
  RESULTS
  Comparing the performance rankings of 268 hospitals using the established model with that using the POA indicator, 67 hospitals' (25 percent) rank differed by ≥10 percent. POA reporting inaccuracy due to overreporting and underreporting had little additional impact; POA overreporting contributed to 4 percent of hospitals' difference in rank compared to the POA model and POA underreporting contributed to <1 percent difference.
  
  
  CONCLUSIONS
  Incorporating POA indicators into risk-adjusted models of AMI care has a substantial impact on hospital rankings of performance that is not primarily attributable to inaccuracy in POA hospital reporting.
authors.affiliation: Department of Medicine, San Francisco General Hospital, University of California San Francisco, San Francisco, CA.
authors.forename: L Elizabeth
authors.initials: LE
authors.lastname: Goldman
authors.affiliation: Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, San Francisco, CA.
authors.forename: Philip W
authors.initials: PW
authors.lastname: Chu
authors.affiliation: Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA.
authors.forename: Peter
authors.initials: P
authors.lastname: Bacchetti
authors.affiliation: Department of Medicine, San Francisco General Hospital, University of California San Francisco, San Francisco, CA.
authors.forename: Jenna
authors.initials: J
authors.lastname: Kruger
authors.affiliation: Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, San Francisco, CA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Bindman
mesh_terms: D000328:Adult; D002140:California; D015897:Comorbidity; D003198:Computer Simulation; D005260:Female; D006304:Health Status; D017052:Hospital Mortality; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay; D008297:Male; D009203:Myocardial Infarction / Q000175:diagnosis / Q000628:therapy; D010343:Patient Admission / Q000592:standards* / Q000706:statistics & numerical data*; D010351:Patient Discharge; D019984:Quality Indicators, Health Care / Q000592:standards* / Q000706:statistics & numerical data*; D044469:Racial Groups; D020379:Risk Adjustment; D012307:Risk Factors
keywords: Present-on-admission; hospital assessments; simulation analysis