title: The accuracy of present-on-admission reporting in administrative data.
abstract: OBJECTIVE
  To test the accuracy of reporting present-on-admission (POA) and to assess whether POA reporting accuracy differs by hospital characteristics.
  
  
  METHODS
  We performed an audit of POA reporting of secondary diagnoses in 1,059 medical records from 48 California hospitals.
  
  
  METHODS
  We used patient discharge data (PDD) to select records with secondary diagnoses that are powerful predictors of mortality and could potentially represent comorbidities or complications among patients who either had a primary procedure of a percutaneous transluminal coronary angioplasty or a primary diagnosis of acute myocardial infarction, community-acquired pneumonia, or congestive heart failure. We modeled the relationship between secondary diagnoses POA reporting accuracy (over-reporting and under-reporting) and hospital characteristics.
  
  
  METHODS
  We created a gold standard from blind reabstraction of the medical records and compared the accuracy of the PDD against the gold standard.
  
  
  RESULTS
  The PDD and gold standard agreed on POA reporting in 74.3 percent of records, with 13.7 percent over-reporting and 11.9 percent under-reporting. For-profit hospitals tended to overcode secondary diagnoses as present on admission (odds ratios [OR] 1.96; 95 percent confidence interval [CI] 1.11, 3.44), whereas teaching hospitals tended to undercode secondary diagnoses as present on admission (OR 2.61; 95 percent CI 1.36, 5.03).
  
  
  CONCLUSIONS
  POA reporting of secondary diagnoses is moderately accurate but varies by hospitals. Steps should be taken to improve POA reporting accuracy before using POA in hospital assessments tied to payments.
authors.affiliation: Department of Medicine, University of California-San Francisco, San Francisco, CA 94110, USA. legoldman@medsfgh.ucsf.edu
authors.forename: L Elizabeth
authors.initials: LE
authors.lastname: Goldman
authors.forename: Philip W
authors.initials: PW
authors.lastname: Chu
authors.forename: Dennis
authors.initials: D
authors.lastname: Osmond
authors.forename: Andrew
authors.initials: A
authors.lastname: Bindman
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002140:California; D003266:Continuity of Patient Care / Q000706:statistics & numerical data; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D008487:Medical History Taking / Q000706:statistics & numerical data*; D008875:Middle Aged; D010343:Patient Admission; D010351:Patient Discharge; D020379:Risk Adjustment / Q000379:methods
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