title: The incidence and cost of adverse events in Victorian hospitals 2003-04.
abstract: OBJECTIVE
  To determine the incidence of adverse events in patients admitted in the year 2003-04 to selected Victorian hospitals; to identify the main hospital-acquired diagnoses; and to estimate the cost of these complications to the Victorian and Australian health system.
  
  
  METHODS
  The patient-level costing dataset for major Victorian public hospitals, 1 July 2003-30 June 2004, was analysed for adverse events by identifying C-prefixed diagnosis codes denoting complications, preventable or otherwise, arising during the course of hospital treatment. The in-hospital cost of adverse events was estimated using linear regression modelling, adjusting for age and comorbidity.
  
  
  METHODS
  Cost of each patient admission ("admitted episode"), length of stay and mortality.
  
  
  RESULTS
  During the designated timeframe, 979,834 admitted episodes were in the sample, of which 67,435 (6.88%) had at least one adverse event. Patients with adverse events stayed about 10 days longer and had over seven times the risk of in-hospital death than those without complications. After adjusting for age and comorbidity, the presence of an adverse event adds dollar 6826 to the cost of each admitted episode. The total cost of adverse events in this dataset in 2003-04 was dollar 460.311 million, representing 15.7% of the total expenditure on direct hospital costs, or an additional 18.6% of the total inpatient hospital budget.
  
  
  CONCLUSIONS
  Adverse events are associated with significant costs. Administrative datasets are a cost-effective source of information that can be used for a range of clinical governance activities to prevent adverse events.
authors.affiliation: Department of Human Services, Melbourne, VIC.
authors.forename: Jonathon P
authors.initials: JP
authors.lastname: Ehsani
authors.forename: Terri
authors.initials: T
authors.lastname: Jackson
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Duckett
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D002648:Child; D002675:Child, Preschool; D003953:Diagnosis-Related Groups; D017721:Hospital Costs / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data; D016014:Linear Models; D019300:Medical Errors / Q000191:economics* / Q000706:statistics & numerical data*; D008875:Middle Aged; D012308:Risk Management