title: Evaluating acute medical admissions through emergency departments in Hong Kong: can one adjust for case-mix variation?
abstract: BACKGROUND
  Healthcare systems are under pressure to efficiently and safely reduce acute care admissions to hospital. There is a need to develop a standardised system for assessing emergency department performance which takes into account case-mix variation. The objective of this study was to derive and validate a standardised tool for assessing variations in medical admissions through emergency departments in Hong Kong.
  
  
  METHODS
  Retrospective study of patients attending emergency departments of 14 acute hospitals in Hong Kong. Data were retrieved from a centralised administrative database.
  
  
  RESULTS
  Of 2,531,225 patients who attended emergency departments between 1 January 2001 and 31 December 2003, 780,444 (30.8%) were admitted to medical wards. A model derived from 2001 data shows well-calibrated admission probabilities, with an area under the receiver operating characteristic curve for probability of admission of 90.3 (95% CI ±0.11). The areas under the receiver operating characteristic curves for 2002 and 2003 validation sets were 89.9 (95% CI ±0.11) and 89.0 (95% CI ±0.12), respectively. With an averaged benchmark, reductions in medical admissions of up to 19% could be achieved, while under the most optimistic assumption, reductions of up 36% could be achieved.
  
  
  CONCLUSIONS
  A tool for benchmarking hospital medical admissions and minimising case-mix variation has been derived and validated in Hong Kong, but it requires further validation in other healthcare systems given the wide variations in admission thresholds internationally. This may be used as one potential method to evaluate the performance of emergency departments against a common standard.
authors.affiliation: Accident and Emergency Academic Unit, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong. thrainer@cuhk.edu.hk
authors.forename: T H
authors.initials: TH
authors.lastname: Rainer
authors.forename: P
authors.initials: P
authors.lastname: Sollich
authors.forename: T
authors.initials: T
authors.lastname: Piotrowski
authors.forename: A C C
authors.initials: AC
authors.lastname: Coolen
authors.forename: B
authors.initials: B
authors.lastname: Cheng
authors.forename: C A
authors.initials: CA
authors.lastname: Graham
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019985:Benchmarking; D004636:Emergency Service, Hospital / Q000592:standards* / Q000706:statistics & numerical data; D005260:Female; D006723:Hong Kong; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D020379:Risk Adjustment; D014218:Triage / Q000592:standards*; D055815:Young Adult