title: Simplification of a scoring system maintained overall accuracy but decreased the proportion classified as low risk.
abstract: OBJECTIVE
  Scoring systems are developed to assist clinicians in making a diagnosis. However, their uptake is often limited because they are cumbersome to use, requiring information on many predictors, or complicated calculations. We examined whether, and how, simplifications affected the performance of a validated score for identifying adults with chest pain in an emergency department who have low risk of major adverse cardiac events.
  
  
  METHODS
  We simplified the Emergency Department Assessment of Chest pain Score (EDACS) by three methods: (1) giving equal weight to each predictor included in the score, (2) reducing the number of predictors, and (3) using both methods--giving equal weight to a reduced number of predictors. The diagnostic accuracy of the simplified scores was compared with the original score in the derivation (n = 1,974) and validation (n = 909) data sets.
  
  
  RESULTS
  There was no difference in the overall accuracy of the simplified versions of the score compared with the original EDACS as measured by the area under the receiver operating characteristic curve (0.74 to 0.75 for simplified versions vs. 0.75 for the original score in the validation cohort). With score cut-offs set to maintain the sensitivity of the combination of score and tests (electrocardiogram and cardiac troponin) at a level acceptable to clinicians (99%), simplification reduced the proportion of patients classified as low risk from 50% with the original score to between 22% and 42%.
  
  
  CONCLUSIONS
  Simplification of a clinical score resulted in similar overall accuracy but reduced the proportion classified as low risk and therefore eligible for early discharge compared with the original score. Whether the trade-off is acceptable, will depend on the context in which the score is to be used. Developers of clinical scores should consider simplification as a method to increase uptake, but further studies are needed to determine the best methods of deriving and evaluating simplified scores.
authors.affiliation: The Centre for Research in Evidence-Based Practice, Faculty of Health Sciences & Medicine, Bond University, University Drive, Gold Coast 4226, Australia. Electronic address: ssanders@bond.edu.au.
authors.forename: Sharon
authors.initials: S
authors.lastname: Sanders
authors.affiliation: Royal Brisbane and Women's Hospital, Butterfield Street, Herston 4029, Queensland, Australia.
authors.forename: Dylan
authors.initials: D
authors.lastname: Flaws
authors.affiliation: Emergency Department, Christchurch Hospital, Riccarton Ave, Christchurch, New Zealand.
authors.forename: Martin
authors.initials: M
authors.lastname: Than
authors.affiliation: Emergency Department, Christchurch Hospital and University of Otago Christchurch, Christchurch, New Zealand.
authors.forename: John W
authors.initials: JW
authors.lastname: Pickering
authors.affiliation: The Centre for Research in Evidence-Based Practice, Faculty of Health Sciences & Medicine, Bond University, University Drive, Gold Coast 4226, Australia.
authors.forename: Jenny
authors.initials: J
authors.lastname: Doust
authors.affiliation: The Centre for Research in Evidence-Based Practice, Faculty of Health Sciences & Medicine, Bond University, University Drive, Gold Coast 4226, Australia.
authors.forename: Paul
authors.initials: P
authors.lastname: Glasziou
mesh_terms: D054058:Acute Coronary Syndrome / Q000175:diagnosis*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002637:Chest Pain / Q000175:diagnosis; D004636:Emergency Service, Hospital; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000706:statistics & numerical data; D055815:Young Adult
keywords: Acute coronary syndrome; Clinical prediction rules; Decision support techniques; Diagnosis; Scoring systems; Work simplification