title: Clinicians required very high sensitivity of a bacteremia prediction rule.
abstract: OBJECTIVE
  Efforts to improve blood culture practice have focused on developing clinical prediction rules to identify patients at risk for bacteremia. However, no such models have been accepted into general clinical use. The goal of this study was to determine physicians' criteria for acceptability of a bacteremia clinical prediction rule.
  
  
  METHODS
  We conducted a survey of all medical and surgical house officers as well as all infectious diseases physicians at the University of Pennsylvania to identify physician requirements for the sensitivity of a bacteremia clinical prediction rule.
  
  
  RESULTS
  Of 225 eligible physicians, 149 (66.2%) completed the survey, including 110 house officers and 39 infectious disease physicians. The median (95% confidence interval) sensitivity of a bacteremia prediction rule required by respondents was 95% (95% confidence interval, 95.9%). Furthermore, 29 (19.5%) respondents required the sensitivity of a prediction rule to be at least 99%. The median required sensitivity was significantly higher for infectious diseases physicians than for house officers (98% and 95%, respectively) (P=.04).
  
  
  CONCLUSIONS
  Our survey of house staff and infectious diseases physicians demonstrates that the sensitivity of any bacteremia prediction rule must be extremely high (i.e., 99% to 100%) to be widely accepted by practicing clinicians. Elucidation of physician criteria for acceptability of clinical predictive models will be invaluable in future efforts to develop such prediction rules.
authors.affiliation: Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6021, USA. elautenb@cceg.med.upenn.edu
authors.forename: Ebbing
authors.initials: E
authors.lastname: Lautenbach
authors.forename: Russell
authors.initials: R
authors.lastname: Localio
authors.forename: Irving
authors.initials: I
authors.lastname: Nachamkin
mesh_terms: D001291:Attitude of Health Personnel; D016470:Bacteremia / Q000175:diagnosis*; D015510:Clinical Medicine; D016001:Confidence Intervals; D003663:Decision Trees; D005260:Female; D006801:Humans; D008297:Male; D008505:Medical Staff, Hospital; D010820:Physicians; D011379:Prognosis; D012680:Sensitivity and Specificity