title: The comprehensive diagnostic study is suggested as a design to model the diagnostic process.
abstract: OBJECTIVE
  The classical diagnostic cross-sectional study has a focus on one disease only. Generalist clinicians, however, are confronted with a wide range of diagnoses. We propose the "comprehensive diagnostic study design" to evaluate diagnostic tests regarding more than one disease outcome.
  
  
  METHODS
  We present the secondary analysis of a data set obtained from patients presenting with chest pain in primary care. Participating clinicians recorded 42 items of the history and physical examination. Diagnostic outcomes were reviewed by an independent panel after 6-month follow-up (n = 710 complete cases). We used Shannon entropy as a measure of uncertainty before and after testing. Four different analytical strategies modeling specific clinical ways of reasoning were evaluated.
  
  
  RESULTS
  Although the "global entropy" strategy reduced entropy most, it is unlikely to be of clinical use because of its complexity. "Inductive" and "fixed-set" strategies turned out to be efficient requiring a small amount of data only. The "deductive" procedure resulted in the smallest reduction of entropy.
  
  
  CONCLUSIONS
  We suggest that the comprehensive diagnostic study design is a feasible and valid option to improve our understanding of the diagnostic process. It is also promising as a justification for clinical recommendations.
authors.affiliation: Department of General Practice/Family Medicine, University of Marburg, Karl-von-Frisch Str. 4, D-35043 Marburg, Germany. Electronic address: Norbert@staff.uni-marburg.de.
authors.forename: Norbert
authors.initials: N
authors.lastname: Donner-Banzhoff
authors.affiliation: Department of General Practice/Family Medicine, University of Marburg, Karl-von-Frisch Str. 4, D-35043 Marburg, Germany.
authors.forename: Jörg
authors.initials: J
authors.lastname: Haasenritter
authors.affiliation: Department of Knowledge Engineering & Bioinformatics, University of Marburg, D-35043 Marburg, Germany.
authors.forename: Eyke
authors.initials: E
authors.lastname: Hüllermeier
authors.affiliation: Department of General Practice/Family Medicine, University of Marburg, Karl-von-Frisch Str. 4, D-35043 Marburg, Germany.
authors.forename: Annika
authors.initials: A
authors.lastname: Viniol
authors.affiliation: Department of General Practice/Family Medicine, University of Marburg, Karl-von-Frisch Str. 4, D-35043 Marburg, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Bösner
authors.affiliation: Department of General Practice/Family Medicine, University of Marburg, Karl-von-Frisch Str. 4, D-35043 Marburg, Germany.
authors.forename: Annette
authors.initials: A
authors.lastname: Becker
mesh_terms: D002637:Chest Pain / Q000175:diagnosis; D003430:Cross-Sectional Studies; D020000:Decision Support Systems, Clinical; D003955:Diagnostic Tests, Routine / Q000379:methods* / Q000592:standards*; D006801:Humans; D010808:Physical Examination; D011320:Primary Health Care / Q000379:methods; D035501:Uncertainty
keywords: Chest pain; Decision support techniques; Diagnosis; Information theory; Primary health care; Research design