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The comprehensive diagnostic study is suggested as a design to model the diagnostic process.

Abstract：

OBJECTIVES: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. STUDY DESIGN AND SETTING: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. CONCLUSION: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.

journal_name

J Clin Epidemiol

journal_title

Journal of clinical epidemiology

authors

Donner-Banzhoff N,Haasenritter J,Hüllermeier E,Viniol A,Bösner S,Becker A

doi

10.1016/j.jclinepi.2013.05.019

subject

Has Abstract

pub_date

2014-02-01 00:00:00

pages

124-32

issue

2

eissn

0895-4356

issn

1878-5921

pii

S0895-4356(13)00385-5

journal_volume

67

pub_type

杂志文章

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