Variance and Dissent
The comprehensive diagnostic study is suggested as a design to model the diagnostic process

https://doi.org/10.1016/j.jclinepi.2013.05.019Get rights and content
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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.

Keywords

Diagnosis
Chest pain
Primary health care
Decision support techniques
Information theory
Research design

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Conflict of interest: None.