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Differential diagnosis generators: an evaluation of currently available computer programs.

William F Bond¹, Linda M Schwartz, Kevin R Weaver

¹Department of Emergency Medicine, Lehigh Valley Health Network, Allentown, PA, USA. william.bond@lvhn.org

Journal of General Internal Medicine

|July 27, 2011

Summary

Differential diagnosis (DDX) generators aid clinicians by providing diagnostic suggestions. DxPlain® and Isabel© demonstrated superior performance in a recent evaluation of these tools.

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Area of Science:

Medical Informatics
Clinical Decision Support Systems
Artificial Intelligence in Medicine

Background:

Differential diagnosis (DDX) generators are computational tools designed to assist clinicians in identifying potential diagnoses based on patient data.
Evaluating the performance and features of these DDX generators is crucial for optimizing their utility in clinical practice.

Purpose of the Study:

To establish consensus-based criteria for evaluating differential diagnosis (DDX) generators.
To assess the features and performance of available DDX generators using standardized criteria and clinical case studies.

Main Methods:

Identified evaluation criteria through expert consensus.
Conducted systematic literature searches to identify relevant DDX generators.
Applied inclusion criteria: list generation, diagnosis ranking, minimum input requirements, comparative functionality, and general medicine scope.
Evaluated four selected DDX generators based on criteria including input method, mobile access, filtering, data integration (labs, meds, geography), EBM content, and references.
Tested performance using 20 clinical cases from NEJM and MKSAP, scoring accuracy on a five-point scale.

Main Results:

Four differential diagnosis (DDX) generators met the inclusion criteria from an initial pool of twenty-three.
Performance testing revealed mean scores: Isabel© (3.45), DxPlain® (3.45), Diagnosis Pro® (2.65), and PEPID™ (1.70).
Higher mean scores correlated with a greater number of exact diagnostic matches.

Conclusions:

Developed and applied consensus criteria for evaluating differential diagnosis (DDX) generators.
DxPlain® and Isabel© emerged as the top-performing DDX generators based on the evaluation criteria and performance testing.
The study supports the use of DxPlain® and Isabel© over other evaluated DDX generators for clinical decision support.