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Methods Used to Compare Narrative Clinical Practice Guidelines: A Scoping Review.
Mohammadreza Azarpira1, Akram Redjdal1, Jacques Bouaud2,1
1Sorbonne Université, Université Sorbonne Paris Nord, INSERM, Laboratoire d'Informatique Médicale et d'Ingénierie des connaissances en e-Santé, LIMICS, F-75006 Paris, France.
Studies in Health Technology and Informatics
|July 1, 2022
Summary
Regularly updating clinical practice guidelines (CPGs) is crucial for clinical decision support systems (CDSSs). This review evaluates methods for comparing CPGs, highlighting the role of expert knowledge in ensuring accuracy.
Area of Science:
- Health Informatics
- Medical Informatics
- Evidence-Based Medicine
Background:
- Clinical decision support systems (CDSSs) require up-to-date clinical practice guidelines (CPGs) for optimal performance.
- The frequent renewal of international CPGs necessitates efficient methods for updating national guidelines and ensuring alignment with the latest evidence.
Purpose of the Study:
- To conduct a scoping review evaluating existing methods for comparing two clinical practice guidelines.
- To identify and assess techniques for extracting CPG components and comparing guidelines at various levels of abstraction.
Main Methods:
- A comprehensive search for methods used in comparing CPGs was performed.
- The review considered both computerized and semi-computerized approaches for CPG comparison and component extraction.
- Scoping review methodology was employed to synthesize findings.
Main Results:
- Various methods for extracting CPG components and comparing guidelines were identified.
- Both automated and semi-automated techniques were recognized as viable approaches.
- Expert knowledge remains essential for evaluating comparisons, particularly for semantic rule extraction and inconsistency resolution.
Conclusions:
- Computerized comparison of clinical guidelines offers an effective solution for managing the growing volume of medical data and CPGs.
- While automated methods show promise, expert judgment is indispensable for validating comparisons and addressing complex issues like semantic inconsistencies.
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