Modeling uncertainty in computerized guidelines using fuzzy logic.
Proc AMIA Symp
; : 284-8, 2001.
Article
in En
| MEDLINE
| ID: mdl-11825196
ABSTRACT
Computerized Clinical Practice Guidelines (CPGs) improve quality of care by assisting physicians in their decision making. A number of problems emerges since patients with close characteristics are given contradictory recommendations. In this article, we propose to use fuzzy logic to model uncertainty due to the use of thresholds in CPGs. A fuzzy classification procedure has been developed that provides for each message of the CPG, a strength of recommendation that rates the appropriateness of the recommendation for the patient under consideration. This work is done in the context of a CPG for the diagnosis and the management of hypertension, published in 1997 by the French agency ANAES. A population of 82 patients with mild to moderate hypertension was selected and the results of the classification system were compared to whose given by a classical decision tree. Observed agreement is 86.6% and the variability of recommendations for patients with close characteristics is reduced.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Decision Making, Computer-Assisted
/
Practice Guidelines as Topic
/
Fuzzy Logic
/
Hypertension
Type of study:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Proc AMIA Symp
Year:
2001
Document type:
Article