Characterizing the dimensions of clinical practice guideline evolution.
The ever growing pace at which medical knowledge is produced requires clinical practice guidelines (CPGs) to be regularly updated. Since clinical decision support systems (CDSSs) are effective means to implement guidelines in routine care, they have to be revised as their knowledge sources evolve. From one version to another, some parts are kept unchanged whereas others are more or less modified. We propose to characterize formally the different dimensions of recommendation evolution in two successive guideline versions from the knowledge modelling perspective. Each atomic recommendation is represented as a rule connecting a clinical condition to recommended action plans. Using subsumption-based comparisons, seven evolution patterns were identified: No change, Action plan refinement, New action plan, Condition refinement, Recommendation refinement, New practice, and Unmatched recommendation. The method has been evaluated on French bladder cancer guidelines in the revisions of 2002 and 2004.
Bouaud
Jacques
J
AP-HP, DSI, STIM, Paris, France.
Séroussi
Brigitte
B
D000465:Algorithms; D020000:Decision Support Systems, Clinical; D005602:France; D006801:Humans; D051188:Knowledge Bases; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D009369:Neoplasms / Q000175:diagnosis / Q000628:therapy*; D017410:Practice Guidelines as Topic; D012984:Software; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis / Q000628:therapy