How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines.
BACKGROUND
Clinical practice guidelines give recommendations about what to do in various medical situations, including therapeutical recommendations for drug prescription. An effective way to computerize these recommendations is to design critiquing decision support systems, i.e. systems that criticize the physician's prescription when it does not conform to the guidelines. These systems are commonly based on a list of "if conditions then criticism" rules. However, writing these rules from the guidelines is not a trivial task. The objective of this article is to propose methods that (1) simplify the implementation of guidelines' therapeutical recommendations in critiquing systems by automatically translating structured therapeutical recommendations into a list of "if conditions then criticize" rules, and (2) can generate an appropriate textual label to explain to the physician why his/her prescription is not recommended.


METHODS
We worked on the therapeutic recommendations in five clinical practice guidelines concerning chronic diseases related to the management of cardiovascular risk. We evaluated the system using a test base of more than 2000 cases.


RESULTS
Algorithms for automatically translating therapeutical recommendations into "if conditions then criticize" rules are presented. Eight generic recommendations are also proposed; they are guideline-independent, and can be used as default behaviour for handling various situations that are usually implicit in the guidelines, such as decreasing the dose of a poorly tolerated drug. Finally, we provide models and methods for generating a human-readable textual critique. The system was successfully evaluated on the test base.


CONCLUSIONS
We show that it is possible to criticize physicians' prescriptions starting from a structured clinical guideline, and to provide clear explanations. We are now planning a randomized clinical trial to evaluate the impact of the system on practices.
Laboratoire d'Informatique Médicale et de Bioinformatique (LIM&BIO), UFR SMBH, University of Paris 13, 74 rue Marcel Cachin, 93017 Bobigny cedex, France. jibalamy@free.fr
Jean-Baptiste
JB
Lamy
Vahid
V
Ebrahiminia
Christine
C
Riou
Brigitte
B
Seroussi
Jacques
J
Bouaud
Christian
C
Simon
Stéphane
S
Dubois
Antoine
A
Butti
Gérard
G
Simon
Madeleine
M
Favre
Hector
H
Falcoff
Alain
A
Venot
D000465:Algorithms; D002908:Chronic Disease / Q000628:therapy; D011307:Drug Prescriptions; D004358:Drug Therapy / Q000592:standards*; D006801:Humans; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians'; D057170:Translational Research, Biomedical