Comparing computer-interpretable guideline models: a case-study approach.
OBJECTIVE
Many groups are developing computer-interpretable clinical guidelines (CIGs) for use during clinical encounters. CIGs use "Task-Network Models" for representation but differ in their approaches to addressing particular modeling challenges. We have studied similarities and differences between CIGs in order to identify issues that must be resolved before a consensus on a set of common components can be developed.


METHODS
We compared six models: Asbru, EON, GLIF, GUIDE, PRODIGY, and PROforma. Collaborators from groups that created these models represented, in their own formalisms, portions of two guidelines: American College of Chest Physicians cough guidelines [correction] and the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.


METHODS
We compared the models according to eight components that capture the structure of CIGs. The components enable modelers to encode guidelines as plans that organize decision and action tasks in networks. They also enable the encoded guidelines to be linked with patient data-a key requirement for enabling patient-specific decision support.


RESULTS
We found consensus on many components, including plan organization, expression language, conceptual medical record model, medical concept model, and data abstractions. Differences were most apparent in underlying decision models, goal representation, use of scenarios, and structured medical actions.


CONCLUSIONS
We identified guideline components that the CIG community could adopt as standards. Some of the participants are pursuing standardization of these components under the auspices of HL7.
Peleg
Mor
M
Stanford Medical Informatics, Stanford University School of Medicine, Stanford, California 94305-5479, USA. peleg@smi.stanford.edu
Tu
Samson
S
Bury
Jonathan
J
Ciccarese
Paolo
P
Fox
John
J
Greenes
Robert A
RA
Hall
Richard
R
Johnson
Peter D
PD
Jones
Neill
N
Kumar
Anand
A
Miksch
Silvia
S
Quaglini
Silvana
S
Seyfang
Andreas
A
Shortliffe
Edward H
EH
Stefanelli
Mario
M
D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D006801:Humans; D017410:Practice Guidelines as Topic; D011381:Programming Languages; D012984:Software