Evaluation of a commercial rule engine as a basis for a clinical decision support service.
Current implementation techniques constrain our ability to rapidly deploy and augment clinical decision support systems at Partners Healthcare Systems. We report on the use of a commercially-available rule engine system-iLog Rules-as the basis for a series of prototypes typifying Partners decision support applications. For three prototypical systems, we successfully decoupled the decision support component from application and support logic, and reimplemented that component using iLog. We found that the rule engine itself provides high-performance execution for the small rulesets we evaluated, and that overall application performance was found to be generally acceptable. We note that the major bottleneck to application performance is the ability to rapidly deliver patient data to the rule engine for execution. Future investigation will focus on abstracting features from each of the prototypes and incorporating them into a scalable and reusable decision support service architecture.
Goldberg
Howard S
HS
Clinical Informatics Research and Development, Partners Healthcare System, Wellesley, USA.
Vashevko
Michael
M
Pastilnik
Anatoly
A
Smith
Kevin
K
Plaks
Nina
N
Blumenfeld
Barry M
BM
D019985:Benchmarking; D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D009323:Natural Language Processing; D010865:Pilot Projects; D012984:Software