Development and verification of a hypertension guideline encoding model.
For encoding sharable and interoperable guideline knowledge for hypertension management, standard guidelines including JNC7 were chosen. The knowledge modeling process consisted of defining scenarios for describing workflow and identifying knowledge logics. Evaluation of the encoding model was conducted by scenario-based testing. Two experts inverted exclamation mark recommendations were compared with those inferred from the encoding model. The agreement level ranged from 77% to 100%.
Kim
Ji Hyun
JH
Center for Interoperable EHR, Seoul, Korea.
Cho
In Sook
IS
Lee
Jae Hyun
JH
Shim
Dong Hyun
DH
Kim
Hyun Young
HY
Kim
Yoon
Y
D000465:Algorithms; D001185:Artificial Intelligence; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D006973:Hypertension / Q000145:classification*; D016247:Information Storage and Retrieval / Q000379:methods; D007723:Korea; D016347:Medical Records Systems, Computerized / Q000592:standards*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D017410:Practice Guidelines as Topic; D009626:Terminology as Topic