A model-driven approach to clinical practice guidelines representation and evaluation using standards.
Clinical Practice Guidelines (CPGs) contain a set of schematic plans for the treatment and management of patients who have a particular clinical condition. CPGs are increasingly being used to support physician decision making. Many groups develop tools for the representation of CPGs. These differ in their approaches to addressing particular modeling challenges. Despite this strong effort, physicians still primarily rely on free-text narrative descriptions. Thus, a core challenge is to develop a formal representation of CPGs that physicians can easily read and verify, yet a machine can process, analyze and apply directly to a patient's EHR data. Our paper proposes a solution to this fundamental problem by describing an approach to CPG formalization using the Natural Rule Language (NRL), coupled with transformation to Object Constraint Language (OCL) constraints that are applied on a patient's clinical data record, in our case an HL7 Continuity of Care Document (CCD). We illustrate our approach on a simple guideline directive for Essential Hypertension.
IBM Haifa Research Lab, Haifa University Campus, Mount Carmel, Haifa, Israel.
Ariel
A
Farkash
John T E
JT
Timm
Zeev
Z
Waks
D000465:Algorithms; D020000:Decision Support Systems, Clinical / Q000592:standards*; D008962:Models, Theoretical; D009323:Natural Language Processing; D017410:Practice Guidelines as Topic; D011785:Quality Assurance, Health Care / Q000592:standards*; D012015:Reference Standards; D012984:Software; D009626:Terminology as Topic