Computerization framework for clinical practice guidelines by extending the XML guidelines element model (GEM).
Contextually sensitive and semantically related evidence-based knowledge play an important role in decision-making. Clinical practice guidelines (CPG) are being developed to provide a rich source of up-to-date knowledge of evidence-based best clinical practices. Such knowledge assists healthcare practitioner in specific clinical circumstances at their decision-points. In many studies, it was shown that the effectiveness of CPG could be improved with their computerization. In this paper, we present our CPG-knowledge computerization framework that has been developed and implemented along the lines of knowledge management approaches. This framework adds context, semantics and related meta-information to the CPGs knowledge content using an extended-knowledge component ontology and UMLS. It also transforms them into a set of structured 'extended-knowledge components'. These extended-knowledge components constitute a 'CPG knowledge base', which is used for providing assistance at point of care.
Hashmi
Zafar
Z
Center of Health Informatics, University New South Wales, Sydney, NSW 2052, Australia. zafarh@cse.unsw.edu.au
Zrimec
Tatjana
T
Hopkins
Andrew
A
D001331:Automation; D008962:Models, Theoretical; D017410:Practice Guidelines as Topic; D011381:Programming Languages; D017432:Unified Medical Language System