Two related problems hinder the knowledge translation process and the practice of evidence-based medicine. First, patients are complex and often do not conform to the “average” patient constructed from the myriad research studies upon which it is based. Second, in addition to the research findings that might be brought to bear on decisions, clinical experience and judgment, patient values, and considerations beyond what research evidence suggests also represent important influences. This paper explores how the “problem knowledge coupling” (PKC®) approach can overcome these difficulties. The approach divides decision making into two stages. The first uses computers to guide the collection of patient data and to “couple” detailed patient findings with various guidance options to present a range of alternative avenues to pursue. Stage two uses human judgment and patient values to determine which alternative offers the most suitable course of action. The paper concludes by exploring the implications of the PKC approach for knowledge translation.
|Keywords:||Knowledge translation, Evidence-based medicine, Clinical guidelines, Patient complexity, Clinical decision making, Computerized decision support, Problem-Knowledge Coupling|
Professor, Health Sciences, University of Ontario Institute of Technology, Oshawa, Ontario, Canada
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