Augmenting GEM-encoded clinical practice guidelines with relevant best evidence autonomously retrieved from MEDLINE

Abstract

Clinical practice guidelines (CPG) are instrumental in standardizing the quality and delivery of care across different practitioners, departments and institutions. Health practitioners will use current best evidence to validate or supplement their understanding of CPG. This study investigates the potential of supplementing computerized CPG with relevant best evidence sourced from reliable medical literature repositories. A web-enabled Best-evidence Retrieval and Delivery (BiRD) system facilitates autonomous retrieval of pertinent medical literature with respect to user-specified content from a GEM-encoded CPG. A multilevel literature search strategy categorizes the search towards predefined clinical query intentions, and subsequently filters insignificant medical terms. The resultant is a highly focused medical literature search query that is objectively derived from CPG content. The technical architecture comprises existing medical language processing tools and vocabularies, together with newly developed tools to automatically generate optimum search queries, retrieve medical articles from MEDLINE, and embed the articles within XML-based CPG.