Abstract
BackgroundClinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE.MethodsAn analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best.Results163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies.ConclusionThe retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies.
Highlights
Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome
The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies
Clinical prediction guides (CPGs), known as clinical prediction rules or clinical decision rules, are increasingly sought by frontline clinicians to assist in their decision making process
Summary
Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. Clinical prediction guides (CPGs), known as clinical prediction rules or clinical decision rules, are increasingly sought by frontline clinicians to assist in their decision making process. They provide an objective standard by which to gauge which elements in a patient's history, physical examination and laboratory tests are the most important in forming an accurate clinical assessment [1]. CPGs can serve as decision aids for determination of causation, diagnosis, prognosis, or patient responsiveness to treatment [1,2,3]. CPG advocates state that, when rigorously created and appropriately applied, CPGs have the potential to influence clinical opinion, change clinical behaviour and increase efficiency while preserving or improving quality patient care and satisfaction [5]
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