Research paper - Searching for clinical prediction rules in MEDLINE

Objectives: Clinical prediction rules have been advocated as a possible mec hanism to enhance clinical judgment in diagnostic, therapeutic, and prognos tic assessment. Despite renewed interest in the their use, inconsistent ter minology makes them difficult to index and retrieve by computerized search systems. No validated approaches to locating clinical prediction rules appe ar in the literature. The objective of this study was to derive and validat e an optimal search filter for retrieving clinical prediction rules, using the National Library of Medicine's MEDLINE database. Design: A comparative, retrospective analysis was conducted. The "gold stan dard" was established by a manual search of all articles from select print journals for the years 1991 through 1998, which identified articles coverin g various aspects of clinical prediction rules such as derivation, validati on, and evaluation. Search filters were derived, from the articles in the J uly through December issues of the journals (derivation set), by analyzing the textwords (words in the title and abstract) and the medical subject hea ding (from the MeSH Thesaurus) used to index, each article. The accuracy of these filters in retrieving clinical prediction rules was then assessed us ing articles in the January through June issues (validation set). Measurements: The sensitivity, specificity, positive predictive value, and positive likelihood ratio of several different search filters were measured . Results: The filter "predict$ OR clinical$ OR outcome$ OR risk$" retrieve d 98 percent of clinical prediction rules. Four filters, such as "predict$ OR validat$ OR rule$ OR predictive value of tests," had both sensitivity an d specificity above 90 percent. The top-performing filter for positive pred ictive value and positive likelihood ratio in the validation set was "predi ct$.ti. AND rule$." Conclusions: Several filters with high retrieval value were found. Dependin g on the goals and time constraints of the searcher, one of these filters c ould be used.