Developing optimal search strategies for detecting clinically sound studies in MEDLINE.
OBJECTIVE
To develop optimal MEDLINE search strategies for retrieving sound clinical studies of the etiology, prognosis, diagnosis, prevention, or treatment of disorders in adult general medicine.


METHODS
Analytic survey of operating characteristics of search strategies developed by computerized combinations of terms selected to detect studies meeting basic methodologic criteria for direct clinical use in adult general medicine.


METHODS
The sensitivities, specificities, precision, and accuracy of 134,264 unique combinations of search terms were determined by comparison with a manual review of all articles (the "gold standard") in ten internal medicine and general medicine journals for 1986 and 1991.


RESULTS
Less than half of the studies of the topics of interest met basic criteria for scientific merit for testing clinical applications. Combinations of search terms reached peak sensitivities of 82% for sound studies of etiology, 92% for prognosis, 92% for diagnosis, and 99% for therapy in 1991. Compared with the best single terms, multiple terms increased sensitivity for sound studies by over 30% (absolute increase), but with some loss of specificity when sensitivity was maximized. For 1986, combinations reached peak sensitivities of 72% for etiology, 95% for prognosis, 86% for diagnosis, and 98% for therapy. When search terms were combined to maximize specificity, over 93% specificity was achieved for all purpose categories in both years. Compared with individual terms, combined terms achieved near-perfect specificity that was maintained with modest increases in sensitivity in all purpose categories except therapy. Increases in accuracy were achieved by combining terms for all purpose categories, with peak accuracies reaching over 90% for therapy in 1986 and 1991.


CONCLUSIONS
The retrieval of studies of important clinical topics cited in MEDLINE can be substantially enhanced by selected combinations of indexing terms and textwords.
Haynes
R B
RB
Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
Wilczynski
N
N
McKibbon
K A
KA
Walker
C J
CJ
Sinclair
J C
JC
D003933:Diagnosis; D004812:Epidemiologic Methods; D016239:MEDLINE; D011379:Prognosis; D012107:Research Design; D009626:Terminology as Topic; D013812:Therapeutics