Optimal search strategies for retrieving scientifically strong studies of diagnosis from Medline: analytical survey. Export

@article{citeulike:162059, abstract = {OBJECTIVE: To develop optimal search strategies in Medline for retrieving sound clinical studies on the diagnosis of health disorders. DESIGN: Analytical survey. SETTING: Medline, 2000. PARTICIPANTS: 170 journals for 2000 of which 161 were indexed in Medline. MAIN OUTCOME MEASURES: The sensitivity, specificity, precision ("positive predictive value"), and accuracy of 4862 unique terms in 17,287 combinations were determined by comparison with a hand search of all articles (the "gold standard") in 161 journals published during 2000 (49,028 articles). RESULTS: Only 147 (18.9\%) of 778 articles about diagnostic tests met basic criteria for scientific merit. Combinations of search terms reached peak sensitivities of 98.6\% at a specificity of 74.3\%. Compared with best single terms, best multiple terms increased sensitivity for sound studies by 6.8\% (absolute increase), while also increasing specificity (absolute increase 6.0\%) when sensitivity was maximised. When terms were combined to maximise specificity, the single term, specificity.tw. (98.4\%), outperformed combinations of terms. The strategies newly reported in this paper outperformed other validated search strategies except for one strategy that had slightly higher sensitivity (99.3\% v 98.6\%) but lower specificity (54.7\% v 74.3\%). CONCLUSION: New empirical search strategies in Medline can optimise retrieval of articles reporting high quality clinical studies of diagnosis.}, address = {Health Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University Faculty of Health Sciences, 1200 Main Street West, Hamilton, ON, L8N 3Z5, Canada. bhaynes@mcmaster.ca}, author = {Haynes, R. B. and Wilczynski, N. L.}, citeulike-article-id = {162059}, citeulike-linkout-0 = {http://dx.doi.org/10.1136/bmj.38068.557998.EE}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15073027}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15073027}, day = {1}, doi = {10.1136/bmj.38068.557998.EE}, issn = {1468-5833}, journal = {BMJ}, keywords = {medline}, month = {May}, number = {7447}, posted-at = {2007-09-14 02:59:01}, priority = {2}, title = {Optimal search strategies for retrieving scientifically strong studies of diagnosis from Medline: analytical survey.}, url = {http://dx.doi.org/10.1136/bmj.38068.557998.EE}, volume = {328}, year = {2004} }

TY - JOUR ID - citeulike:162059 L3 - citeulike-article-id:162059 N2 - OBJECTIVE: To develop optimal search strategies in Medline for retrieving sound clinical studies on the diagnosis of health disorders. DESIGN: Analytical survey. SETTING: Medline, 2000. PARTICIPANTS: 170 journals for 2000 of which 161 were indexed in Medline. MAIN OUTCOME MEASURES: The sensitivity, specificity, precision ("positive predictive value"), and accuracy of 4862 unique terms in 17,287 combinations were determined by comparison with a hand search of all articles (the "gold standard") in 161 journals published during 2000 (49,028 articles). RESULTS: Only 147 (18.9%) of 778 articles about diagnostic tests met basic criteria for scientific merit. Combinations of search terms reached peak sensitivities of 98.6% at a specificity of 74.3%. Compared with best single terms, best multiple terms increased sensitivity for sound studies by 6.8% (absolute increase), while also increasing specificity (absolute increase 6.0%) when sensitivity was maximised. When terms were combined to maximise specificity, the single term, specificity.tw. (98.4%), outperformed combinations of terms. The strategies newly reported in this paper outperformed other validated search strategies except for one strategy that had slightly higher sensitivity (99.3% v 98.6%) but lower specificity (54.7% v 74.3%). CONCLUSION: New empirical search strategies in Medline can optimise retrieval of articles reporting high quality clinical studies of diagnosis. IS - 7447 JF - BMJ SN - 1468-5833 AD - Health Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University Faculty of Health Sciences, 1200 Main Street West, Hamilton, ON, L8N 3Z5, Canada. bhaynes@mcmaster.ca TI - Optimal search strategies for retrieving scientifically strong studies of diagnosis from Medline: analytical survey. VL - 328 KW - medline AU - Haynes, RB AU - Wilczynski, NL PY - 2004/05/01/ UR - http://dx.doi.org/10.1136/bmj.38068.557998.EE ER -