Literature DB >> 20671080

Optimal search filters for detecting quality improvement studies in Medline.

N L Wilczynski1, R B Haynes.   

Abstract

BACKGROUND: As the knowledge translation and comparative effectiveness research agendas gain momentum, we can expect more evidence on which to base quality improvement (QI) programmes. Unaided searches for such content in the literature, however, are likely to be daunting, with searches missing key articles while mainly retrieving articles that are irrelevant to the question being asked. The objective of this study was to develop and validate optimal Medline search filters for retrieving original and review articles about clinical QI.
METHODS: Analytical survey in the McMaster Clinical Hedges database and Health Knowledge Refinery (HKR) of 161 clinical journals to determine the operating characteristics of QI search filters developed by computerised combinations of terms selected to detect original QI studies and systematic reviews meeting basic methodological criteria for scientific merit. Results from a derivation random subset of articles were tested in a validation random subset.
RESULTS: The Clinical Hedges QI database contained 49,233 citations of which 471 (0.96%) were original or review QI studies; of those, 282 (60%) were methodologically sound. Combinations of search terms reached peak sensitivities of 100% at a specificity of 89.3% for detecting methodologically sound original and review QI studies, and sensitivities of 97.6% at a specificity of 53.0% for detecting all original and review QI studies independent of rigour. Operating characteristics of the search filters derived in the development database worked similarly in the validation database, without statistical differences.
CONCLUSION: New empirically derived Medline search filters have been validated to optimise retrieval of original and review QI articles.

Mesh:

Year:  2010        PMID: 20671080     DOI: 10.1136/qshc.2010.042432

Source DB:  PubMed          Journal:  Qual Saf Health Care        ISSN: 1475-3898


  3 in total

1.  Identifying quality improvement intervention publications--a comparison of electronic search strategies.

Authors:  Susanne Hempel; Lisa V Rubenstein; Roberta M Shanman; Robbie Foy; Su Golder; Marjorie Danz; Paul G Shekelle
Journal:  Implement Sci       Date:  2011-08-01       Impact factor: 7.327

2.  Search strategies to identify observational studies in MEDLINE and Embase.

Authors:  Li Li; Helen E Smith; Rifat Atun; Lorainne Tudor Car
Journal:  Cochrane Database Syst Rev       Date:  2019-03-12

3.  Development and testing of a medline search filter for identifying patient and public involvement in health research.

Authors:  Morwenna Rogers; Alison Bethel; Kate Boddy
Journal:  Health Info Libr J       Date:  2017-01-01
  3 in total

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