Literature DB >> 20819111

Derivation and validation of a MEDLINE search strategy for research studies that use administrative data.

Carl Van Walraven1, Carol Bennett, Alan J Forster.   

Abstract

OBJECTIVE: To derive and validate a search strategy that identifies administrative database research (ADR) in the MEDLINE database.
DESIGN: Analytical survey.
METHODS: We downloaded all articles published between January 1, 2008 and October 7, 2009 in 20 top journals in internal medicine, cardiovascular medicine, public health, and health services research. These were reviewed to determine whether they were ADR (in which the study cohort, exposure, or outcome was defined using electronic data created for or during the processing of patients through their health care). We used chi-squared recursive partitioning to create a search strategy that maximized sensitivity based on publication type, MeSH headings, and text words. MAIN OUTCOME MEASURES: Sensitivity and positive predictive value of the search strategy for true ADR in three samples: derivation (n=5,513); internal validation (n=2,710); and external validation (n=1,500).
RESULTS: The prevalence of ADR in the derivation, internal validation, and external validation samples was 2.6, 2.9, and 2.2 percent, respectively. The sensitivity of our search strategy in these samples was 90.9 percent (95 percent confidence interval [CI] 85.0-95.1), 88.5 percent (79.2-94.6), and 100 percent (99.3-100), respectively. The positive predictive value in these samples was 10.7 percent (9.0-12.6), 11.5 percent (9.1-14.4), and 3.3 percent (2.3-4.6), respectively.
CONCLUSION: We derived and validated a search strategy that is highly sensitive for ADR in MEDLINE. © Health Research and Educational Trust.

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Mesh:

Year:  2010        PMID: 20819111      PMCID: PMC3026961          DOI: 10.1111/j.1475-6773.2010.01159.x

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  3 in total

1.  Optimal search strategies for detecting clinically sound prognostic studies in EMBASE: an analytic survey.

Authors:  Nancy L Wilczynski; R Brian Haynes
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

2.  Optimal search strategies for retrieving scientifically strong studies of treatment from Medline: analytical survey.

Authors:  R Brian Haynes; K Ann McKibbon; Nancy L Wilczynski; Stephen D Walter; Stephen R Werre
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3.  Developing optimal search strategies for detecting clinically sound prognostic studies in MEDLINE: an analytic survey.

Authors:  Nancy L Wilczynski; R Brian Haynes
Journal:  BMC Med       Date:  2004-06-09       Impact factor: 8.775

  3 in total

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