Address correspondence to Carl van Walraven, M.D., M.Sc., F.R.C.P.C., Ottawa Hospital Research Institute, Institute for Clinical Evaluative Sciences, ASB 1-003 1053 Carling Avenue, Ottawa, ON K1Y 4E9; e-mail: email@example.com. Carol Bennett, M.Sc., is with the Ottawa Hospital Research Institute, Ottawa, ON. Alan J. Forster, M.D., M.Sc., F.R.C.P.C., is with the Ottawa Hospital Research Institute, Institute for Clinical Evaluative Sciences, Ottawa, ON.
Derivation and Validation of a MEDLINE Search Strategy for Research Studies That Use Administrative Data
Version of Record online: 1 SEP 2010
© Health Research and Educational Trust
Health Services Research
Volume 45, Issue 6p1, pages 1836–1845, December 2010
How to Cite
Van Walraven, C., Bennett, C. and Forster, A. J. (2010), Derivation and Validation of a MEDLINE Search Strategy for Research Studies That Use Administrative Data. Health Services Research, 45: 1836–1845. doi: 10.1111/j.1475-6773.2010.01159.x
- Issue online: 8 NOV 2010
- Version of Record online: 1 SEP 2010
- Administrative data uses;
- biostatistical methods;
- information technology in health
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.