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Derivation and Validation of a MEDLINE Search Strategy for Research Studies That Use Administrative Data

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.

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