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Considering clustering: a methodological review of clinical decision support system studies.

2000·42 Zitationen·PubMedOpen Access
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42

Zitationen

3

Autoren

2000

Jahr

Abstract

Computer-based clinical decision support systems (CDSSs) are often implemented at a cluster level, but standard statistical methods for sample estimation and analysis may not be appropriate for such studies. This review aims to determine whether the design and analysis methods of cluster-based studies were adequately addressed in reports of CDSS studies. We retrieved 61 reports of the CDSS controlled trials and identified 24 studies meeting our inclusion criteria. Of these, none included sample size calculations that allowed for clustering, while 14 (58%) took account of clustering in the analysis. Although there is increasing recognition of the methodological issues associated with cluster design in health care, many medical informaticians are still not aware of these issues. Investigators should publish estimates of the intracluster correlation coefficients and variance components in their reports to guide the planning of the future studies.

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Electronic Health Records SystemsArtificial Intelligence in HealthcareMachine Learning in Healthcare
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