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Crit Care Med. 2010 Aug;38(8 Suppl):S282-91. doi: 10.1097/CCM.0b013e3181e69e02.

Using an interdisciplinary approach to identify factors that affect clinicians' compliance with evidence-based guidelines.

Author information

1
Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. agurses1@jhmi.edu

Abstract

OBJECTIVE:

Our objective was to identify factors that affect clinicians' compliance with the evidence-based guidelines using an interdisciplinary approach and develop a conceptual framework that can provide a comprehensive and practical guide for designing effective interventions.

DESIGN:

A literature review and a brainstorming session with 11 researchers from a variety of scientific disciplines were used to identify theoretical and conceptual models describing clinicians' guideline compliance. MEDLINE, EMBASE, CINAHL, and the bibliographies of the papers identified were used as data sources for identifying the relevant theoretical and conceptual models.

RESULTS:

Thirteen different models that originated from various disciplines including medicine, rural sociology, psychology, human factors and systems engineering, organizational management, marketing, and health education were identified. Four main categories of factors that affect compliance emerged from our analysis: clinician characteristics, guideline characteristics, system characteristics, and implementation characteristics. Based on these findings, we developed an interdisciplinary conceptual framework that specifies the expected interrelationships among these four categories of factors and their impact on clinicians' compliance.

CONCLUSIONS:

An interdisciplinary approach is needed to improve clinicians' compliance with evidence-based guidelines. The conceptual framework from this research can provide a comprehensive and systematic guide to identify barriers to guideline compliance and design effective interventions to improve patient safety.

PMID:
20647785
DOI:
10.1097/CCM.0b013e3181e69e02
[Indexed for MEDLINE]
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