Literature DB >> 17522582

Knowledge translation in critical care: factors associated with prescription of commonly recommended best practices for critically ill patients.

Roy Ilan1, Robert A Fowler, Ryan Geerts, Ruxandra Pinto, William J Sibbald, Claudio M Martin.   

Abstract

OBJECTIVE: To describe prescription rates of commonly recommended best practices (clinical interventions with a strong base of evidence supporting their implementation) for critically ill patients and determine factors associated with increased rates of prescription.
DESIGN: A retrospective observational study.
SETTING: A university-affiliated medical-surgical-trauma intensive care unit over a 1-yr period. PATIENTS: One hundred randomly selected critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Among the best practices studied, there was great variability in the proportion of patients eligible (median 36.5%, range 10% to 100%) and the proportion without contraindication (32.5%, range 10% to 86%) for each practice. The median rate of prescription of best practices for eligible patients was 56.5%, with a range from 8% to 95%. There was greater prescription of best practices when standard admission orders included an option to prescribe them (p = .048). Among those practices with standard admission orders, there was greatest prescription for practices additionally having a specialty consultation service (p = .004). There was an inverse association between severity of illness and prescription of best practices (p = .001): Sicker patients were less likely to be prescribed best practices.
CONCLUSIONS: There may be substantial variability in the acceptance and prescription of commonly recommended best practices for critically ill patients. Standard order sets and focused specialty consultation may improve knowledge translation and prescription of best practice.

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Mesh:

Year:  2007        PMID: 17522582     DOI: 10.1097/01.CCM.0000269041.05527.80

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


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