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


METHODS
A retrospective observational study.


METHODS
A university-affiliated medical-surgical-trauma intensive care unit over a 1-yr period.


METHODS
One hundred randomly selected critically ill patients.


METHODS
None.


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.
Ilan
Roy
R
Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Fowler
Robert A
RA
Geerts
Ryan
R
Pinto
Ruxandra
R
Sibbald
William J
WJ
Martin
Claudio M
CM
D000328:Adult; D000368:Aged; D003422:Critical Care; D004059:Diffusion of Innovation; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D007362:Intensive Care Units; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009864:Ontario; D017410:Practice Guidelines as Topic; D012189:Retrospective Studies