- Kensaku Kawamoto, fellow1,
- Caitlin A Houlihan, scientist1,
- E Andrew Balas, professor and dean2,
- David F Lobach (), associate professor1
- 1Division of Clinical Informatics, Department of Community and Family Medicine, Box 2914, Duke University Medical Center, Durham, NC 27710, USA
- 2College of Health Sciences, Old Dominion University, Norfolk, VA 23529, USA
- Correspondence to: David F Lobach
- Accepted 14 February 2005
Objective To identify features of clinical decision support systems critical for improving clinical practice.
Design Systematic review of randomised controlled trials.
Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews.
Study selection Studies had to evaluate the ability of decision support systems to improve clinical practice.
Data extraction Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature.
Results Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations.
Conclusions Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these features whenever feasible and appropriate.
References w1-w88, the studies reviewed in this article, are on bmj.com
Contributors KK, DFL, and EAB contributed to the study design. KK, CAH, and DFL contributed to the data abstraction. All authors contributed to the data analysis. KK managed the project and wrote the manuscript, and all authors contributed to the critical revision and final approval of the manuscript. DFL is guarantor.
Funding This study was supported by research grants T32-GM07171 and F37-LM008161-01 from the National Institutes of Health, Bethesda, Maryland, USA; and by research grants R01-HS10472 and R03-HS10814 from the Agency for Healthcare Research and Quality, Rockville, Maryland, USA. These funders did not play a role in the design, execution, analysis, or publication of this study.
Competing interests None declared.
Ethical approval Not required.
- Accepted 14 February 2005