• Christopher L Fillmore, Bruce E Bray, and Kensaku Kawamoto.
• Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah 84112, USA. christopher.fillmore@utah.edu.
• Bmc Med Inform Decis. 2013 Jan 1;13:135.

BackgroundHealthcare costs are increasing rapidly and at an unsustainable rate in many countries, and inpatient hospitalizations are a significant driver of these costs. Clinical decision support (CDS) represents a promising approach to not only improve care but to reduce costs in the inpatient setting. The purpose of this study was to systematically review trials of CDS interventions with the potential to reduce inpatient costs, so as to identify promising interventions for more widespread implementation and to inform future research in this area.MethodsTo identify relevant studies, MEDLINE was searched up to July 2013. CDS intervention studies with the potential to reduce inpatient healthcare costs were identified through titles and abstracts, and full text articles were reviewed to make a final determination on inclusion. Relevant characteristics of the studies were extracted and summarized.ResultsFollowing a screening of 7,663 articles, 78 manuscripts were included. 78.2% of studies were controlled before-after studies, and 15.4% were randomized controlled trials. 53.8% of the studies were focused on pharmacotherapy. The majority of manuscripts were published during or after 2008. 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. Only 12.8% of the studies directly measured the financial impact of an intervention, whereas the financial impact was inferred in the remainder of studies. Data on cost effectiveness was available for only one study.ConclusionsSignificantly more research is required on the impact of clinical decision support on inpatient costs. In particular, there is a remarkable gap in the availability of cost effectiveness studies required by policy makers and decision makers in healthcare systems.

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