Research Activities January 2013, No. 389
Computerized clinical decision support produces only modest savings for nursing home residents with impaired kidney function
Computerized clinical decision support (CCDS) systems can help ensure proper treatment for residents in long-term care facilities who have renal insufficiency (impaired kidney function). However, a new study finds that cost reductions due to CCDS are modest compared to unassisted prescribing by a physician.
Renal insufficiency, defined as a creatinine clearance of less than 60 ml/min, affects up to 40 percent of nursing home residents older than 75 years. The researchers conducted a randomized study assessing CCDS prescribing recommendations and the impact on costs in a long-term care setting. The CCDS modestly reduced drug costs, which were partially offset by an increase in additional laboratory testing that resulted from alerts.
Units of the facility where the doctors received CCDS alerts reduced direct costs for drugs 7.6 percent ($1,391), assuming a course of drug treatment of 30 days. Estimated savings increased further assuming longer courses of drug therapy (e.g., 90 days or 180 days). The calculations did not include the savings from avoidance of serious adverse drug events due to renal insufficiency.
The study was conducted in an academically affiliated long-term care facility in Canada with an electronic medical record system with integrated computerized provider order entry. Twenty-two long-stay units were randomly assigned to having physicians receive alerts for medication treatments requiring consideration of renal function or having alerts generated, but not presented to the prescribing physician. The study was funded in part by the Agency for Healthcare Research and Quality (HS10481 and HS15430).
More details are in "Immediate financial impact of computerized clinical decision support for long-term care residents with renal insufficiency: A case study," by Sujha Subramanian, PhD, Sonja Hoover, M.P.P, Joann L. Wagner, MSW, and others in the May 2012 Journal of the American Medical Informatics Association 19(3), pp. 439-442.
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