Clinical Decision Support Tool Reduces Tests, Antibiotic Use

Jennifer Garcia

July 29, 2013

Providers who used an integrated clinical decision support tool for the management of patients with respiratory tract infections were less likely to prescribe antibiotics or order point-of-care testing when compared with providers not using the tool. Results of the randomized controlled trial were published online July 29 in JAMA Internal Medicine.

Thomas G. McGinn, MD, MPH, from the Hofstra North Shore-LIJ School of Medicine, Manhasset, New York, and colleagues evaluated the use of clinical prediction rules among 168 primary care providers within 2 large urban practices between November 1, 2010, and October 31, 2011. Providers were divided into a control group (usual care) or an intervention group that would use the clinical prediction rules; specifically, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. These rules were integrated into the electronic health records (EHRs) used by the intervention group, and providers received a 1-hour training session on use of the tool in the EHR.

The researchers found that providers who used the decision tool were less likely to order antibiotics than those in the control group (age-adjusted relative risk [RR], 0.74; 95% confidence interval [CI], 0.60 - 0.92; P = .008). They also found a difference in the type of antibiotics ordered, noting the RR ratio for ordering quinolones in the intervention group compared with the control group was 0.50 (95% CI, 0.29 - 0.88; P = .02). Providers who used the tool were also less likely to order rapid streptococcal tests in pharyngitis encounters compared with the control group (RR, 0.75; 95% CI, 0.58 - 0.97; P = .03).

"In addition to our high overall adoption rate of 62.8%, we found that 57.5% of all relevant encounters resulted in the provider completing the risk score calculator and generating a risk score assessment," Dr. McGinn and colleagues write. "We believe our results indicate that providers may have perceived the tool as being helpful with the clinical diagnosis of pharyngitis and pneumonia, enhancing clinical work flow and improving patient care, which are hallmarks of [clinical decision support] interventions that are well received by physicians."

The authors acknowledge that further studies will be required to determine the effect of clinical setting and patient demographics on CPR effectiveness.

Provider Training the Key to Implementation?

In an accompanying editor's note, Mitchell H. Katz, MD, director of the Los Angeles County Department of Health Services in California and a deputy editor for JAMA Internal Medicine, discusses the many reasons why clinical decision tools have not been widely implemented in practice. In the present study however, Dr. Katz notes that "the tool was developed with focus group input from physicians and usability testing, and supportive training was provided to physicians." Dr. Katz suggests that these are the reasons for the high adoption rate noted by the researchers and that "physician input, customization, and training are critical for success" when integrating these tools into EHRs.

Funding for this study was provided by a grant from the Agency for Health and Quality Research. One of the authors is a member of the research board of EHE International; has received consulting fees from Merck, IMS Health, and UBS; and is the recipient of a research grant from GlaxoSmithKline. The other authors and editorialist have disclosed no relevant financial relationships.

JAMA Intern Med. Published online July 29, 2013.


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