Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use
Many hospitals are experiencing an increasing incidence of bacterial resistance in patients requires inpatient medical care. Most often, this can be attributed to inappropriate administration of antimicrobial therapy. In an effort to decrease this trend, many facilities have restricted the use certain antimicrobials and have enlisted the aid of antimicrobial management teams (AMT) to intervene when unnecessary antimicrobial therapy is occurs. Medical intervention by an AMT has proven to be successful in improving patient care but such teams’ reliance on post-prescription review and retroactive chart inspection may hinder the teams’ ability to intervene in a timely fashion. The purpose of this study was to explore what impact the use automated alerts generated by a computerized decision support system (CDSS) would have on standard levels of care on patients receiving antimicrobial therapy.
For approximately 12 weeks, the University Of Maryland Medical Center conducted a study involving 4, 507 adult inpatients. Patients were randomly divided into two groups. The AMT was responsible for managing the antimicrobial therapy for both groups. The control group consisted of 2,270 patients, of whom whose antimicrobial therapy was managed using established protocols. The intervention group, consisted of 2,237 patients whose therapy was whose antimicrobial management was augmented by system alerts generated by a CDSS. Automatic alerts were designed to be generated by the system when the patient’s current antimicrobial therapy included one of the facility’s 23 restricted drugs, a specific antimicrobial, double coverage of antimicrobials targeted to treat specific bacteria or those antimicrobials not clinically indicated based on bacterial susceptibility results. Alerts for each scenario might require intervention on the part of the AMT. For both groups, recommendations for changes in therapy were communicated verbally to primary care team or noted on the patient’s chart.
Aided by alerts produced by the CDSS, the AMT was able to intervene on 8.1% more patients in the intervention group than those in the control group, with 61% of the alerts triggered as a result of patients being prescribed restricted antimicrobials. In using the CDSS, the facility was able to realize a 22.8% costs reduction in antimicrobial expense, as compared to that was spent for the control group. Additionally, more patients in the intervention group were spared the negative side effects of being placed on unnecessary antimicrobials. Because of the researchers’ preliminary findings, which include the reduction in time spent on making therapy inventions, the study was stopped and the CDSS was implemented in the facility.
Comments: The deployment of a CDSS proves valuable in addressing issues related to antimicrobial utilization and management. Such a system provides clinicians with the opportunity to adjust antimicrobial therapy in a timely manner and therefore significantly curb antimicrobial resistance and improve patient outcomes. By improving antimicrobial management protocol, medical facilities have the potential to improve their bottom-line by drastically reducing antimicrobial expenditures.
This study proved successful mainly because it was designed for and fully embraced by the AMT. As the authors stated, the institution did not have an Electronic Medical Record system in place during the study. One would have to speculate as to what additional benefits would be realized if such as system were to be integrated with an EMR and implemented at the point of care.