The Role of Computerized Clinical Decision Support in Reducing Inappropriate Medication Administration During Epidural Therapy

Abstract

Background: The use of epidural anesthesia has been shown to improve outcomes in the postoperative setting. To minimize risk of complications, avoiding certain medications with epidural anesthesia is advised. Objective: This study sought to determine the role of a computerized clinical decision support module implemented into the computerized physician order entry (CPOE) system on the incidence of administration of medications known to increase complications with epidural anesthesia. Methods: This study was a retrospective cohort chart review in adult patients receiving epidural anesthesia for at least 1 day. Patients were identified retrospectively and divided into 2 cohorts, those receiving an epidural 3 months prior to initiation of the module and those receiving an epidural 3 months following implementation. The primary end point was incidence of inappropriate medication administration before and after implementation. Complications of therapy were collected as secondary end points. Results: There was a reduction in the incidence of inappropriate medication administration in the postimplementation group versus the preimplementation group (6.3% vs 12.8%) although statistical significance was not achieved. In addition, the incidence of enoxaparin administration was significantly lower postimplementation than the preimplementation (0% vs 3.9%). There were no significant differences in other complications of therapy. Conclusions: This study demonstrated that application of decision support for this high-risk procedural population was able to eliminate the incidence of the most common inappropriate medication for epidural analgesia, enoxaparin. A reduction in incidence of other inappropriate medications was also observed; however, statistical significance was not reached. The use of computerized clinical decision support can be a powerful tool in reducing or ameliorating medication errors, and further study will be required to determine the most appropriate and effective implementation strategies.