eDST ACLS app
Aim of the study: In-house cardiac arrest is a common event associated with high morbidity and mortality. Fortunately, an optimal clinical response can improve patient outcomes. Advanced cardiac life support (ACLS) guidelines represent evidence-based management of in-hospital cardiac arrest, but numerous studies show that compliance is suboptimal. We developed an electronic decision support tool and investigated whether the use of the tool improves adherence to ACLS guidelines. Methods: A prospective randomised trial was conducted at Vanderbilt University Medical Center. Unannounced in-situ simulations of in-hospital cardiac arrest were performed in intensive care unit settings over 15 months. Code teams assembled from physicians and nurses on clinical duty at the time of simulation were randomised to either the electronic decision support tool (eDST) or a control group. Simulations were video recorded and graded for adherence to ACLS guidelines. Results: Use of the new tool resulted in an absolute 10% increase in the percentage of correct clinical actions between the control (n=16) and intervention (eDST; n=11; 73% vs 83%; p=0.001). Use of the tool also resulted in a reduction in median number of errors committed per simulation (2 vs 1, p<0.001). Conclusion: In this study, an electronic decision support tool improved team performance as measured by increased adherence to ACLS guidelines and a reduction in errors. Future research should investigate optimal implementation of the eDST into routine clinical practice and observed impact on both process and outcome metrics.