Transfusion Medicine Informatics: Analysis of User Burden from Clinical Decision Support Alerts in Promoting Patient Blood Management

Abstract

Abstract Introduction/Objective To increase efficiency of blood product ordering and delivery processes and improve appropriateness of orders, a major project to implement clinical decision support (CDS) alerts in the electronic medical record (EMR) was undertaken. A design team was assembled including hospital and laboratory medicine information technology and clinical informatics, transfusion services, nursing and clinical services from medical and surgical specialties. Methods Consensus-derived thresholds in hemoglobin/hematocrit, platelet count, INR, and fibrinogen for red blood cell (RBC), platelet, plasma, and cryoprecipitate blood products CDS alerts were determined. Data from the EMR and laboratory information system were queried from the 12-month period before and after implementation and the data was analyzed. Results During the analysis period, 5813 RBC (avg. monthly = 484), 1040 platelet (avg. monthly = 87), 423 plasma (avg. monthly = 35), and 88 cryoprecipitate (avg. monthly = 7) alerts fired. The average time it took for a user to respond was 5.175 seconds. The total amount of time alerts displayed over 12 months was 5813 seconds (~97 minutes of user time) compared to 56503 blood products transfused. Of active CDS alerts, hemoglobin/RBC alerts fired most often with ~1:5 (31141 RBC units) alert to transfusion ratio and 4% of orders canceled (n=231) when viewing the alert, platelet alerts fired with ~1:15 (15385 platelet units) alert to transfusion ratio and 6% orders canceled (n=66), INR/plasma alerts fired with ~1:21 (8793 plasma units) alert to transfusion ratio and 10% orders canceled (n=41), cryoprecipitate alerts fired with ~1:13 (1184 cryoprecipitate units) alert to transfusion ratio and 10% orders canceled (n=9). Overall monthly blood utilization normalized to 1000 patient discharges did not appear to have statistically significant differences comparing pre- versus post-go-live, except a potentially significant increase in monthly plasma usage at one facility with p = 0.34, although possibly due to an outlier single month of heavy usage. Conclusion Clinical decision support alerts can guide provider ordering with minimal user burden. This resulted in increased safety and quality use of the ordering process, although overall blood utilization did not appear to change significantly.