Quality Improvement in Pediatric Head Trauma with PECARN Rules Implementation as Computerized Decision Support

BACKGROUND: For the 1.4 million emergency department (ED) visits for traumatic brain injury (TBI) annually in the United States, computed tomography (CT) may be over utilized. The Pediatric Emergency Care Applied Research Network developed 2 prediction rules to identify children at very low risk of clinically important TBI. We implemented these prediction rules as decision support within our electronic health record (EHR) to reduce CT. OBJECTIVE: To test EHR decision support implementation in reducing CT rates for head trauma at 2 pediatric EDs. METHODS: We compared monthly CT rates 1 year before [preimplementation (PRE)] and 1 year after [postimplementation (POST)] decision support implementation. The primary outcome was change in CT use rate over time, measured using statistical process control charts. Secondary analyses included multivariate comparisons of PRE to POST. Balancing measures included ED length of stay and returns within 7 days after ED release. RESULTS: There were 2,878 patients with head trauma (1,329 PRE and 1,549 POST) included. Statistical process control charts confirmed decreased CT rates over time POST that was not present PRE. Secondary statistical analyses confirmed that CT scan utilization rates decreased from 26.8% to 18.9% (unadjusted Odds Ratio [OR], 0.64; 95% Confidence Interval [CI], 0.53 -0.76; adjusted OR, 0.71; 95% CI, 0.58 -0.86). Length of stay was unchanged. There was no increase in returns within 7 days and no significant missed diagnoses. CONCLUSIONS: Implementation of EHR-integrated decision support for children with head trauma presenting to the ED is associated with a decrease in CT utilization and no increase in significant safety events.