Use of Traumatic Brain Injury Prediction Rules With Clinical Decision Support.

2017

2017 Mar 24

1098-4275

<p><strong>OBJECTIVES: </strong>We determined whether implementing the Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) prediction rules and providing risks of clinically important TBIs (ciTBIs) with computerized clinical decision support (CDS) reduces computed tomography (CT) use for children with minor head trauma.</p>

<p><strong>METHODS: </strong>Nonrandomized trial with concurrent controls at 5 pediatric emergency departments (PEDs) and 8 general EDs (GEDs) between November 2011 and June 2014. Patients were &lt;18 years old with minor blunt head trauma. Intervention sites received CDS with CT recommendations and risks of ciTBI, both for patients at very low risk of ciTBI (no Pediatric Emergency Care Applied Research Network rule factors) and those not at very low risk. The primary outcome was the rate of CT, analyzed by site, controlling for time trend.</p>

<p><strong>RESULTS: </strong>We analyzed 16 635 intervention and 2394 control patients. Adjusted for time trends, CT rates decreased significantly (P &lt; .05) but modestly (2.3%-3.7%) at 2 of 4 intervention PEDs for children at very low risk. The other 2 PEDs had small (0.8%-1.5%) nonsignificant decreases. CT rates did not decrease consistently at the intervention GEDs, with low baseline CT rates (2.1%-4.0%) in those at very low risk. The control PED had little change in CT use in similar children (from 1.6% to 2.9%); the control GED showed a decrease in the CT rate (from 7.1% to 2.6%). For all children with minor head trauma, intervention sites had small decreases in CT rates (1.7%-6.2%).</p>

<p><strong>CONCLUSIONS: </strong>The implementation of TBI prediction rules and provision of risks of ciTBIs by using CDS was associated with modest, safe, but variable decreases in CT use. However, some secular trends were also noted.</p>

10.1542/peds.2016-2709

Pediatrics

28341799

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma.

2016

101-10

2016 Mar

1872-8243

<p><strong>OBJECTIVE: </strong>To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma.</p>

<p><strong>MATERIALS AND METHODS: </strong>We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians.</p>

<p><strong>RESULTS: </strong>The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service.</p>

<p><strong>DISCUSSION: </strong>The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock.</p>

<p><strong>CONCLUSION: </strong>With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions.</p>

10.1016/j.ijmedinf.2015.12.002

Int J Med Inform

26806717