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Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma: Development, Implementation, and Lessons
Eric Tham1, Marguerite Swietlik2, Sara Deakyne2
1Children's Hospital Colorado, Aurora, CO; University of Colorado, Denver, CO.
Insights
Implementing the PECARN TBI prediction rules using electronic health record clinical decision support (CDS) in a multicenter trial proved successful. This strategy aids clinicians in deciding which children with blunt head trauma need computed tomography (CT) scans.
Area of Science:
- Emergency Medicine
- Clinical Informatics
- Pediatric Traumatology
Background:
- Emergency department (ED) clinicians face challenges in determining the necessity of computed tomography (CT) scans for children with blunt head trauma to rule out traumatic brain injury (TBI).
- The Pediatric Emergency Care Applied Research Network (PECARN) developed evidence-based prediction rules to identify low-risk pediatric patients who may not require CT scans, aiming to reduce unnecessary radiation exposure and healthcare costs.
Purpose of the Study:
- To describe the strategy for implementing the PECARN TBI prediction rules using electronic health record (EHR) clinical decision support (CDS) within a multicenter clinical trial.
- To evaluate the feasibility and effectiveness of integrating these prediction rules into routine clinical workflows in diverse ED settings.
Main Methods:
- A multicenter clinical trial involving 13 EDs was conducted, with 10 sites implementing EHR-based CDS using the Epic EHR system.
- The CDS intervention was designed based on sociotechnical analysis, enabling immediate display of recommendations after data entry, with a centralized build and export of the intervention package.
Main Results:
- Despite variations in site-specific workflows and provider involvement, the centralized development and export of the CDS system successfully supported the multicenter clinical trial.
- Challenges included varying completion rates and provider types completing the electronic data form due to customized workflows and site-specific change management processes.
Conclusions:
- The implementation strategy of a centralized build and export of a CDS system within a commercial EHR successfully facilitated a multicenter clinical trial.
- This approach demonstrates a viable method for disseminating and implementing clinical prediction rules across multiple healthcare institutions, potentially improving the care of pediatric head trauma patients.
Introduction:
For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial.
Methods:
Thirteen EDs participated in this trial. The 10 sites receiving the CDS intervention used the Epic(®) EHR. All sites implementing EHR-based CDS built the rules by using the vendor's CDS engine. Based on a sociotechnical analysis, we designed the CDS so that recommendations could be displayed immediately after any provider entered prediction rule data. One central site developed and tested the intervention package to be exported to other sites. The intervention package included a clinical trial alert, an electronic data collection form, the CDS rules and the format for recommendations.
Results:
The original PECARN head trauma prediction rules were derived from physician documentation while this pragmatic trial led each site to customize their workflows and allow multiple different providers to complete the head trauma assessments. These differences in workflows led to varying completion rates across sites as well as differences in the types of providers completing the electronic data form. Site variation in internal change management processes made it challenging to maintain the same rigor across all sites. This led to downstream effects when data reports were developed.
Conclusions:
The process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial.
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