Tham Eric, Swietlik Marguerite, Deakyne Sara, Hoffman Jeffrey M, Grundmeier Robert W, Paterno Marilyn D, Rocha Beatriz H, Schaeffer Molly H, Pabbathi Deepika, Alessandrini Evaline, Ballard Dustin, Goldberg Howard S, Kuppermann Nathan, Dayan Peter S
Children's Hospital Colorado, Aurora, CO; University of Colorado, Denver, CO.
Children's Hospital Colorado , Aurora, CO.
Appl Clin Inform. 2016 Jun 15;7(2):534-42. doi: 10.4338/ACI-2015-10-CR-0144. eCollection 2016.
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.
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.
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.
The process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial.
对于因钝性头部外伤而前往急诊科(ED)就诊的儿童,急诊科临床医生必须决定哪些儿童需要进行计算机断层扫描(CT)以评估创伤性脑损伤(TBI)。儿科急诊护理应用研究网络(PECARN)制定并验证了两条基于年龄的预测规则,以识别临床上重要的创伤性脑损伤(ciTBI)风险极低且通常不需要CT扫描的儿童。在本病例报告中,我们描述了通过电子健康记录(EHR)临床决策支持(CDS)实施PECARN TBI预测规则的策略,该策略作为一项多中心临床试验的干预措施。
13个急诊科参与了该试验。接受CDS干预的10个地点使用了Epic(®)电子健康记录系统。所有实施基于电子健康记录的CDS的地点都使用供应商的CDS引擎来构建规则。基于社会技术分析,我们设计了CDS,以便在任何提供者输入预测规则数据后立即显示建议。一个中心站点开发并测试了要导出到其他站点的干预包。干预包包括临床试验警报、电子数据收集表、CDS规则和建议格式。
最初的PECARN头部外伤预测规则源自医生的记录,而这项务实的试验导致每个站点定制其工作流程,并允许多个不同的提供者完成头部外伤评估。这些工作流程的差异导致各站点的完成率不同,以及完成电子数据表单的提供者类型也存在差异。各站点内部变更管理流程的差异使得在所有站点保持相同的严谨性具有挑战性。这在生成数据报告时产生了下游影响。
在一个商业电子健康记录系统中集中构建和导出CDS系统的过程成功支持了一项多中心临床试验。