儿科 ICU 脓毒症预测工具的设计、实施和验证：作为临床决策支持。
Design, Implementation, and Validation of a Pediatric ICU Sepsis Prediction Tool as Clinical Decision Support.
机构信息
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States.
出版信息
Appl Clin Inform. 2020 Mar;11(2):218-225. doi: 10.1055/s-0040-1705107. Epub 2020 Mar 25.
BACKGROUND
Sepsis is an uncontrolled inflammatory reaction caused by infection. Clinicians in the pediatric intensive care unit (PICU) developed a paper-based tool to identify patients at risk of sepsis. To improve the utilization of the tool, the PICU team integrated the paper-based tool as a real-time clinical decision support (CDS) intervention in the electronic health record (EHR).
OBJECTIVE
This study aimed to improve identification of PICU patients with sepsis through an automated EHR-based CDS intervention.
METHODS
A prospective cohort study of all patients admitted to the PICU from May 2017 to May 2019. A CDS intervention was implemented in May 2018. The CDS intervention screened patients for nonspecific sepsis criteria, temperature dysregulation and a blood culture within 6 hours. Following the screening, an interruptive alert prompted nursing staff to complete a perfusion screen to assess for clinical signs of sepsis. The primary alert performance outcomes included sensitivity, specificity, and positive and negative predictive value. The secondary clinical outcome was completion of sepsis management tasks.
RESULTS
During the 1-year post implementation period, there were 45.0 sepsis events per 1,000 patient days over 10,805 patient days. The sepsis alert identified 392 of the 436 sepsis episodes accurately with sensitivity of 92.5%, specificity of 95.6%, positive predictive value of 46.0%, and negative predictive value of 99.7%. Examining only patients with severe sepsis confirmed by chart review, test characteristics fell to a sensitivity of 73.3%, a specificity of 92.5%. Prior to the initiation of the alert, 18.6% (13/70) of severe sepsis patients received recommended sepsis interventions. Following the implementation, 34% (27/80) received these interventions in the time recommended, = 0.04.
CONCLUSION
An EHR CDS intervention demonstrated strong performance characteristics and improved completion of recommended sepsis interventions.
背景
败血症是由感染引起的失控性炎症反应。儿科重症监护病房（PICU）的临床医生开发了一种基于纸质的工具，以识别有败血症风险的患者。为了提高该工具的利用率，PICU 团队将基于纸质的工具整合到电子病历（EHR）中，作为实时临床决策支持（CDS）干预措施。
目的
本研究旨在通过基于电子病历的 CDS 干预来提高败血症患者的识别率。
方法
这是一项针对 2017 年 5 月至 2019 年 5 月期间入住 PICU 的所有患者的前瞻性队列研究。2018 年 5 月实施了 CDS 干预。该 CDS 干预措施筛查了 6 小时内非特定败血症标准、体温失调和血培养的患者。筛查后，中断警报提示护理人员完成灌注筛查，以评估败血症的临床体征。主要警报性能结果包括敏感性、特异性、阳性预测值和阴性预测值。次要临床结局是完成败血症管理任务。
结果
在实施后的 1 年期间，在 10805 个患者日中，每 1000 个患者日有 45.0 例败血症事件。败血症警报准确识别了 436 例败血症发作中的 392 例，其敏感性为 92.5%，特异性为 95.6%，阳性预测值为 46.0%，阴性预测值为 99.7%。仅检查经图表审查确认的严重败血症患者，测试特征下降至敏感性 73.3%，特异性 92.5%。在警报启动之前，18.6%（13/70）的严重败血症患者接受了推荐的败血症干预措施。实施后，34%（27/80）的患者在推荐时间内接受了这些干预措施，=0.04。
结论
EHR CDS 干预措施表现出较强的性能特征，并提高了推荐的败血症干预措施的完成率。
Zotero 插件