A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.
A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.
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DOI：
10.1177/2054270415609004
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发表时间：
2015-10
期刊：
影响因子：
--
通讯作者：
Haley JM
中科院分区：
文献类型：
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作者：
Amland RC;Lyons JJ;Greene TL;Haley JM
检验两阶段临床决策支持系统对脓毒症患者的早期识别和分层诊断的准确性。观察性队列研究采用两阶段脓毒症临床决策支持来识别和分层脓毒症患者。第一阶段由基于云的临床决策支持和全天候监测组成，以检测有脓毒症风险的患者。基于云的临床决策支持向患者的指定护士发送通知，后者随后以电子方式联系提供商。第二阶段的组成部分包括一个脓毒症筛查和分层表格，集成到患者的电子健康记录中，基本上是一个基于证据的决策辅助，由提供者用来在床边评估患者。在美国，有284个急诊床位的社区医院；每年有16,000人次住院。对2014年实施临床决策支持后的2620例成人患者的资料进行回顾性收集。“可疑感染”是评估临床决策支持临床学表现的金标准。在2620名住院的成人患者中，有417人(16%)启动了败血症警报。以“疑似感染”为标准，患者群体特征的敏感性为72%，阳性预测值为73%。提供者在床边对417名患者进行的警示后筛查获得了81%的敏感性和94%的阳性预测值。提供者记录了89%的患者由临床决策支持激活的警报，并在通知后一小时内完成了75%的败血症患者的床边筛查和分层。具有交叉检查功能的临床决策支持二元警报系统改善了脓毒症患者的早期识别，并促进了患者的分层。
To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients’ designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. ‘Suspected infection’ was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying ‘suspected infection’ as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.