Epic Sepsis Model Inpatient Predictive Analytic Tool: A Validation Study.

John Cull, Robert Brevetta, Jeff Gerac, Shanu Kothari, Dawn Blackhurst
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引用次数: 1

Abstract

Earlier treatment of sepsis leads to decreased mortality. Epic is an electronic medical record providing a predictive alert system for sepsis, the Epic Sepsis Model (ESM) Inpatient Predictive Analytic Tool. External validation of this system is lacking. This study aims to evaluate the ESM as a sepsis screening tool and determine whether an association exists between ESM alert system implementation and subsequent sepsis-related mortality.

Design: Before-and-after study comparing baseline and intervention period.

Setting: Urban 746-bed academic level 1 trauma center.

Patients: Adult acute care inpatients discharged between January 12, 2018, and July 31, 2019.

Interventions: During the before period, ESM was turned on in the background, but nurses and providers were not alerted of results. The system was then activated to alert providers of scores greater than or equal to 5, a set point determined using receiver operating characteristic curve analysis (area under the curve, 0.834; p < 0.001).

Measurements and main results: Primary outcome was mortality during hospitalization; secondary outcomes were sepsis order set utilization, length of stay, and timing of administration of sepsis-appropriate antibiotics. Of the 11,512 inpatient encounters assessed by ESM, 10.2% (1,171) had sepsis based on diagnosis codes. As a screening test, the ESM had sensitivity, specificity, positive predictive value, and negative predictive value rates of 86.0%, 80.8%, 33.8%, and 98.11%, respectively. After ESM implementation, unadjusted mortality rates in patients with ESM score greater than or equal to 5 and who had not yet received sepsis-appropriate antibiotics declined from 24.3% to 15.9%; multivariable analysis yielded an odds ratio of sepsis-related mortality (95% CI) of 0.56 (0.39-0.80).

Conclusions: In this single-center before-and-after study, utilization of the ESM score as a screening test was associated with a 44% reduction in the odds of sepsis-related mortality. Due to wide utilization of Epic, this is a potentially promising tool to improve sepsis mortality in the United States. This study is hypothesis generating, and further work with more rigorous study design is needed.

Abstract Image

Epic败血症模型住院患者预测分析工具:一项验证研究。
早期治疗败血症可降低死亡率。Epic是一种电子病历,提供败血症的预测警报系统,即Epic败血症模型(ESM)住院患者预测分析工具。该系统缺乏外部验证。本研究旨在评估ESM作为败血症筛查工具的作用,并确定ESM警报系统的实施与随后败血症相关死亡率之间是否存在关联。设计:前后比较基线和干预期的研究。环境:城市746个床位的一级创伤中心。患者:2018年1月12日至2019年7月31日出院的成人急症住院患者。干预措施:在术前,ESM在后台打开,但护士和提供者没有被告知结果。然后激活系统,提醒提供者分数大于或等于5,这是一个设定值,由受试者工作特征曲线分析确定(曲线下面积,0.834;P < 0.001)。测量方法和主要结果:主要结局为住院期间死亡率;次要结果是脓毒症的使用顺序、住院时间和使用适合脓毒症的抗生素的时间。在ESM评估的11,512例住院患者中,根据诊断代码,10.2%(1,171例)患有败血症。作为筛查试验,ESM的敏感性、特异性、阳性预测值和阴性预测值分别为86.0%、80.8%、33.8%和98.11%。实施ESM后,ESM评分大于或等于5且尚未接受败血症适宜抗生素治疗的患者的未调整死亡率从24.3%下降到15.9%;多变量分析得出败血症相关死亡率的比值比(95% CI)为0.56(0.39-0.80)。结论:在这项单中心前后对照研究中,使用ESM评分作为筛选试验与败血症相关死亡率降低44%相关。由于Epic的广泛应用,这是一个潜在的有前途的工具,以提高败血症死亡率在美国。本研究是假设生成的,需要进一步开展更严格的研究设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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