Westra Bonnie L, Landman Sean, Yadav Pranjul, Steinbach Michael
Bonnie L. Westra, PhD, RN, FAAN, FACMI, University of Minnesota, School of Nursing, 308 Harvard St SE, WDH 5-140, Minneapolis, MN, USA 55455, Email:
Appl Clin Inform. 2017 Jan 18;8(1):47-66. doi: 10.4338/ACI-2016-07-RA-0112.
To conduct an independent secondary analysis of a multi-focal intervention for early detection of sepsis that included implementation of change management strategies, electronic surveillance for sepsis, and evidence based point of care alerting using the POC AdvisorTM application.
Propensity score matching was used to select subsets of the cohorts with balanced covariates. Bootstrapping was performed to build distributions of the measured difference in rates/means. The effect of the sepsis intervention was evaluated for all patients, and High and Low Risk subgroups for illness severity. A separate analysis was performed patients on the intervention and non-intervention units (without the electronic surveillance). Sensitivity, specificity, and the positive predictive values were calculated to evaluate the accuracy of the alerting system for detecting sepsis or severe sepsis/ septic shock.
There was positive effect on the intervention units with sepsis electronic surveillance with an adjusted mortality rate of -6.6%. Mortality rates for non-intervention units also improved, but at a lower rate of -2.9%. Additional outcomes improved for patients on both intervention and non-intervention units for home discharge (7.5% vs 1.1%), total length of hospital stay (-0.9% vs -0.3%), and 30 day readmissions (-6.6% vs -1.6%). Patients on the intervention units showed better outcomes compared with non-intervention unit patients, and even more so for High Risk patients. The sensitivity was 95.2%, specificity of 82.0% and PPV of 50.6% for the electronic surveillance alerts.
There was improvement over time across the hospital for patients on the intervention and non-intervention units with more improvement for sicker patients. Patients on intervention units with electronic surveillance have better outcomes; however, due to differences in exclusion criteria and types of units, further study is needed to draw a direct relationship between the electronic surveillance system and outcomes.
对一项多焦点脓毒症早期检测干预措施进行独立的二次分析，该干预措施包括实施变革管理策略、脓毒症电子监测以及使用POC AdvisorTM应用程序进行基于证据的床边警报。
采用倾向得分匹配法选择协变量平衡的队列子集。进行自助法以构建率/均值测量差异的分布。对所有患者评估脓毒症干预措施的效果，并对疾病严重程度的高风险和低风险亚组进行评估。对干预组和非干预组（无电子监测）的患者进行单独分析。计算敏感性、特异性和阳性预测值，以评估警报系统检测脓毒症或严重脓毒症/脓毒性休克的准确性。
脓毒症电子监测干预组有积极效果，调整后的死亡率为-6.6%。非干预组的死亡率也有所改善，但改善率较低，为-2.9%。干预组和非干预组患者在出院回家（7.5%对1.1%）、住院总时长（-0.9%对-0.3%）和30天再入院率（-6.6%对-1.6%）方面的其他结果也有所改善。与非干预组患者相比，干预组患者的结局更好，高危患者更是如此。电子监测警报的敏感性为95.2%，特异性为82.0%，阳性预测值为50.6%。
随着时间推移，干预组和非干预组的患者在全院范围内均有改善，病情较重的患者改善更为明显。有电子监测的干预组患者结局更好；然而，由于排除标准和科室类型的差异，需要进一步研究以确定电子监测系统与结局之间的直接关系。
