Secondary Analysis of an Electronic Surveillance System Combined with Multi-focal Interventions for Early Detection of Sepsis

Bonnie L. Westra; Sean Landman; Pranjul Yadav; Michael Steinbach

doi:10.4338/ACI-2016-07-RA-0112

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2017; 08(01): 47-66
DOI: 10.4338/ACI-2016-07-RA-0112

Research Article

Schattauer GmbH

Secondary Analysis of an Electronic Surveillance System Combined with Multi-focal Interventions for Early Detection of Sepsis

Authors

Bonnie L. Westra

¹University of Minnesota, School of Nursing, Minneapolis, MN, USA 55455
Sean Landman

²University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA
Pranjul Yadav

²University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA
Michael Steinbach

²University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA

Abstract

Summary

Summary: To conduct an independent secondary analysis of a multi-focal intervention for early detection of sepsis that included implementation of change management strategies, electronic surveil-lance for sepsis, and evidence based point of care alerting using the POC AdvisorTM application. Methods: 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.

Results: 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. Conclusion: 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.

Keywords

Sepsis - clinical decision support - electronic surveillance - sepsis outcomes - informatics

Full Text

References

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