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Implementation and evaluation of sepsis surveillance and decision support in medical ICU and emergency department - 09/12/21

Doi : 10.1016/j.ajem.2021.09.086 
Kirill Lipatov, MD b, Craig E. Daniels, MD b, John G. Park, MD b, Jennifer Elmer, APRN, CNS, DNP c, Andrew C. Hanson d, Bo E. Madsen, MD, MPH e, Casey M. Clements, MD, PhD e, Ognjen Gajic, MD b, Brian W. Pickering, MB, BCh a, Vitaly Herasevich, MD a,
a Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA 
b Department of Pulmonary and Critical Care Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA 
c Department of Nursing, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA 
d Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA 
e Department of Emergency Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA 

Corresponding author.

Abstract

Objective

To improve the timely diagnosis and treatment of sepsis many institutions implemented automated sepsis alerts. Poor specificity, time delays, and a lack of actionable information lead to limited adoption by bedside clinicians and no change in practice or clinical outcomes. We aimed to compare sepsis care compliance before and after a multi-year implementation of a sepsis surveillance coupled with decision support in a tertiary care center.

Design

Single center before and after study.

Setting

Large academic Medical Intensive Care Unit (MICU) and Emergency Department (ED).

Population

Patients 18 years of age or older admitted to *** Hospital MICU and ED from 09/4/2011 to 05/01/2018 with severe sepsis or septic shock.

Interventions

Electronic medical record-based sepsis surveillance system augmented by clinical decision support and completion feedback.

Measurements and main results

There were 1950 patients admitted to the MICU with the diagnosis of severe sepsis or septic shock during the study period. The baseline characteristics were similar before (N = 854) and after (N = 1096) implementation of sepsis surveillance. The performance of the alert was modest with a sensitivity of 79.9%, specificity of 76.9%, positive predictive value (PPV) 27.9%, and negative predictive value (NPV) 97.2%. There were 3424 unique alerts and 1131 confirmed sepsis patients after the sniffer implementation. During the study period average care bundle compliance was higher; however after taking into account improvements in compliance leading up to the intervention, there was no association between intervention and improved care bundle compliance (Odds ratio: 1.16; 95% CI: 0.71 to 1.89; p-value 0.554). Similarly, the intervention was not associated with improvement in hospital mortality (Odds ratio: 1.55; 95% CI: 0.95 to 2.52; p-value: 0.078).

Conclusions

A sepsis surveillance system incorporating decision support or completion feedback was not associated with improved sepsis care and patient outcomes.

Il testo completo di questo articolo è disponibile in PDF.

Keywords : Sepsis, Shock, Informatics, Data display, Surveillance, Information technology


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© 2021  Pubblicato da Elsevier Masson SAS.
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Vol 51

P. 378-383 - Gennaio 2022 Ritorno al numero
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