Implementation and evaluation of sepsis surveillance and decision support in medical ICU and emergency department

Kirill Lipatov; Craig E Daniels; John G Park; Jennifer Elmer; Andrew C Hanson; Bo E Madsen; Casey M Clements; Ognjen Gajic; Brian W Pickering; Vitaly Herasevich

doi:10.1016/j.ajem.2021.09.086

Implementation and evaluation of sepsis surveillance and decision support in medical ICU and emergency department

Am J Emerg Med. 2022 Jan:51:378-383. doi: 10.1016/j.ajem.2021.09.086. Epub 2021 Nov 11.

Authors

Affiliations

¹ Department of Pulmonary and Critical Care Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
² Department of Nursing, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
³ Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
⁴ Department of Emergency Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
⁵ Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
⁶ Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA. Electronic address: [email protected].

PMID: 34823194
DOI: 10.1016/j.ajem.2021.09.086

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.

Keywords: Data display; Informatics; Information technology; Sepsis; Shock; Surveillance.

Publication types

Observational Study

MeSH terms

Academic Medical Centers
Aged
Aged, 80 and over
Controlled Before-After Studies
Decision Support Systems, Clinical*
Emergency Service, Hospital / standards
Emergency Service, Hospital / statistics & numerical data*
Feedback
Female
Hospital Mortality
Humans
Intensive Care Units / standards
Intensive Care Units / supply & distribution*
Linear Models
Male
Middle Aged
Patient Care Bundles / standards
Retrospective Studies
Sentinel Surveillance
Sepsis / diagnosis*
Sepsis / mortality
Sepsis / therapy
Shock, Septic / diagnosis
Shock, Septic / mortality
Shock, Septic / therapy