The Epic Sepsis Model Falls Short — The Importance of External Validation

The ESM did not identify 67% of patients with sepsis, 

despite generating alerts for an ESM score of 6 or higher for 18% of hospitalized patients, thus creating a large burden of alert fatigue.


JAMA Network, Editorial
Anand R. Habib, MD, MPhil1,2; Anthony L. Lin, MD1; Richard W. Grant, MD, MPH3,4
June 21, 2021
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Sepsis accounts for nearly 1 million hospitalizations annually and is a major contributor to hospital length of stay, health care expenditures, and in-hospital mortality (ranging from 12.5%-15%).1 

Early sepsis identification allows care teams to promptly implement goal-directed therapy to mitigate clinical deterioration.

In this issue of JAMA Internal Medicine, Wong et al2 report on their external validation of the Epic Sepsis Model (ESM), a prediction tool available within the Epic electronic health record that is designed to generate automated alerts that warn clinicians that patients may be developing sepsis. 

Based on their examination of 38 455 hospitalizations at the University of Michigan (Ann Arbor) between December 2018 and October 2019, Wong et al2 found that the ESM had a sensitivity of 33%, specificity of 83%, positive predictive value of 12%, and negative predictive value of 95%, with an area under the curve of 0.63 (95% CI, 0.62–0.64). 

This falls short of the area under the curve of 0.76 to 0.83 that was jointly reported by Epic and University of Colorado Health.3 

Despite generating alerts on 18% of all patients, the ESM did not detect sepsis in 67% of patients with sepsis.


Originally published https://jamanetwork.com

About the authors


Anand R. Habib, MD, MPhil1,2

Anthony L. Lin, MD1
Richard W. Grant, MD, MPH3,4

1 Department of Medicine, 
University of California, San Francisco

2 Editorial Fellow, 
JAMA Internal Medicine

3 Division of Research, 
Kaiser Permanente Northern California, Oakland

4 Associate Editor, 
JAMA Internal Medicine


ORIGINAL PUBLICATION 

External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients


JAMA Network

Andrew Wong, MD1; Erkin Otles, MEng2,3; John P. Donnelly, PhD4; et alAndrew Krumm, PhD4; Jeffrey McCullough, PhD5; Olivia DeTroyer-Cooley, BSE6; Justin Pestrue, MEcon6; Marie Phillips, BA7; Judy Konye, MSN, RN8; Carleen Penoza, MHSA, RN8; Muhammad Ghous, MBBS4; Karandeep Singh, MD, MMSc1,4

June 21, 2021

KEY POINTS


Question
 


How accurately does the Epic Sepsis Model, a proprietary sepsis prediction model implemented at hundreds of US hospitals, predict the onset of sepsis?

Findings 


In this cohort study of 27 697 patients undergoing 38 455 hospitalizations, sepsis occurred in 7% of the hosptalizations. The Epic Sepsis Model predicted the onset of sepsis with an area under the curve of 0.63, which is substantially worse than the performance reported by its developer.

Meaning 

This study suggests that the Epic Sepsis Model poorly predicts sepsis; its widespread adoption despite poor performance raises fundamental concerns about sepsis management on a national level.


ABSTRACT

Importance 


The Epic Sepsis Model (ESM), a proprietary sepsis prediction model, is implemented at hundreds of US hospitals. The ESM’s ability to identify patients with sepsis has not been adequately evaluated despite widespread use.


The Epic Sepsis Model (ESM), a proprietary sepsis prediction model, is implemented at hundreds of US hospitals. The ESM’s ability to identify patients with sepsis has not been adequately evaluated despite widespread use.

Objective 


To externally validate the ESM in the prediction of sepsis and evaluate its potential clinical value compared with usual care.


Design, Setting, and Participants 


This retrospective cohort study was conducted among 27 697 patients aged 18 years or older admitted to Michigan Medicine, the academic health system of the University of Michigan, Ann Arbor, with 38 455 hospitalizations between December 6, 2018, and October 20, 2019.


Exposure 


The ESM score, calculated every 15 minutes.


Main Outcomes and Measures 


Sepsis, as defined by a composite of (1) the Centers for Disease Control and Prevention surveillance criteria and (2) International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnostic codes accompanied by 2 systemic inflammatory response syndrome criteria and 1 organ dysfunction criterion within 6 hours of one another. 

Model discrimination was assessed using the area under the receiver operating characteristic curve at the hospitalization level and with prediction horizons of 4, 8, 12, and 24 hours. 

Model calibration was evaluated with calibration plots. The potential clinical benefit associated with the ESM was assessed by evaluating the added benefit of the ESM score compared with contemporary clinical practice (based on timely administration of antibiotics). 

Alert fatigue was evaluated by comparing the clinical value of different alerting strategies.


Results 


We identified 27 697 patients who had 38 455 hospitalizations (21 904 women [57%]; median age, 56 years [interquartile range, 35–69 years]) meeting inclusion criteria, of whom sepsis occurred in 2552 (7%). 

The ESM had a hospitalization-level area under the receiver operating characteristic curve of 0.63 (95% CI, 0.62–0.64). 

The ESM identified 183 of 2552 patients with sepsis (7%) who did not receive timely administration of antibiotics, highlighting the low sensitivity of the ESM in comparison with contemporary clinical practice. 

The ESM also did not identify 1709 patients with sepsis (67%) despite generating alerts for an ESM score of 6 or higher for 6971 of all 38 455 hospitalized patients (18%), thus creating a large burden of alert fatigue.


The ESM also did not identify 1709 patients with sepsis (67%) despite generating alerts for an ESM score of 6 or higher for 6971 of all 38 455 hospitalized patients (18%), thus creating a large burden of alert fatigue.


Group-B Streptococcus - Sepsis

Conclusions and Relevance 


This external validation cohort study suggests that the ESM has poor discrimination and calibration in predicting the onset of sepsis. 

The widespread adoption of the ESM despite its poor performance raises fundamental concerns about sepsis management on a national level.


This external validation cohort study suggests that the ESM has poor discrimination and calibration in predicting the onset of sepsis.

The widespread adoption of the ESM despite its poor performance raises fundamental concerns about sepsis management on a national level.


About the authors


Andrew Wong, MD1; Erkin Otles, MEng2,3; John P. Donnelly, PhD4; Andrew Krumm, PhD4; Jeffrey McCullough, PhD5; Olivia DeTroyer-Cooley, BSE6; Justin Pestrue, MEcon6; Marie Phillips, BA7; Judy Konye, MSN, RN8; Carleen Penoza, MHSA, RN8; Muhammad Ghous, MBBS4; Karandeep Singh, MD, MMSc1,4

Author Affiliations

1Department of Internal Medicine, 
University of Michigan Medical School, Ann Arbor

2Medical Scientist Training Program, University of Michigan Medical School, Ann Arbor

3Department of Industrial and Operations Engineering, University of Michigan College of Engineering, Ann Arbor

4Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor

5School of Public Health, University of Michigan, Ann Arbor

6Department of Quality, 
Michigan Medicine, Ann Arbor

7Health Information Technology and Services, Michigan Medicine, Ann Arbor

8Nursing Informatics, Michigan Medicine, Ann Arbor

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