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Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact
INTRODUCTION: For early detection of sepsis, automated systems within the electronic health record have evolved to alert emergency department (ED) personnel to the possibility of sepsis, and in some cases link them to suggested care pathways. We conducted a systematic review of automated sepsis-aler...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Department of Emergency Medicine, University of California, Irvine School of Medicine
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514413/ https://www.ncbi.nlm.nih.gov/pubmed/32970576 http://dx.doi.org/10.5811/westjem.2020.5.46010 |
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author | Hwang, Matthew I. Bond, William F. Powell, Emilie S. |
author_facet | Hwang, Matthew I. Bond, William F. Powell, Emilie S. |
author_sort | Hwang, Matthew I. |
collection | PubMed |
description | INTRODUCTION: For early detection of sepsis, automated systems within the electronic health record have evolved to alert emergency department (ED) personnel to the possibility of sepsis, and in some cases link them to suggested care pathways. We conducted a systematic review of automated sepsis-alert detection systems in the ED. METHODS: We searched multiple health literature databases from the earliest available dates to August 2018. Articles were screened based on abstract, again via manuscript, and further narrowed with set inclusion criteria: 1) adult patients in the ED diagnosed with sepsis, severe sepsis, or septic shock; 2) an electronic system that alerts a healthcare provider of sepsis in real or near-real time; and 3) measures of diagnostic accuracy or quality of sepsis alerts. The final, detailed review was guided by QUADAS-2 and GRADE criteria. We tracked all articles using an online tool (Covidence), and the review was registered with PROSPERO registry of reviews. A two-author consensus was reached at the article choice stage and final review stage. Due to the variation in alert criteria and methods of sepsis diagnosis confirmation, the data were not combined for meta-analysis. RESULTS: We screened 693 articles by title and abstract and 20 by full text; we then selected 10 for the study. The articles were published between 2009–2018. Two studies had algorithm-based alert systems, while eight had rule-based alert systems. All systems used different criteria based on systemic inflammatory response syndrome (SIRS) to define sepsis. Sensitivities ranged from 10–100%, specificities from 78–99%, and positive predictive value from 5.8–54%. Negative predictive value was consistently high at 99–100%. Studies showed some evidence for improved process-of-care markers, including improved time to antibiotics. Length of stay improved in two studies. One low quality study showed improved mortality. CONCLUSION: The limited evidence available suggests that sepsis alerts in the ED setting can be set to high sensitivity. No high-quality studies showed a difference in mortality, but evidence exists for improvements in process of care. Significant further work is needed to understand the consequences of alert fatigue and sensitivity set points. |
format | Online Article Text |
id | pubmed-7514413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Department of Emergency Medicine, University of California, Irvine School of Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-75144132020-09-29 Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact Hwang, Matthew I. Bond, William F. Powell, Emilie S. West J Emerg Med Emergency Department Operations INTRODUCTION: For early detection of sepsis, automated systems within the electronic health record have evolved to alert emergency department (ED) personnel to the possibility of sepsis, and in some cases link them to suggested care pathways. We conducted a systematic review of automated sepsis-alert detection systems in the ED. METHODS: We searched multiple health literature databases from the earliest available dates to August 2018. Articles were screened based on abstract, again via manuscript, and further narrowed with set inclusion criteria: 1) adult patients in the ED diagnosed with sepsis, severe sepsis, or septic shock; 2) an electronic system that alerts a healthcare provider of sepsis in real or near-real time; and 3) measures of diagnostic accuracy or quality of sepsis alerts. The final, detailed review was guided by QUADAS-2 and GRADE criteria. We tracked all articles using an online tool (Covidence), and the review was registered with PROSPERO registry of reviews. A two-author consensus was reached at the article choice stage and final review stage. Due to the variation in alert criteria and methods of sepsis diagnosis confirmation, the data were not combined for meta-analysis. RESULTS: We screened 693 articles by title and abstract and 20 by full text; we then selected 10 for the study. The articles were published between 2009–2018. Two studies had algorithm-based alert systems, while eight had rule-based alert systems. All systems used different criteria based on systemic inflammatory response syndrome (SIRS) to define sepsis. Sensitivities ranged from 10–100%, specificities from 78–99%, and positive predictive value from 5.8–54%. Negative predictive value was consistently high at 99–100%. Studies showed some evidence for improved process-of-care markers, including improved time to antibiotics. Length of stay improved in two studies. One low quality study showed improved mortality. CONCLUSION: The limited evidence available suggests that sepsis alerts in the ED setting can be set to high sensitivity. No high-quality studies showed a difference in mortality, but evidence exists for improvements in process of care. Significant further work is needed to understand the consequences of alert fatigue and sensitivity set points. Department of Emergency Medicine, University of California, Irvine School of Medicine 2020-09 2020-08-24 /pmc/articles/PMC7514413/ /pubmed/32970576 http://dx.doi.org/10.5811/westjem.2020.5.46010 Text en Copyright: © 2020 Hwang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Emergency Department Operations Hwang, Matthew I. Bond, William F. Powell, Emilie S. Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title | Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title_full | Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title_fullStr | Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title_full_unstemmed | Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title_short | Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact |
title_sort | sepsis alerts in emergency departments: a systematic review of accuracy and quality measure impact |
topic | Emergency Department Operations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514413/ https://www.ncbi.nlm.nih.gov/pubmed/32970576 http://dx.doi.org/10.5811/westjem.2020.5.46010 |
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