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Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department
BACKGROUND: Presentation of sepsis is dependent on synthesis of varied clinical information, making identification of septic patients challenging. Common practice is to identify sepsis through a manual screening tool, which may miss opportunities for early sepsis detection. Electronic screening effo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132749/ http://dx.doi.org/10.1097/pq9.0000000000000070 |
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author | Lloyd, Julia K. Ahrens, Erin A. Clark, Donnie Nuss, Kathryn E. |
author_facet | Lloyd, Julia K. Ahrens, Erin A. Clark, Donnie Nuss, Kathryn E. |
author_sort | Lloyd, Julia K. |
collection | PubMed |
description | BACKGROUND: Presentation of sepsis is dependent on synthesis of varied clinical information, making identification of septic patients challenging. Common practice is to identify sepsis through a manual screening tool, which may miss opportunities for early sepsis detection. Electronic screening efforts requiring additional documentation by providers may not integrate easily into provider workflow. OBJECTIVES: To develop an automated sepsis risk screening tool in the electronic health record that would accurately identify patients at risk for sepsis without requiring additional documentation. METHODS: Criteria in the manual screening tool were mapped to standard documentation routinely entered in the electronic health record (Epic Systems, Corp.). Data elements were scored electronically at arrival and every 15 minutes during their encounter from the medical history, medication record, vital signs, and physical assessment (Fig. 1). Scores that exceeded a predefined sepsis risk threshold triggered a Best Practice Advisory, which alerted bedside staff to perform sepsis huddles and consider appropriate interventions. Statistical comparison of the automated tool to the manual process was completed by two-tail paired t test. RESULTS: In an 8-week testing period, the automated sepsis risk screening tool identified 100% of patients flagged by the manual process (N = 29) (Table 1). The electronic tool identified sepsis patients, on average, 68 minutes earlier. This was statistically significant (P < 0.001). CONCLUSIONS/IMPLICATIONS: The automated sepsis risk screening tool is as accurate as a validated manual process and alerted bedside clinicians earlier. Deployment has potential to improve timely sepsis detection and management of patients without requiring additional documentation by provider. |
format | Online Article Text |
id | pubmed-6132749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-61327492018-10-02 Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department Lloyd, Julia K. Ahrens, Erin A. Clark, Donnie Nuss, Kathryn E. Pediatr Qual Saf Symposium Proceedings: Improving Pediatric Sepsis Outcomes Colloquium – Dallas TX, December 2017 BACKGROUND: Presentation of sepsis is dependent on synthesis of varied clinical information, making identification of septic patients challenging. Common practice is to identify sepsis through a manual screening tool, which may miss opportunities for early sepsis detection. Electronic screening efforts requiring additional documentation by providers may not integrate easily into provider workflow. OBJECTIVES: To develop an automated sepsis risk screening tool in the electronic health record that would accurately identify patients at risk for sepsis without requiring additional documentation. METHODS: Criteria in the manual screening tool were mapped to standard documentation routinely entered in the electronic health record (Epic Systems, Corp.). Data elements were scored electronically at arrival and every 15 minutes during their encounter from the medical history, medication record, vital signs, and physical assessment (Fig. 1). Scores that exceeded a predefined sepsis risk threshold triggered a Best Practice Advisory, which alerted bedside staff to perform sepsis huddles and consider appropriate interventions. Statistical comparison of the automated tool to the manual process was completed by two-tail paired t test. RESULTS: In an 8-week testing period, the automated sepsis risk screening tool identified 100% of patients flagged by the manual process (N = 29) (Table 1). The electronic tool identified sepsis patients, on average, 68 minutes earlier. This was statistically significant (P < 0.001). CONCLUSIONS/IMPLICATIONS: The automated sepsis risk screening tool is as accurate as a validated manual process and alerted bedside clinicians earlier. Deployment has potential to improve timely sepsis detection and management of patients without requiring additional documentation by provider. Wolters Kluwer Health 2018-04-17 /pmc/articles/PMC6132749/ http://dx.doi.org/10.1097/pq9.0000000000000070 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Symposium Proceedings: Improving Pediatric Sepsis Outcomes Colloquium – Dallas TX, December 2017 Lloyd, Julia K. Ahrens, Erin A. Clark, Donnie Nuss, Kathryn E. Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title | Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title_full | Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title_fullStr | Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title_full_unstemmed | Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title_short | Automation of a Paper-based Screening Tool for Early Sepsis Risk Detection in the Emergency Department |
title_sort | automation of a paper-based screening tool for early sepsis risk detection in the emergency department |
topic | Symposium Proceedings: Improving Pediatric Sepsis Outcomes Colloquium – Dallas TX, December 2017 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132749/ http://dx.doi.org/10.1097/pq9.0000000000000070 |
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