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Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality
Objective: We created a system using a triad of change management, electronic surveillance, and algorithms to detect sepsis and deliver highly sensitive and specific decision support to the point of care using a mobile application. The investigators hypothesized that this system would result in a re...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654083/ https://www.ncbi.nlm.nih.gov/pubmed/27225197 http://dx.doi.org/10.1093/jamia/ocw056 |
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author | Manaktala, Sharad Claypool, Stephen R |
author_facet | Manaktala, Sharad Claypool, Stephen R |
author_sort | Manaktala, Sharad |
collection | PubMed |
description | Objective: We created a system using a triad of change management, electronic surveillance, and algorithms to detect sepsis and deliver highly sensitive and specific decision support to the point of care using a mobile application. The investigators hypothesized that this system would result in a reduction in sepsis mortality. Methods: A before-and-after model was used to study the impact of the interventions on sepsis-related mortality. All patients admitted to the study units were screened per the Institute for Healthcare Improvement Surviving Sepsis Guidelines using real-time electronic surveillance. Sepsis surveillance algorithms that adjusted clinical parameters based on comorbid medical conditions were deployed for improved sensitivity and specificity. Nurses received mobile alerts for all positive sepsis screenings as well as severe sepsis and shock alerts over a period of 10 months. Advice was given for early goal-directed therapy. Sepsis mortality during a control period from January 1, 2011 to September 30, 2013 was used as baseline for comparison. Results: The primary outcome, sepsis mortality, decreased by 53% (P = 0.03; 95% CI, 1.06-5.25). The 30-day readmission rate reduced from 19.08% during the control period to 13.21% during the study period (P = 0.05; 95% CI, 0.97-2.52). No significant change in length of hospital stay was noted. The system had observed sensitivity of 95% and specificity of 82% for detecting sepsis compared to gold-standard physician chart review. Conclusion: A program consisting of change management and electronic surveillance with highly sensitive and specific decision support delivered to the point of care resulted in significant reduction in deaths from sepsis. |
format | Online Article Text |
id | pubmed-7654083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76540832020-11-30 Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality Manaktala, Sharad Claypool, Stephen R J Am Med Inform Assoc Research and Applications Objective: We created a system using a triad of change management, electronic surveillance, and algorithms to detect sepsis and deliver highly sensitive and specific decision support to the point of care using a mobile application. The investigators hypothesized that this system would result in a reduction in sepsis mortality. Methods: A before-and-after model was used to study the impact of the interventions on sepsis-related mortality. All patients admitted to the study units were screened per the Institute for Healthcare Improvement Surviving Sepsis Guidelines using real-time electronic surveillance. Sepsis surveillance algorithms that adjusted clinical parameters based on comorbid medical conditions were deployed for improved sensitivity and specificity. Nurses received mobile alerts for all positive sepsis screenings as well as severe sepsis and shock alerts over a period of 10 months. Advice was given for early goal-directed therapy. Sepsis mortality during a control period from January 1, 2011 to September 30, 2013 was used as baseline for comparison. Results: The primary outcome, sepsis mortality, decreased by 53% (P = 0.03; 95% CI, 1.06-5.25). The 30-day readmission rate reduced from 19.08% during the control period to 13.21% during the study period (P = 0.05; 95% CI, 0.97-2.52). No significant change in length of hospital stay was noted. The system had observed sensitivity of 95% and specificity of 82% for detecting sepsis compared to gold-standard physician chart review. Conclusion: A program consisting of change management and electronic surveillance with highly sensitive and specific decision support delivered to the point of care resulted in significant reduction in deaths from sepsis. Oxford University Press 2017-01 2016-05-25 /pmc/articles/PMC7654083/ /pubmed/27225197 http://dx.doi.org/10.1093/jamia/ocw056 Text en © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research and Applications Manaktala, Sharad Claypool, Stephen R Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title | Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title_full | Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title_fullStr | Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title_full_unstemmed | Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title_short | Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
title_sort | evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654083/ https://www.ncbi.nlm.nih.gov/pubmed/27225197 http://dx.doi.org/10.1093/jamia/ocw056 |
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