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An electronic warning system helps reduce the time to diagnosis of sepsis

OBJECTIVE: To describe the improvements of an early warning system for the identification of septic patients on the time to diagnosis, antibiotic delivery, and mortality. METHODS: This was an observational cohort study that describes the successive improvements made over a period of 10 years using a...

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Autores principales: Westphal, Glauco Adrieno, Pereira, Aline Braz, Fachin, Silvia Maria, Sperotto, Geonice, Gonçalves, Maurício, Albino, Lucimeri, Bittencourt, Rodolfo, Franzini, Vanessa de Rossi, Koenig, Álvaro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Associação de Medicina Intensiva Brasileira - AMIB 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334482/
https://www.ncbi.nlm.nih.gov/pubmed/30570029
http://dx.doi.org/10.5935/0103-507X.20180059
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author Westphal, Glauco Adrieno
Pereira, Aline Braz
Fachin, Silvia Maria
Sperotto, Geonice
Gonçalves, Maurício
Albino, Lucimeri
Bittencourt, Rodolfo
Franzini, Vanessa de Rossi
Koenig, Álvaro
author_facet Westphal, Glauco Adrieno
Pereira, Aline Braz
Fachin, Silvia Maria
Sperotto, Geonice
Gonçalves, Maurício
Albino, Lucimeri
Bittencourt, Rodolfo
Franzini, Vanessa de Rossi
Koenig, Álvaro
author_sort Westphal, Glauco Adrieno
collection PubMed
description OBJECTIVE: To describe the improvements of an early warning system for the identification of septic patients on the time to diagnosis, antibiotic delivery, and mortality. METHODS: This was an observational cohort study that describes the successive improvements made over a period of 10 years using an early warning system to detect sepsis, including systematic active manual surveillance, electronic alerts via a telephonist, and alerts sent directly to the mobile devices of nurses. For all periods, after an alert was triggered, early treatment was instituted according to the institutional sepsis guidelines. RESULTS: In total, 637 patients with sepsis were detected over the study period. The median triage-to-diagnosis time was reduced from 19:20 (9:10 - 38:15) hours to 12:40 (2:50 - 23:45) hours when the manual surveillance method was used (p = 0.14), to 2:10 (1:25 - 2:20) hours when the alert was sent automatically to the hospital telephone service (p = 0.014), and to 1:00 (0:30 - 1:10) hour when the alert was sent directly to the nurse's mobile phone (p = 0.016). The diagnosis-to-antibiotic time was reduced to 1:00 (0:55 - 1:30) hours when the alert was sent to the telephonist and to 0:45 (0:30 - 1:00) minutes when the alert was sent directly to the nurse's mobile phone (p = 0.02), with the maintenance of similar values over the following years. There was no difference in the time of treatment between survivors and non-survivors. CONCLUSION: Electronic systems help reduce the triage-to-diagnosis time and diagnosis-to-antibiotic time in patients with sepsis.
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spelling pubmed-63344822019-01-24 An electronic warning system helps reduce the time to diagnosis of sepsis Westphal, Glauco Adrieno Pereira, Aline Braz Fachin, Silvia Maria Sperotto, Geonice Gonçalves, Maurício Albino, Lucimeri Bittencourt, Rodolfo Franzini, Vanessa de Rossi Koenig, Álvaro Rev Bras Ter Intensiva Original Article OBJECTIVE: To describe the improvements of an early warning system for the identification of septic patients on the time to diagnosis, antibiotic delivery, and mortality. METHODS: This was an observational cohort study that describes the successive improvements made over a period of 10 years using an early warning system to detect sepsis, including systematic active manual surveillance, electronic alerts via a telephonist, and alerts sent directly to the mobile devices of nurses. For all periods, after an alert was triggered, early treatment was instituted according to the institutional sepsis guidelines. RESULTS: In total, 637 patients with sepsis were detected over the study period. The median triage-to-diagnosis time was reduced from 19:20 (9:10 - 38:15) hours to 12:40 (2:50 - 23:45) hours when the manual surveillance method was used (p = 0.14), to 2:10 (1:25 - 2:20) hours when the alert was sent automatically to the hospital telephone service (p = 0.014), and to 1:00 (0:30 - 1:10) hour when the alert was sent directly to the nurse's mobile phone (p = 0.016). The diagnosis-to-antibiotic time was reduced to 1:00 (0:55 - 1:30) hours when the alert was sent to the telephonist and to 0:45 (0:30 - 1:00) minutes when the alert was sent directly to the nurse's mobile phone (p = 0.02), with the maintenance of similar values over the following years. There was no difference in the time of treatment between survivors and non-survivors. CONCLUSION: Electronic systems help reduce the triage-to-diagnosis time and diagnosis-to-antibiotic time in patients with sepsis. Associação de Medicina Intensiva Brasileira - AMIB 2018 /pmc/articles/PMC6334482/ /pubmed/30570029 http://dx.doi.org/10.5935/0103-507X.20180059 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Westphal, Glauco Adrieno
Pereira, Aline Braz
Fachin, Silvia Maria
Sperotto, Geonice
Gonçalves, Maurício
Albino, Lucimeri
Bittencourt, Rodolfo
Franzini, Vanessa de Rossi
Koenig, Álvaro
An electronic warning system helps reduce the time to diagnosis of sepsis
title An electronic warning system helps reduce the time to diagnosis of sepsis
title_full An electronic warning system helps reduce the time to diagnosis of sepsis
title_fullStr An electronic warning system helps reduce the time to diagnosis of sepsis
title_full_unstemmed An electronic warning system helps reduce the time to diagnosis of sepsis
title_short An electronic warning system helps reduce the time to diagnosis of sepsis
title_sort electronic warning system helps reduce the time to diagnosis of sepsis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334482/
https://www.ncbi.nlm.nih.gov/pubmed/30570029
http://dx.doi.org/10.5935/0103-507X.20180059
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