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A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study
OBJECTIVE: To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. DESIGN: Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. Th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SAGE Publications
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4601128/ https://www.ncbi.nlm.nih.gov/pubmed/26688744 http://dx.doi.org/10.1177/2054270415609004 |
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author | Amland, Robert C Lyons, Jason J Greene, Tracy L Haley, James M |
author_facet | Amland, Robert C Lyons, Jason J Greene, Tracy L Haley, James M |
author_sort | Amland, Robert C |
collection | PubMed |
description | OBJECTIVE: To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. DESIGN: Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients’ designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. SETTING: Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. PARTICIPANTS: Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. MAIN OUTCOME MEASURE: ‘Suspected infection’ was the established gold standard to assess clinical decision support clinimetric performance. RESULTS: A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying ‘suspected infection’ as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. CONCLUSION: A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis. |
format | Online Article Text |
id | pubmed-4601128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-46011282015-12-18 A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study Amland, Robert C Lyons, Jason J Greene, Tracy L Haley, James M JRSM Open Research OBJECTIVE: To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. DESIGN: Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients’ designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. SETTING: Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. PARTICIPANTS: Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. MAIN OUTCOME MEASURE: ‘Suspected infection’ was the established gold standard to assess clinical decision support clinimetric performance. RESULTS: A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying ‘suspected infection’ as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. CONCLUSION: A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis. SAGE Publications 2015-10-08 /pmc/articles/PMC4601128/ /pubmed/26688744 http://dx.doi.org/10.1177/2054270415609004 Text en © The Author(s) 2015 http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Research Amland, Robert C Lyons, Jason J Greene, Tracy L Haley, James M A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title | A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title_full | A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title_fullStr | A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title_full_unstemmed | A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title_short | A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
title_sort | two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4601128/ https://www.ncbi.nlm.nih.gov/pubmed/26688744 http://dx.doi.org/10.1177/2054270415609004 |
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