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Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study

INTRODUCTION: Traditional early warning scores (EWSs) use vital sign derangements to detect clinical deterioration in patients treated on hospital wards. Combining vital signs with demographics and laboratory results improves EWS performance. We have developed the Hospital Alerting Via Electronic No...

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Autores principales: Malycha, James, Redfern, Oliver C, Ludbrook, Guy, Young, Duncan, Watkinson, Peter J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747664/
https://www.ncbi.nlm.nih.gov/pubmed/31511294
http://dx.doi.org/10.1136/bmjopen-2019-032429
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author Malycha, James
Redfern, Oliver C
Ludbrook, Guy
Young, Duncan
Watkinson, Peter J
author_facet Malycha, James
Redfern, Oliver C
Ludbrook, Guy
Young, Duncan
Watkinson, Peter J
author_sort Malycha, James
collection PubMed
description INTRODUCTION: Traditional early warning scores (EWSs) use vital sign derangements to detect clinical deterioration in patients treated on hospital wards. Combining vital signs with demographics and laboratory results improves EWS performance. We have developed the Hospital Alerting Via Electronic Noticeboard (HAVEN) system. HAVEN uses vital signs, as well as demographic, comorbidity and laboratory data from the electronic patient record, to quantify and rank the risk of unplanned admission to an intensive care unit (ICU) within 24 hours for all ward patients. The primary aim of this study is to find additional variables, potentially missed during development, which may improve HAVEN performance. These variables will be sought in the medical record of patients misclassified by the HAVEN risk score during testing. METHODS: This will be a prospective, observational, cohort study conducted at the John Radcliffe Hospital, part of the Oxford University Hospitals NHS Foundation Trust in the UK. Each day during the study periods, we will document all highly ranked patients (ie, those with the highest risk for unplanned ICU admission) identified by the HAVEN system. After 48 hours, we will review the progress of the identified patients. Patients who were subsequently admitted to the ICU will be removed from the study (as they will have been correctly classified by HAVEN). Highly ranked patients not admitted to ICU will undergo a structured medical notes review. Additionally, at the end of the study periods, all patients who had an unplanned ICU admission but whom HAVEN failed to rank highly will have a structured medical notes review. The review will identify candidate variables, likely associated with unplanned ICU admission, not included in the HAVEN risk score. ETHICS AND DISSEMINATION: Approval has been granted for gathering the data used in this study from the South Central Oxford C Research Ethics Committee (16/SC/0264, 13 June 2016) and the Confidentiality Advisory Group (16/CAG/0066). DISCUSSION: Our study will use a clinical expert conducting a structured medical notes review to identify variables, associated with unplanned ICU admission, not included in the development of the HAVEN risk score. These variables will then be added to the risk score and evaluated for potential performance gain. To the best of our knowledge, this is the first study of this type. We anticipate that documenting the HAVEN development methods will assist other research groups developing similar technology. TRIAL REGISTRATION NUMBER: ISRCTN12518261
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spelling pubmed-67476642019-09-27 Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study Malycha, James Redfern, Oliver C Ludbrook, Guy Young, Duncan Watkinson, Peter J BMJ Open Intensive Care INTRODUCTION: Traditional early warning scores (EWSs) use vital sign derangements to detect clinical deterioration in patients treated on hospital wards. Combining vital signs with demographics and laboratory results improves EWS performance. We have developed the Hospital Alerting Via Electronic Noticeboard (HAVEN) system. HAVEN uses vital signs, as well as demographic, comorbidity and laboratory data from the electronic patient record, to quantify and rank the risk of unplanned admission to an intensive care unit (ICU) within 24 hours for all ward patients. The primary aim of this study is to find additional variables, potentially missed during development, which may improve HAVEN performance. These variables will be sought in the medical record of patients misclassified by the HAVEN risk score during testing. METHODS: This will be a prospective, observational, cohort study conducted at the John Radcliffe Hospital, part of the Oxford University Hospitals NHS Foundation Trust in the UK. Each day during the study periods, we will document all highly ranked patients (ie, those with the highest risk for unplanned ICU admission) identified by the HAVEN system. After 48 hours, we will review the progress of the identified patients. Patients who were subsequently admitted to the ICU will be removed from the study (as they will have been correctly classified by HAVEN). Highly ranked patients not admitted to ICU will undergo a structured medical notes review. Additionally, at the end of the study periods, all patients who had an unplanned ICU admission but whom HAVEN failed to rank highly will have a structured medical notes review. The review will identify candidate variables, likely associated with unplanned ICU admission, not included in the HAVEN risk score. ETHICS AND DISSEMINATION: Approval has been granted for gathering the data used in this study from the South Central Oxford C Research Ethics Committee (16/SC/0264, 13 June 2016) and the Confidentiality Advisory Group (16/CAG/0066). DISCUSSION: Our study will use a clinical expert conducting a structured medical notes review to identify variables, associated with unplanned ICU admission, not included in the development of the HAVEN risk score. These variables will then be added to the risk score and evaluated for potential performance gain. To the best of our knowledge, this is the first study of this type. We anticipate that documenting the HAVEN development methods will assist other research groups developing similar technology. TRIAL REGISTRATION NUMBER: ISRCTN12518261 BMJ Publishing Group 2019-09-11 /pmc/articles/PMC6747664/ /pubmed/31511294 http://dx.doi.org/10.1136/bmjopen-2019-032429 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Intensive Care
Malycha, James
Redfern, Oliver C
Ludbrook, Guy
Young, Duncan
Watkinson, Peter J
Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title_full Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title_fullStr Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title_full_unstemmed Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title_short Testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
title_sort testing a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort study
topic Intensive Care
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747664/
https://www.ncbi.nlm.nih.gov/pubmed/31511294
http://dx.doi.org/10.1136/bmjopen-2019-032429
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