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
<p><strong>Introduction</strong> 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 th...
| Autores principales: | , , , , |
|---|---|
| Formato: | Journal article |
| Lenguaje: | English |
| Publicado: |
BMJ Publishing Group
2019
|
| _version_ | 1826304345578143744 |
|---|---|
| author | Malycha, J Redfern, OC Ludbrook, G Young, D Watkinson, PJ |
| author_facet | Malycha, J Redfern, OC Ludbrook, G Young, D Watkinson, PJ |
| author_sort | Malycha, J |
| collection | OXFORD |
| description | <p><strong>Introduction</strong> 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.</p> <p><strong>Methods</strong> 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 <em>admitted</em> to the ICU will be removed from the study (as they will have been correctly classified by HAVEN). Highly ranked patients <em>not admitted</em> 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 <em>failed to rank highly</em> 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.</p> <p><strong>Ethics and dissemination</strong> 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).</p> <p><strong>Discussion</strong> 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.</p> <p><strong>Trial registration number</strong> ISRCTN12518261</p> |
| first_indexed | 2024-03-07T06:16:24Z |
| format | Journal article |
| id | oxford-uuid:f137bd14-8bbb-45d6-b68a-2ec1824b77d9 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:16:24Z |
| publishDate | 2019 |
| publisher | BMJ Publishing Group |
| record_format | dspace |
| spelling | oxford-uuid:f137bd14-8bbb-45d6-b68a-2ec1824b77d92022-03-27T11:54:22ZTesting a digital system that ranks the risk of unplanned intensive care unit admission in all ward patients: protocol for a prospective observational cohort studyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:f137bd14-8bbb-45d6-b68a-2ec1824b77d9EnglishSymplectic Elements at OxfordBMJ Publishing Group2019Malycha, JRedfern, OCLudbrook, GYoung, DWatkinson, PJ<p><strong>Introduction</strong> 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.</p> <p><strong>Methods</strong> 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 <em>admitted</em> to the ICU will be removed from the study (as they will have been correctly classified by HAVEN). Highly ranked patients <em>not admitted</em> 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 <em>failed to rank highly</em> 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.</p> <p><strong>Ethics and dissemination</strong> 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).</p> <p><strong>Discussion</strong> 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.</p> <p><strong>Trial registration number</strong> ISRCTN12518261</p> |
| spellingShingle | Malycha, J Redfern, OC Ludbrook, G Young, D Watkinson, PJ 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 |
| work_keys_str_mv | AT malychaj testingadigitalsystemthatrankstheriskofunplannedintensivecareunitadmissioninallwardpatientsprotocolforaprospectiveobservationalcohortstudy AT redfernoc testingadigitalsystemthatrankstheriskofunplannedintensivecareunitadmissioninallwardpatientsprotocolforaprospectiveobservationalcohortstudy AT ludbrookg testingadigitalsystemthatrankstheriskofunplannedintensivecareunitadmissioninallwardpatientsprotocolforaprospectiveobservationalcohortstudy AT youngd testingadigitalsystemthatrankstheriskofunplannedintensivecareunitadmissioninallwardpatientsprotocolforaprospectiveobservationalcohortstudy AT watkinsonpj testingadigitalsystemthatrankstheriskofunplannedintensivecareunitadmissioninallwardpatientsprotocolforaprospectiveobservationalcohortstudy |