Dataset Information

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.

ABSTRACT:

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.

SUBMITTER: Malycha J

PROVIDER: S-EPMC6747664 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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 J Redfern Oliver C OC Ludbrook Guy G Young Duncan D Watkinson Peter J PJ

BMJ open 20190911 9

<h4>Introduction</h4>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 admissio ...[more]

PMID: 31511294

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Project description:PurposeTo systematically review and evaluate the effectiveness of interventions in order to improve the safety and efficiency of patient handover between intensive care unit (ICU) and general ward healthcare professionals at ICU discharge.MethodsPubMed, CINAHL, PsycINFO, EMBASE, Web of Science, and the Cochrane Library were searched for intervention studies with the aim to improve clinical handover between ICU and general ward healthcare professionals that had been published up to and including June 2013. The methods for article inclusion and data analysis were pre-specified and aligned with recommendations outlined in the PRISMA guideline. Two reviewers independently extracted data (study purpose, setting, population, method of sampling, sample size, intervention characteristics, outcome, and implementation activities) and assessed the quality of the included studies.ResultsFrom the 6,591 citations initially extracted from the six databases, we included 11 studies in this review. Of these, six (55 %) reported statistically significant effects. Effective interventions included liaison nurses to improve communication and coordination of care and forms to facilitate timely, complete and accurate handover information. Effective interventions resulted in improved continuity of care (e.g., reduced discharge delay) and in reduced adverse events. Inconsistent effects were observed for use of care, namely, reduction of length of stay versus increase of readmissions to higher care. No statistically significant effects were found in the reduction of mortality. The overall methodological quality of the 11 studies reviewed was relatively low, with an average score of 4.5 out of 11 points.ConclusionsThis review shows that liaison nurses and handover forms are promising interventions to improve the quality of patient handover between the ICU and general ward. More robust evidence is needed on the effectiveness of interventions aiming to improve ICU handover and supportive implementation strategies.

Project description:ObjectivesEarly warning scores (EWS) alerting for in-hospital deterioration are commonly developed using routinely collected vital-sign data from the whole in-hospital population. As these in-hospital populations are dominated by those over the age of 45 years, resultant scores may perform less well in younger age groups. We developed and validated an age-specific early warning score (ASEWS) derived from statistical distributions of vital signs.DesignObservational cohort study.SettingOxford University Hospitals (OUH) July 2013 to March 2018 and Portsmouth Hospitals (PH) NHS Trust January 2010 to March 2017 within the Hospital Alerting Via Electronic Noticeboard database.ParticipantsHospitalised patients with electronically documented vital-sign observations OUTCOME: Composite outcome of unplanned intensive care unit admission, mortality and cardiac arrest.Methods and resultsStatistical distributions of vital signs were used to develop an ASEWS to predict the composite outcome within 24 hours. The OUH development set consisted of 2 538 099 vital-sign observation sets from 142 806 admissions (mean age (SD): 59.8 (20.3)). We compared the performance of ASEWS to the National Early Warning Score (NEWS) and our previous EWS (MCEWS) on an OUH validation set consisting of 581 571 observation sets from 25 407 emergency admissions (mean age (SD): 63.0 (21.4)) and a PH validation set consisting of 5 865 997 observation sets from 233 632 emergency admissions (mean age (SD): 64.3 (21.1)). ASEWS performed better in the 16-45 years age group in the OUH validation set (AUROC 0.820 (95% CI 0.815 to 0.824)) and PH validation set (AUROC 0.840 (95% CI 0.839 to 0.841)) than NEWS (AUROC 0.763 (95% CI 0.758 to 0.768) and AUROC 0.836 (95% CI 0.835 to 0.838) respectively) and MCEWS (AUROC 0.808 (95% CI 0.803 to 0.812) and AUROC 0.833 (95% CI 0.831 to 0.834) respectively). Differences in performance were not consistent in the elder age group.ConclusionsAccounting for age-related vital sign changes can more accurately detect deterioration in younger patients.

Dataset Information

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

Methods

Ethics and dissemination

Discussion

Trial registration number

Publications

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.

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