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Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration.
We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU.
A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a ‘static’ score of the patient’s condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient’s risk of deterioration throughout their hospital stay.
Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model.
A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort.
Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653).
We showed that a scoring system incorporating data from a patient’s stay in the ICU has better performance than commonly used EWS systems based on vital signs alone.
The COVID-19 pandemic has had both direct and indirect impacts on the health of populations worldwide. While racial/ethnic health inequities in COVID-19 infection are now well known (and ongoing), knowledge about the impact of COVID-19 pandemic management on non-COVID-19-related outcomes for Indigenous peoples is less well understood. This article presents the study protocol for the Health Research Council of New Zealand funded project ‘Mā te Mōhio ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities’. The study aims to explore changes in access to healthcare, quality of healthcare and health outcomes for Māori, the Indigenous peoples of Aotearoa New Zealand (NZ) and non-Māori during the COVID-19 outbreak period across NZ.
This observational study is framed within a Kaupapa Māori research positioning that includes Kaupapa Māori epidemiology. National datasets will be used to report on access to healthcare, quality of healthcare and health outcomes between Māori and non-Māori during the COVID-19 pandemic in NZ. Study periods are defined as (a) prepandemic period (2015–2019), (b) first pandemic year without COVID-19 vaccines (2020) and (c) pandemic period with COVID-19 vaccines (2021 onwards). Regional and national differences between Māori and non-Māori will be explored in two phases focused on identified health priority areas for NZ including (1) mortality, cancer, long-term conditions, first 1000 days, mental health and (2) rheumatic fever.
This study has ethical approval from the Auckland Health Research Ethics Committee (AHREC AH26253). An advisory group will work with the project team to disseminate the findings of this project via project-specific meetings, peer-reviewed publications and a project-specific website. The overall intention of the project is to highlight areas requiring health policy and practice interventions to address Indigenous inequities in health resulting from COVID-19 pandemic management (both historical and in the future).
To gain staff feedback on the implementation and impact of a novel ambulatory monitoring system to support coronavirus patient management on an isolation ward.
Qualitative service evaluation.
Semi-structured interviews were conducted with 15 multidisciplinary isolation ward staff in the United Kingdom between July 2020 and May 2021. Interviews were audio-recorded, transcribed and analysed using thematic analysis.
Adopting Innovation to Assist Patient Safety was identified as the overriding theme. Three interlinked sub-themes represent facets of how the system supported patient safety. Patient Selection was developed throughout the pandemic, as clinical staff became more confident in choosing which patients would benefit most. Trust In the System described how nurses coped with discrepancies between the ambulatory system and ward observation machines. Finally, Resource Management examined how, once trust was built, staff perceived the ambulatory system assisted with caseload management. This supported efficient personal protective equipment resource use by reducing the number of isolation room entries. Despite these reported benefits, face-to-face contact was still highly valued, despite the risk of coronavirus exposure.
Hospital wards should consider using ambulatory monitoring systems to support caseload management and patient safety. Patients in isolation rooms or at high risk of deterioration may particularly benefit from this additional monitoring. However, these systems should be seen as an adjunct to nursing care, not a replacement.
Nurses valued ambulatory monitoring as a means of ensuring the safety of patients at risk of deterioration and prioritizing their workload.
The findings of this research will be useful to all those developing or considering implementation of ambulatory monitoring systems in hospital wards.
This manuscript follows the Consolidated criteria for Reporting Qualitative Research (COREQ) guidelines with inclusion of relevant SQUIRE guidelines for reporting quality improvement.
No Patient or Public Contribution.
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