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Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK.

ABSTRACT: To develop a clinical prediction model for poor outcome after intensive care unit (ICU) discharge in a large observational data set and couple this to an acute post-ICU ward-based review tool (PIRT) to identify high-risk patients at the time of ICU discharge and improve their acute ward-based review and outcome.Retrospective patient cohort of index ICU admissions between June 2006 and October 2011 receiving routine inpatient review. Prospective cohort between March 2012 and March 2013 underwent risk scoring (PIRT) which subsequently guided inpatient ward-based review.Two UK adult ICUs.4212 eligible discharges from ICU in the retrospective development cohort and 1028 patients included in the prospective intervention cohort.Multivariate analysis was performed to determine factors associated with poor outcome in the retrospective cohort and used to generate a discharge risk score. A discharge and daily ward-based review tool incorporating an adjusted risk score was introduced. The prospective cohort underwent risk scoring at ICU discharge and inpatient review using the PIRT.The primary outcome was the composite of death or readmission to ICU within 14 days of ICU discharge following the index ICU admission.PIRT review was achieved for 67.3% of all eligible discharges and improved the targeting of acute post-ICU review to high-risk patients. The presence of ward-based PIRT review in the prospective cohort did not correlate with a reduction in poor outcome overall (P=0.876) or overall readmission but did reduce early readmission (within the first 48?hours) from 4.5% to 3.6% (P=0.039), while increasing the rate of late readmission (48?hours to 14 days) from 2.7% to 5.8% (P=0.046).PIRT facilitates the appropriate targeting of nurse-led inpatient review acutely after ICU discharge but does not reduce hospital mortality or overall readmission rates to ICU.

SUBMITTER: Fabes J

PROVIDER: S-EPMC5770841 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK.

Fabes Jez J Seligman William W Barrett Carolyn C McKechnie Stuart S Griffiths John J

BMJ open 20171226 12

<h4>Objective</h4>To develop a clinical prediction model for poor outcome after intensive care unit (ICU) discharge in a large observational data set and couple this to an acute post-ICU ward-based review tool (PIRT) to identify high-risk patients at the time of ICU discharge and improve their acute ward-based review and outcome.<h4>Design</h4>Retrospective patient cohort of index ICU admissions between June 2006 and October 2011 receiving routine inpatient review. Prospective cohort between Mar ...[more]

PMID: 29282265

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Project description:BackgroundThe implementation of evidence-based interventions for people with dementia is complex and challenging. However, successful implementation might be a key element to ensure evidence-based practice and high quality of care. There is a need to improve implementation processes in dementia care by better understanding the arising challenges. Thus, the aim of this study was to identify recent knowledge concerning barriers and facilitators to implementing nurse-led interventions in dementia care.MethodsWe performed a scoping review using the methodological framework of Arksey and O'Malley. Studies explicitly reporting on the implementation process and factors influencing the implementation of a nurse-led intervention in dementia care in all settings were included. We searched eight databases from January 2015 until January 2019. Two authors independently selected the studies. For data analysis, we used an inductive approach to build domains and categories.ResultsWe included 26 studies in the review and identified barriers as well as facilitators in five domains: policy (e.g. financing issues, health insurance), organisation (e.g. organisational culture and vision, resources, management support), intervention/implementation (e.g. complexity of the intervention, perceived value of the intervention), staff (e.g. knowledge, experience and skills, attitude towards the intervention), and person with dementia/family (e.g. nature and stage of dementia, response of persons with dementia and their families).ConclusionsBesides general influencing factors for implementing nursing interventions, we identified dementia-specific factors reaching beyond already known barriers and facilitators. A pre-existing person-centred culture of care as well as consistent team cultures and attitudes have a facilitating effect on implementation processes. Furthermore, there is a need for interventions that are highly flexible and sensitive to patients' condition, needs and behaviour.

Project description:INTRODUCTION: The discharge of patients from the intensive care unit (ICU) to a hospital ward is a common transition of care that is associated with error and adverse events. Risk stratification tools may help identify high-risk patients for targeted interventions, but it is unclear if proper tools have been developed. METHODS: We searched Ovid EMBASE, Ovid MEDLINE, CINAHL, PUBMED and Cochrane Central Register of Controlled Trials from the earliest available date through March 2013, plus reference lists and citations of all studies included in the systematic review. Cohort studies were selected that described the derivation, validation or clinical impact of tools for predicting medical emergency team activation, ICU readmission or mortality following patient discharge from the ICU. Data were extracted on the study design, setting, population, sample size, tool (components, measurement properties) and outcomes. RESULTS: The literature search identified 9,926 citations, of which eight studies describing eight tools met the inclusion criteria. Reported outcomes included ICU readmission (n=4 studies), hospital mortality (n=3 studies) and both ICU readmission and hospital mortality (n=1 studies). Seven of the tools were comprised of distinct measurable component variables, while one tool used subjective scoring of patient risk by intensive care physicians. The areas under receiver operator curves were reported for all studies and ranged from 0.66 to 0.92. A single study provided a direct comparative analysis between two tools. We did not find any studies evaluating the impact of risk prediction on processes and outcomes of care. CONCLUSIONS: Eight risk stratification tools for predicting severe adverse events following patient discharge from ICU have been developed, but have undergone limited comparative evaluation. Although risk stratification tools may help clinician decision-making, further evaluation of the existing tools' effects on care is required prior to clinical implementation.

Dataset Information

Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK.

Publications

Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK.

Similar Datasets

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