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PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study

INTRODUCTION: Survivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25–30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated with unplanned readmission; develop a risk mode...

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Autores principales: Walsh, Timothy S, Salisbury, Lisa, Donaghy, Eddie, Ramsay, Pamela, Lee, Robert, Rattray, Janice, Lone, Nazir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4932276/
https://www.ncbi.nlm.nih.gov/pubmed/27354086
http://dx.doi.org/10.1136/bmjopen-2016-012590
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author Walsh, Timothy S
Salisbury, Lisa
Donaghy, Eddie
Ramsay, Pamela
Lee, Robert
Rattray, Janice
Lone, Nazir
author_facet Walsh, Timothy S
Salisbury, Lisa
Donaghy, Eddie
Ramsay, Pamela
Lee, Robert
Rattray, Janice
Lone, Nazir
author_sort Walsh, Timothy S
collection PubMed
description INTRODUCTION: Survivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25–30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated with unplanned readmission; develop a risk model to identify intensive care unit (ICU) survivors at highest readmission risk; understand the modifiable and non-modifiable readmission drivers; and develop a risk assessment tool for identifying patients and areas for early intervention. METHODS AND ANALYSIS: We will use mixed methods with concurrent data collection. Quantitative data will comprise linked healthcare records for adult Scottish residents requiring ICU admission (1 January 2000–31 December 2013) who survived to hospital discharge. The outcome will be unplanned emergency readmission within 90 days of index hospital discharge. Exposures will include pre-ICU demographic data, comorbidities and health status, and critical illness variables representing illness severity. Regression analyses will be used to identify factors associated with increased readmission risk, and to develop and validate a risk prediction model. Qualitative data will comprise recorded/transcribed interviews with up to 60 patients and carers recently experiencing unplanned readmissions in three health board regions. A deductive and inductive thematic analysis will be used to identify factors contributing to readmissions and how they may interact. Through iterative triangulation of quantitative and qualitative data, we will develop a construct/taxonomy that captures reasons and drivers for unplanned readmission. We will validate and further refine this in focus groups with patients/carers who experienced readmissions in six Scottish health board regions, and in consultation with an independent expert group. A tool will be developed to screen for ICU survivors at risk of readmission and inform anticipatory interventions. ETHICS AND DISSEMINATION: Data linkage has approval but does not require ethical approval. The qualitative study has ethical approval. Dissemination with key healthcare stakeholders and policymakers is planned. TRIAL REGISTRATION NUMBER: UKCRN18023.
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spelling pubmed-49322762016-07-12 PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study Walsh, Timothy S Salisbury, Lisa Donaghy, Eddie Ramsay, Pamela Lee, Robert Rattray, Janice Lone, Nazir BMJ Open Intensive Care INTRODUCTION: Survivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25–30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated with unplanned readmission; develop a risk model to identify intensive care unit (ICU) survivors at highest readmission risk; understand the modifiable and non-modifiable readmission drivers; and develop a risk assessment tool for identifying patients and areas for early intervention. METHODS AND ANALYSIS: We will use mixed methods with concurrent data collection. Quantitative data will comprise linked healthcare records for adult Scottish residents requiring ICU admission (1 January 2000–31 December 2013) who survived to hospital discharge. The outcome will be unplanned emergency readmission within 90 days of index hospital discharge. Exposures will include pre-ICU demographic data, comorbidities and health status, and critical illness variables representing illness severity. Regression analyses will be used to identify factors associated with increased readmission risk, and to develop and validate a risk prediction model. Qualitative data will comprise recorded/transcribed interviews with up to 60 patients and carers recently experiencing unplanned readmissions in three health board regions. A deductive and inductive thematic analysis will be used to identify factors contributing to readmissions and how they may interact. Through iterative triangulation of quantitative and qualitative data, we will develop a construct/taxonomy that captures reasons and drivers for unplanned readmission. We will validate and further refine this in focus groups with patients/carers who experienced readmissions in six Scottish health board regions, and in consultation with an independent expert group. A tool will be developed to screen for ICU survivors at risk of readmission and inform anticipatory interventions. ETHICS AND DISSEMINATION: Data linkage has approval but does not require ethical approval. The qualitative study has ethical approval. Dissemination with key healthcare stakeholders and policymakers is planned. TRIAL REGISTRATION NUMBER: UKCRN18023. BMJ Publishing Group 2016-06-28 /pmc/articles/PMC4932276/ /pubmed/27354086 http://dx.doi.org/10.1136/bmjopen-2016-012590 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Intensive Care
Walsh, Timothy S
Salisbury, Lisa
Donaghy, Eddie
Ramsay, Pamela
Lee, Robert
Rattray, Janice
Lone, Nazir
PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title_full PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title_fullStr PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title_full_unstemmed PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title_short PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
title_sort preventing early unplanned hospital readmission after critical illness (profile): protocol and analysis framework for a mixed methods study
topic Intensive Care
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4932276/
https://www.ncbi.nlm.nih.gov/pubmed/27354086
http://dx.doi.org/10.1136/bmjopen-2016-012590
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