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Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls

BACKGROUND: This retrospective study will assess the extent to which multidisciplinary case management in the form of virtual wards (VWs) leads to changes in the use of health care and social care by patients at high risk of future unplanned hospital admission. VWs use the staffing, systems and dail...

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Autores principales: Lewis, Geraint, Bardsley, Martin, Vaithianathan, Rhema, Steventon, Adam, Georghiou, Theo, Billings, John, Dixon, Jennifer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Igitur publishing 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3178802/
https://www.ncbi.nlm.nih.gov/pubmed/21949489
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author Lewis, Geraint
Bardsley, Martin
Vaithianathan, Rhema
Steventon, Adam
Georghiou, Theo
Billings, John
Dixon, Jennifer
author_facet Lewis, Geraint
Bardsley, Martin
Vaithianathan, Rhema
Steventon, Adam
Georghiou, Theo
Billings, John
Dixon, Jennifer
author_sort Lewis, Geraint
collection PubMed
description BACKGROUND: This retrospective study will assess the extent to which multidisciplinary case management in the form of virtual wards (VWs) leads to changes in the use of health care and social care by patients at high risk of future unplanned hospital admission. VWs use the staffing, systems and daily routines of a hospital ward to deliver coordinated care to patients in their own homes. Admission to a VW is offered to patients identified by a predictive risk model as being at high risk of unplanned hospital admission in the coming 12 months. STUDY DESIGN AND DATA COLLECTION METHODS: We will compare the health care and social care use of VW patients to that of matched controls. Controls will be drawn from (a) national, and (b) local, individual-level pseudonymous routine data. The costs of setting up and running a VW will be determined from the perspectives of both health and social care organizations using a combination of administrative data, interviews and diaries. METHODS OF ANALYSIS: Using propensity score matching and prognostic matching, we will create matched comparator groups to estimate the effect size of virtual wards in reducing unplanned hospital admissions. CONCLUSIONS: This study will allow us to determine relative to matched comparator groups: whether VWs reduce the use of emergency hospital care; the impact, if any, of VWs on the uptake of primary care, community health services and council-funded social care; and the potential costs and savings of VWs from the perspectives of the national health service (NHS) and local authorities.
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spelling pubmed-31788022011-09-23 Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls Lewis, Geraint Bardsley, Martin Vaithianathan, Rhema Steventon, Adam Georghiou, Theo Billings, John Dixon, Jennifer Int J Integr Care Research and Theory BACKGROUND: This retrospective study will assess the extent to which multidisciplinary case management in the form of virtual wards (VWs) leads to changes in the use of health care and social care by patients at high risk of future unplanned hospital admission. VWs use the staffing, systems and daily routines of a hospital ward to deliver coordinated care to patients in their own homes. Admission to a VW is offered to patients identified by a predictive risk model as being at high risk of unplanned hospital admission in the coming 12 months. STUDY DESIGN AND DATA COLLECTION METHODS: We will compare the health care and social care use of VW patients to that of matched controls. Controls will be drawn from (a) national, and (b) local, individual-level pseudonymous routine data. The costs of setting up and running a VW will be determined from the perspectives of both health and social care organizations using a combination of administrative data, interviews and diaries. METHODS OF ANALYSIS: Using propensity score matching and prognostic matching, we will create matched comparator groups to estimate the effect size of virtual wards in reducing unplanned hospital admissions. CONCLUSIONS: This study will allow us to determine relative to matched comparator groups: whether VWs reduce the use of emergency hospital care; the impact, if any, of VWs on the uptake of primary care, community health services and council-funded social care; and the potential costs and savings of VWs from the perspectives of the national health service (NHS) and local authorities. Igitur publishing 2011-06-30 /pmc/articles/PMC3178802/ /pubmed/21949489 Text en Copyright 2011, International Journal of Integrated Care (IJIC) http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research and Theory
Lewis, Geraint
Bardsley, Martin
Vaithianathan, Rhema
Steventon, Adam
Georghiou, Theo
Billings, John
Dixon, Jennifer
Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title_full Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title_fullStr Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title_full_unstemmed Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title_short Do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? A research protocol using propensity matched controls
title_sort do ‘virtual wards’ reduce rates of unplanned hospital admissions, and at what cost? a research protocol using propensity matched controls
topic Research and Theory
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3178802/
https://www.ncbi.nlm.nih.gov/pubmed/21949489
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