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Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset
AIMS: The Symphony Project is designed to identify which groups of the South Somerset population in England would most benefit from greater integration across primary, community, acute and social care settings. METHODS: We analysed linked health and social care data for the entire South Somerset pop...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Igitur publishing
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314133/ https://www.ncbi.nlm.nih.gov/pubmed/25674043 |
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author | Kasteridis, Panagiotis Street, Andrew Dolman, Matthew Gallier, Lesley Hudson, Kevin Martin, Jeremy Wyer, Ian |
author_facet | Kasteridis, Panagiotis Street, Andrew Dolman, Matthew Gallier, Lesley Hudson, Kevin Martin, Jeremy Wyer, Ian |
author_sort | Kasteridis, Panagiotis |
collection | PubMed |
description | AIMS: The Symphony Project is designed to identify which groups of the South Somerset population in England would most benefit from greater integration across primary, community, acute and social care settings. METHODS: We analysed linked health and social care data for the entire South Somerset population for the financial year 2012/2013. The data captured acute, primary, community, mental health and social care utilisation and costs; demographic characteristics; and indicators of morbidity for each individual. We employed generalized linear models to analyse variation in annual health and social care costs for all 114,874 members of the South Somerset population and for 1458 individuals with three or more selected chronic conditions. RESULTS: We found that multi-morbidity, not age, was the key driver of health and social care costs. Moreover, the number of chronic conditions is as useful as information about specific conditions at predicting costs. We are able to explain 7% of the variation in total annual costs for population as a whole, and 14% of the variation for those with three or more conditions. We are best able to explain primary care costs, but explanatory power is poor for mental health and social care costs. CONCLUSIONS: The linked dataset makes it possible to understand existing patterns of health and social care utilisation and to analyse variation in annual costs, for the whole population and for sub-groups, in total and by setting. This has made it possible to identify who would most benefit from improved integrated care and to calculate capitated budgets to support financial integration. |
format | Online Article Text |
id | pubmed-4314133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Igitur publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-43141332015-02-11 Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset Kasteridis, Panagiotis Street, Andrew Dolman, Matthew Gallier, Lesley Hudson, Kevin Martin, Jeremy Wyer, Ian Int J Integr Care Integrated Care Case AIMS: The Symphony Project is designed to identify which groups of the South Somerset population in England would most benefit from greater integration across primary, community, acute and social care settings. METHODS: We analysed linked health and social care data for the entire South Somerset population for the financial year 2012/2013. The data captured acute, primary, community, mental health and social care utilisation and costs; demographic characteristics; and indicators of morbidity for each individual. We employed generalized linear models to analyse variation in annual health and social care costs for all 114,874 members of the South Somerset population and for 1458 individuals with three or more selected chronic conditions. RESULTS: We found that multi-morbidity, not age, was the key driver of health and social care costs. Moreover, the number of chronic conditions is as useful as information about specific conditions at predicting costs. We are able to explain 7% of the variation in total annual costs for population as a whole, and 14% of the variation for those with three or more conditions. We are best able to explain primary care costs, but explanatory power is poor for mental health and social care costs. CONCLUSIONS: The linked dataset makes it possible to understand existing patterns of health and social care utilisation and to analyse variation in annual costs, for the whole population and for sub-groups, in total and by setting. This has made it possible to identify who would most benefit from improved integrated care and to calculate capitated budgets to support financial integration. Igitur publishing 2015-01-28 /pmc/articles/PMC4314133/ /pubmed/25674043 Text en Copyright 2015, Authors retain the copyright of their article http://creativecommons.org/licenses/by/3.0/ This work is licensed under a (http://creativecommons.org/licenses/by/3.0) Creative Commons Attribution 3.0 Unported License |
spellingShingle | Integrated Care Case Kasteridis, Panagiotis Street, Andrew Dolman, Matthew Gallier, Lesley Hudson, Kevin Martin, Jeremy Wyer, Ian Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title | Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title_full | Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title_fullStr | Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title_full_unstemmed | Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title_short | Who would most benefit from improved integrated care? Implementing an analytical strategy in South Somerset |
title_sort | who would most benefit from improved integrated care? implementing an analytical strategy in south somerset |
topic | Integrated Care Case |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314133/ https://www.ncbi.nlm.nih.gov/pubmed/25674043 |
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