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Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK
OBJECTIVES: The aim of this study was to develop prediction models for the individual-level impacts of cardiovascular events on UK healthcare costs. METHODS: In the UK Biobank, people 40–70 years old, recruited in 2006–2010, were followed in linked primary (N = 192,983 individuals) and hospital care...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10085892/ https://www.ncbi.nlm.nih.gov/pubmed/36826687 http://dx.doi.org/10.1007/s40273-022-01219-6 |
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author | Zhou, Junwen Wu, Runguo Williams, Claire Emberson, Jonathan Reith, Christina Keech, Anthony Robson, John Wilkinson, Kenneth Armitage, Jane Gray, Alastair Simes, John Baigent, Colin Mihaylova, Borislava |
author_facet | Zhou, Junwen Wu, Runguo Williams, Claire Emberson, Jonathan Reith, Christina Keech, Anthony Robson, John Wilkinson, Kenneth Armitage, Jane Gray, Alastair Simes, John Baigent, Colin Mihaylova, Borislava |
author_sort | Zhou, Junwen |
collection | PubMed |
description | OBJECTIVES: The aim of this study was to develop prediction models for the individual-level impacts of cardiovascular events on UK healthcare costs. METHODS: In the UK Biobank, people 40–70 years old, recruited in 2006–2010, were followed in linked primary (N = 192,983 individuals) and hospital care (N = 501,807 individuals) datasets. Regression models of annual primary and annual hospital care costs (2020 UK£) associated with individual characteristics and experiences of myocardial infarction (MI), stroke, coronary revascularization, incident diabetes mellitus and cancer, and vascular and nonvascular death are reported. RESULTS: For both people without and with previous cardiovascular disease (CVD), primary care costs were modelled using one-part generalised linear models (GLMs) with identity link and Poisson distribution, and hospital costs with two-part models (part 1: logistic regression models the probability of incurring costs; part 2: GLM with identity link and Poisson distribution models the costs conditional on incurring any). In people without previous CVD, mean annual primary and hospital care costs were £360 and £514, respectively. The excess primary care costs were £190 and £360 following MI and stroke, respectively, whereas excess hospital costs decreased from £4340 and £5590, respectively, in the year of these events, to £190 and £410 two years later. People with previous CVD had more than twice higher annual costs, and incurred higher excess costs for cardiovascular events. Other characteristics associated with higher costs included older age, female sex, south Asian ethnicity, higher socioeconomic deprivation, smoking, lower level of physical activities, unhealthy body mass index, and comorbidities. CONCLUSIONS: These individual-level healthcare cost prediction models could inform assessments of the value of health technologies and policies to reduce cardiovascular and other disease risks and healthcare costs. An accompanying Excel calculator is available to facilitate the use of the models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40273-022-01219-6. |
format | Online Article Text |
id | pubmed-10085892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100858922023-04-12 Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK Zhou, Junwen Wu, Runguo Williams, Claire Emberson, Jonathan Reith, Christina Keech, Anthony Robson, John Wilkinson, Kenneth Armitage, Jane Gray, Alastair Simes, John Baigent, Colin Mihaylova, Borislava Pharmacoeconomics Original Research Article OBJECTIVES: The aim of this study was to develop prediction models for the individual-level impacts of cardiovascular events on UK healthcare costs. METHODS: In the UK Biobank, people 40–70 years old, recruited in 2006–2010, were followed in linked primary (N = 192,983 individuals) and hospital care (N = 501,807 individuals) datasets. Regression models of annual primary and annual hospital care costs (2020 UK£) associated with individual characteristics and experiences of myocardial infarction (MI), stroke, coronary revascularization, incident diabetes mellitus and cancer, and vascular and nonvascular death are reported. RESULTS: For both people without and with previous cardiovascular disease (CVD), primary care costs were modelled using one-part generalised linear models (GLMs) with identity link and Poisson distribution, and hospital costs with two-part models (part 1: logistic regression models the probability of incurring costs; part 2: GLM with identity link and Poisson distribution models the costs conditional on incurring any). In people without previous CVD, mean annual primary and hospital care costs were £360 and £514, respectively. The excess primary care costs were £190 and £360 following MI and stroke, respectively, whereas excess hospital costs decreased from £4340 and £5590, respectively, in the year of these events, to £190 and £410 two years later. People with previous CVD had more than twice higher annual costs, and incurred higher excess costs for cardiovascular events. Other characteristics associated with higher costs included older age, female sex, south Asian ethnicity, higher socioeconomic deprivation, smoking, lower level of physical activities, unhealthy body mass index, and comorbidities. CONCLUSIONS: These individual-level healthcare cost prediction models could inform assessments of the value of health technologies and policies to reduce cardiovascular and other disease risks and healthcare costs. An accompanying Excel calculator is available to facilitate the use of the models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40273-022-01219-6. Springer International Publishing 2023-02-23 2023 /pmc/articles/PMC10085892/ /pubmed/36826687 http://dx.doi.org/10.1007/s40273-022-01219-6 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Research Article Zhou, Junwen Wu, Runguo Williams, Claire Emberson, Jonathan Reith, Christina Keech, Anthony Robson, John Wilkinson, Kenneth Armitage, Jane Gray, Alastair Simes, John Baigent, Colin Mihaylova, Borislava Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title | Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title_full | Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title_fullStr | Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title_full_unstemmed | Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title_short | Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK |
title_sort | prediction models for individual-level healthcare costs associated with cardiovascular events in the uk |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10085892/ https://www.ncbi.nlm.nih.gov/pubmed/36826687 http://dx.doi.org/10.1007/s40273-022-01219-6 |
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