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Main drivers of health expenditure growth in China: a decomposition analysis

BACKGROUND: In past two decades, health expenditure in China grew at a rate of 11.6% per year, which is much faster than the growth of the country’s economy (9.9% per year). As cost containment is a key aspect of China’s new health system reform agenda, this study aims to identify the main drivers o...

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Autores principales: Zhai, Tiemin, Goss, John, Li, Jinjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343399/
https://www.ncbi.nlm.nih.gov/pubmed/28274228
http://dx.doi.org/10.1186/s12913-017-2119-1
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author Zhai, Tiemin
Goss, John
Li, Jinjing
author_facet Zhai, Tiemin
Goss, John
Li, Jinjing
author_sort Zhai, Tiemin
collection PubMed
description BACKGROUND: In past two decades, health expenditure in China grew at a rate of 11.6% per year, which is much faster than the growth of the country’s economy (9.9% per year). As cost containment is a key aspect of China’s new health system reform agenda, this study aims to identify the main drivers of past growth so that cost containment policies are focussed in the right areas. METHOD: The analysis covered the period 1993–2012. To understand the drivers of past growth during this period, Das Gupta’s decomposition method was used to decompose the changes in health expenditure by disease into five main components that include population growth, population ageing, disease prevalence rate, expenditure per case of disease, and excess health price inflation. Demographic data on population size and age-composition were obtained from the Department of Economic and Social Affairs of the United Nations. Age- and disease- specific expenditure and prevalence rates by age and disease were extracted from China’s National Health Accounts studies and Global Burden of Disease 2013 studies of the Institute for Health Metrics and Evaluation, respectively. RESULTS: Growth in health expenditure in China was mainly driven by a rapid increase in real expenditure per prevalent case, which contributed 8.4 percentage points of the 11.6% annual average growth. Excess health price inflation and population growth contributed 1.3 and 1.3% respectively. The effect of population ageing was relatively small, contributing 0.8% per year. However, reductions in disease prevalence rates reduced the growth rate by 0.3 percentage points. CONCLUSION: Future policy in optimising growth in health expenditure in China should address growth in expenditure per prevalent case. This is especially so for neoplasms, and for circulatory and respiratory disease. And a focus on effective interventions to reduce the prevalence of disease in the country will ensure that changing disease rates do not lead to a higher growth in future health expenditure; Measures should be taken to strengthen the capacity of health personnel in grass-roots facilities and to establish an effective referral system, so as to reduce the growth in expenditure per case of disease and to ensure that excess health price inflation does not grow out of control. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-017-2119-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-53433992017-03-10 Main drivers of health expenditure growth in China: a decomposition analysis Zhai, Tiemin Goss, John Li, Jinjing BMC Health Serv Res Research Article BACKGROUND: In past two decades, health expenditure in China grew at a rate of 11.6% per year, which is much faster than the growth of the country’s economy (9.9% per year). As cost containment is a key aspect of China’s new health system reform agenda, this study aims to identify the main drivers of past growth so that cost containment policies are focussed in the right areas. METHOD: The analysis covered the period 1993–2012. To understand the drivers of past growth during this period, Das Gupta’s decomposition method was used to decompose the changes in health expenditure by disease into five main components that include population growth, population ageing, disease prevalence rate, expenditure per case of disease, and excess health price inflation. Demographic data on population size and age-composition were obtained from the Department of Economic and Social Affairs of the United Nations. Age- and disease- specific expenditure and prevalence rates by age and disease were extracted from China’s National Health Accounts studies and Global Burden of Disease 2013 studies of the Institute for Health Metrics and Evaluation, respectively. RESULTS: Growth in health expenditure in China was mainly driven by a rapid increase in real expenditure per prevalent case, which contributed 8.4 percentage points of the 11.6% annual average growth. Excess health price inflation and population growth contributed 1.3 and 1.3% respectively. The effect of population ageing was relatively small, contributing 0.8% per year. However, reductions in disease prevalence rates reduced the growth rate by 0.3 percentage points. CONCLUSION: Future policy in optimising growth in health expenditure in China should address growth in expenditure per prevalent case. This is especially so for neoplasms, and for circulatory and respiratory disease. And a focus on effective interventions to reduce the prevalence of disease in the country will ensure that changing disease rates do not lead to a higher growth in future health expenditure; Measures should be taken to strengthen the capacity of health personnel in grass-roots facilities and to establish an effective referral system, so as to reduce the growth in expenditure per case of disease and to ensure that excess health price inflation does not grow out of control. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-017-2119-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-09 /pmc/articles/PMC5343399/ /pubmed/28274228 http://dx.doi.org/10.1186/s12913-017-2119-1 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhai, Tiemin
Goss, John
Li, Jinjing
Main drivers of health expenditure growth in China: a decomposition analysis
title Main drivers of health expenditure growth in China: a decomposition analysis
title_full Main drivers of health expenditure growth in China: a decomposition analysis
title_fullStr Main drivers of health expenditure growth in China: a decomposition analysis
title_full_unstemmed Main drivers of health expenditure growth in China: a decomposition analysis
title_short Main drivers of health expenditure growth in China: a decomposition analysis
title_sort main drivers of health expenditure growth in china: a decomposition analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343399/
https://www.ncbi.nlm.nih.gov/pubmed/28274228
http://dx.doi.org/10.1186/s12913-017-2119-1
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