↓ Skip to main content

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

Overview of attention for article published in BMC Health Services Research, March 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
70 Mendeley
Title
Main drivers of health expenditure growth in China: a decomposition analysis
Published in
BMC Health Services Research, March 2017
DOI 10.1186/s12913-017-2119-1
Pubmed ID
Authors

Tiemin Zhai, John Goss, Jinjing Li

Abstract

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. 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. 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. 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.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 19%
Student > Master 10 14%
Student > Ph. D. Student 8 11%
Student > Doctoral Student 3 4%
Student > Bachelor 3 4%
Other 13 19%
Unknown 20 29%
Readers by discipline Count As %
Nursing and Health Professions 11 16%
Economics, Econometrics and Finance 10 14%
Medicine and Dentistry 9 13%
Social Sciences 5 7%
Business, Management and Accounting 4 6%
Other 7 10%
Unknown 24 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 September 2021.
All research outputs
#20,974,124
of 25,761,363 outputs
Outputs from BMC Health Services Research
#7,501
of 8,760 outputs
Outputs of similar age
#249,525
of 322,088 outputs
Outputs of similar age from BMC Health Services Research
#141
of 162 outputs
Altmetric has tracked 25,761,363 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,760 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.