Evidence map›Paper›PMID 34565389›Full record

ArticleInternational journal for equity in health2021

Determinants of China's health expenditure growth: based on Baumol's cost disease theory.

Linan Wang, Yuqian Chen

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Article in International journal for equity in health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

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17citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Baumol's cost disease in acute versus long-term care: Do the differences loom large?International journal of health economics and management · 2025
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Linan WangSchool of Public Economics and Administration, Shanghai University of Finance and Economics, No. 777 Guoding Road, Yangpu District, Shanghai, 200433, China.
Yuqian ChenShanghai Health Development Research Center, No. 1477 West Beijing Road, Jing'an District, Shanghai, 200041, China. yvqianc@163.com.ORCID 0000-0003-1032-0991

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the past four decades, China's total health expenditure and health expenditure per capita have both experienced a dramatic increase in growth rate. This study aims to explore the determinants of health expenditure growth and the influencing mechanism of these determinants, with considering the productivity efficiency represented by Baumol's cost disease.

methodsBased on the longitudinal data of 30 provincial-level administrative regions in China, from 2010 to 2017, multi-variates regression models were constructed to assess the determinants, including demography, income, Baumol's cost disease, technology, their effects on per capital total health expenditure growth and the three financing sources: government, society and out-of-pocket health expenditure. Moreover, the Spatial Durbin Model was used to analyze the influence mechanism of determinants on the increase of health expenditure across provinces.

resultsAmong 210 province-year growth rate observations, all of the average growth rate of total health expenditure (12.78%) was much higher than the growth rate of per capita GDP (8.06%). According to the statistical analysis, we found that:(1) Income and Baumol's cost disease have a significant positive impact on health expenditure growth(P < 0.01). The impact of technical factors on government health expenditure is significantly positive. (2) The determinants affected the growth of health costs in different regions variably; the eastern region is mainly driven by Baumol's cost disease and technical factors, while the central and western regions are mainly affected by income factors and Baumol's cost disease. (3) There is a significant spatial spillover effect on the health expenditure growth between regions. The income factor and Baumol's cost disease have a positive impact on the health expenditure growth in its own region as well as in other regions.

conclusionsIncome and Baumol's cost disease significantly contributed to China health expenditure growth. The health expenditure determinants showed spatial varies effect and space spillover effect on the neighborhood areas. Which indicates that a reasonable salary system should be contrasted to meet the changeling from the Baumol's cost disease, and the necessity of equity in health resource allocation among provinces in China.

Indexed as

Health ExpendituresChinaCost of IllnessHumansIncomeBaumol’s cost diseaseDeterminantsHealth expenditure growthSpatial Durbin model

Identifiers

PMID34565389
PMCPMC8474747

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.