Abstract
Abstract
Background
During 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.
Methods
Based 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.
Results
Among 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.
Conclusions
Income 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.
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health,Health Policy
Reference54 articles.
1. Zhai T, Zhang Y, Wan Q, Chai P, Guo F, Li Y, et al. The results and analysis of National Health Accounts in China in 2018. Chin Health Econ. 2020;39:5–8.
2. Lorenzoni L, Marino A, Morgan D, James C. Health spending projections to 2030: new results based on a revised OECD methodology. In: ECD Health Working Papers; 2019.
3. Marino A, Morgan D, Lorenzoni L, James C. Future trends in health care expenditure: a modelling framework for cross-country forecasts. In: OECD Health Working Papers; 2017.
4. Astolfi R, Lorenzoni L, Oderkirk J. Informing policy makers about future health spending: a comparative analysis of forecasting methods in OECD countries. Health Policy. 2012;107:1–10.
5. Chernew ME, Newhouse JP. Health care spending growth. In Handbook of health economics. Volume 2, Oxford: Elsevier; 2011. p. 1–43.
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