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The Impact of Internet Medical Information Overflow on Residents’ Medical Expenditure Based on China’s Observations

Author

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  • Junqiang Han

    (School of Public Management, South-Central University for Nationalities, Wuhan 430074, China)

  • Xiaodong Zhang

    (Centre for Social Security Studies, Wuhan University, Wuhan 430072, China)

  • Yingying Meng

    (Centre for Social Security Studies, Wuhan University, Wuhan 430072, China)

Abstract

Background : The rapid rise of medical expenditure is a common problem in the field of public health around the world, but the challenges for the Chinese government are even greater. How to control the rapid rise in medical expenditure and reduce individuals’ economic burden when receiving medical treatment has become one of the core issues that the Chinese government urgently needs to solve. The aim of this study was to evaluate the impact of Internet use on individuals’ medical expenditure and further discuss the potential impact mechanism. Methods : The data used in this study were from the 2018 China Family Panel Studies (CFPS) conducted by Peking University. The Heckman sample selection model was used to analyse the impact of Internet use on individuals’ medical expenditure. Results : Internet use reduced the medical expenditure of individuals by 6.19%; high frequency Internet use reduced the medical expenditure of individuals by 15.1%, while low frequency Internet use had no impact. In addition, Internet use had different impacts on individuals’ medical expenditure at different levels of hospitals. Specifically, Internet use reduced the medical expenditure of individuals who received medical treatment at general hospitals by 9.63%, and high frequency Internet use reduced the medical expenditure of individuals by 22.2%. However, Internet use had no impact on the medical expenditure of individuals who received medical treatment at primary hospitals. Conclusions : Findings from this study underscore the importance of Internet use as an important role in reducing individuals’ medical expenditure. The use of the Internet can significantly reduce the level of individuals’ medical expenditure, and high frequency Internet use has a greater effect. However, Internet use has different impacts on individuals’ medical expenditure among different levels of hospitals. The reduction effect of Internet use on individuals’ medical expenditure is mainly concentrated in general hospitals but has no effect in primary hospitals.

Suggested Citation

  • Junqiang Han & Xiaodong Zhang & Yingying Meng, 2020. "The Impact of Internet Medical Information Overflow on Residents’ Medical Expenditure Based on China’s Observations," IJERPH, MDPI, vol. 17(10), pages 1-16, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3539-:d:359933
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    References listed on IDEAS

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    1. Ting Liu, 2011. "Credence Goods Markets With Conscientious And Selfish Experts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 227-244, February.
    2. Sharmila Gamlath & Radhika Lahiri, 2019. "Health expenditures and inequality: a political economy perspective," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(4), pages 942-964, August.
    3. Amy Finkelstein, 2007. "The Aggregate Effects of Health Insurance: Evidence from the Introduction of Medicare," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 1-37.
    4. Ingela Alger & François Salanié, 2006. "A Theory of Fraud and Overtreatment in Experts Markets," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 15(4), pages 853-881, December.
    5. Wagner, Todd H. & Hu, Teh-wei & Hibbard, Judith H., 2001. "The demand for consumer health information," Journal of Health Economics, Elsevier, vol. 20(6), pages 1059-1075, November.
    6. Darby, Michael R & Karni, Edi, 1973. "Free Competition and the Optimal Amount of Fraud," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 67-88, April.
    7. Goddeeris, John H, 1984. "Medical Insurance, Technological Change, and Welfare," Economic Inquiry, Western Economic Association International, vol. 22(1), pages 56-67, January.
    8. Ellis, Randall P. & McGuire, Thomas G., 1986. "Provider behavior under prospective reimbursement : Cost sharing and supply," Journal of Health Economics, Elsevier, vol. 5(2), pages 129-151, June.
    9. Cotten, Shelia R & Gupta, Sipi S, 2004. "Characteristics of online and offline health information seekers and factors that discriminate between them," Social Science & Medicine, Elsevier, vol. 59(9), pages 1795-1806, November.
    10. Weisbrod, Burton A, 1991. "The Health Care Quadrilemma: An Essay on Technological Change, Insurance, Quality of Care, and Cost Containment," Journal of Economic Literature, American Economic Association, vol. 29(2), pages 523-552, June.
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    1. Shujie Zou & Chiawei Chu & Ning Shen & Jia Ren, 2023. "Healthcare Cost Prediction Based on Hybrid Machine Learning Algorithms," Mathematics, MDPI, vol. 11(23), pages 1-13, November.

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