IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i10p3539-d359933.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/10/3539/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/10/3539/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Goddeeris, John H, 1984. "Medical Insurance, Technological Change, and Welfare," Economic Inquiry, Western Economic Association International, vol. 22(1), pages 56-67, January.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yongmin Chen & Jianpei Li & Jin Zhang, 2022. "Efficient Liability In Expert Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1717-1744, November.
    2. Fang Liu & Alexander Rasch & Marco A. Schwarz & Christian Waibel, 2020. "The role of diagnostic ability in markets for expert services," Working Papers 2020-07, Faculty of Economics and Statistics, Universität Innsbruck.
    3. Bertrand Crettez & Régis Deloche & Marie‐Hélène Jeanneret‐Crettez, 2020. "A demand‐induced overtreatment model with heterogeneous experts," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(5), pages 1713-1733, September.
    4. Katharina Momsen & Markus Ohndorf, 2022. "Seller Opportunism in Credence Good Markets – The Role of Market Conditions," Working Papers 2022-10, Faculty of Economics and Statistics, Universität Innsbruck.
    5. Helmut Bester & Matthias Dahm, 2018. "Credence Goods, Costly Diagnosis and Subjective Evaluation," Economic Journal, Royal Economic Society, vol. 128(611), pages 1367-1394, June.
    6. Balafoutas, Loukas & Kerschbamer, Rudolf, 2020. "Credence goods in the literature: What the past fifteen years have taught us about fraud, incentives, and the role of institutions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    7. Chen, Yongmin & Li, Jianpei & Zhang, Jin, 2017. "Liability in Markets for Credence Goods," MPRA Paper 80206, University Library of Munich, Germany.
    8. Dominik Erharter, 2012. "Credence goods markets, distributional preferences and the role of institutions," Working Papers 2012-11, Faculty of Economics and Statistics, Universität Innsbruck.
    9. Dulleck, Uwe & Kerschbamer, Rudolf & Konovalov, Alexander, 2014. "Too Much or Too Little? Price-Discrimination in a Market for Credence Goods," Working Papers in Economics 582, University of Gothenburg, Department of Economics, revised Apr 2014.
    10. Jeffrey Clemens & Joshua D. Gottlieb, 2014. "Do Physicians' Financial Incentives Affect Medical Treatment and Patient Health?," American Economic Review, American Economic Association, vol. 104(4), pages 1320-1349, April.
    11. Liu, Ting & Ma, Ching-to Albert, 2024. "Equilibrium information in credence goods," Games and Economic Behavior, Elsevier, vol. 145(C), pages 84-101.
    12. Cao, Yiran & Chen, Yongmin & Ding, Yucheng & Zhang, Tianle, 2022. "Search and competition in expert markets," MPRA Paper 114170, University Library of Munich, Germany.
    13. Tianyan Hu & Sandra L. Decker & Shin-Yi Chou, 2014. "The Impact of Health Insurance Expansion on Physician Treatment Choice: Medicare Part D and Physician Prescribing," NBER Working Papers 20708, National Bureau of Economic Research, Inc.
    14. Bester, Helmut & Ouyang, Yaofu, 2018. "Optimal procurement of a credence good under limited liability," International Journal of Industrial Organization, Elsevier, vol. 61(C), pages 96-129.
    15. Paolo Pertile, 2008. "Investment in Health Technologies in a Competitive Model with Real Options," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 10(5), pages 923-952, October.
    16. David Bardey & Denis Gromb & David Martimort & Jérôme Pouyet, 2020. "Controlling Sellers Who Provide Advice: Regulation and Competition," Journal of Industrial Economics, Wiley Blackwell, vol. 68(3), pages 409-444, September.
    17. Rudolf Kerschbamer & Matthias Sutter & Uwe Dulleck, 2009. "The Impact of Distributional Preferences on (Experimental) Markets for Expert Services," Working Papers 2009-28, Faculty of Economics and Statistics, Universität Innsbruck.
    18. Pratt, John W & Zeckhauser, Richard J, 1996. "Willingness to Pay and the Distribution of Risk and Wealth," Journal of Political Economy, University of Chicago Press, vol. 104(4), pages 747-763, August.
    19. Freedman, Seth & Lin, Haizhen & Simon, Kosali, 2015. "Public health insurance expansions and hospital technology adoption," Journal of Public Economics, Elsevier, vol. 121(C), pages 117-131.
    20. Joachim Heinzel, 2019. "Credence Goods Markets with Fair and Opportunistic Experts," Working Papers CIE 119, Paderborn University, CIE Center for International Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3539-:d:359933. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.