IDEAS home Printed from https://ideas.repec.org/a/spr/hecrev/v12y2022i1d10.1186_s13561-021-00353-9.html
   My bibliography  Save this article

Examining proximity to death and health care expenditure by disease: a Bayesian-based descriptive statistical analysis from the National Health Insurance database in Japan

Author

Listed:
  • Yuji Hiramatsu

    (The University of Tokyo
    AXA Life Insurance Co., Ltd)

  • Hiroo Ide

    (The University of Tokyo)

  • Atsuko Tsuchiya

    (Shizuoka Prefectural Government)

  • Yuji Furui

    (The University of Tokyo)

Abstract

Background Japan is one of the Organization for Economic Co-operation and Development (OECD) countries where population aging and increasing health care expenditures (HCE) are urgent issues. Recent studies have identified factors other than age, such as proximity to death and morbidity, as contributing factors to the increase in medical costs. It is important to assess HCE by disease and analyze their factors to estimate and improve future HCE. Methods We extracted individual records spanning approximately 2 years prior to the death of persons aged 65 to 95 years from the National Health Insurance data in Japan, and used a Bayesian approach to decompose monthly HCE into five disease groups (circulatory, chronic kidney disease, neoplasms, respiratory, and others). The relationship between the proximity to death and the average HCE in each disease group was stratified by sex and age and analyzed using a descriptive statistical method similar to the two-part model. Results The average HCE increased rapidly as death approached in most disease groups, but the increase-pattern differed greatly among disease groups, sex, and age groups. The effect of proximity to death on average HCE was small for chronic diseases, but large for lethal diseases. When stratified by age and sex, younger and male decedents tended to have higher average HCE, but the extent of this varied by disease group. The two-year cumulative average HCE for neoplasms in the 65–75 years age group was about six times larger than those in the 85–95 years age group. Conclusions In Japan, it was suggested that disease, proximity to death, age, and sex may contribute to HCE. However, these factors interact in a complex manner, and it is important to analyze HCE by disease. In addition, preventing or delaying the severity of diseases with high medical burdens in younger people may be effective in reducing future terminal care costs. These findings have important implications for future projections and improvements of HCE.

Suggested Citation

  • Yuji Hiramatsu & Hiroo Ide & Atsuko Tsuchiya & Yuji Furui, 2022. "Examining proximity to death and health care expenditure by disease: a Bayesian-based descriptive statistical analysis from the National Health Insurance database in Japan," Health Economics Review, Springer, vol. 12(1), pages 1-19, December.
  • Handle: RePEc:spr:hecrev:v:12:y:2022:i:1:d:10.1186_s13561-021-00353-9
    DOI: 10.1186/s13561-021-00353-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13561-021-00353-9
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1186/s13561-021-00353-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    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. Insoo Cho & Peter F. Orazem, 2021. "How endogenous risk preferences and sample selection affect analysis of firm survival," Small Business Economics, Springer, vol. 56(4), pages 1309-1332, April.
    2. Walter Beckert, 2015. "Choice in the Presence of Experts," Birkbeck Working Papers in Economics and Finance 1503, Birkbeck, Department of Economics, Mathematics & Statistics.
    3. Cameron, Trudy Ann & Shaw, W. Douglass & Ragland, Shannon E. & Callaway, J. Mac & Keefe, Sally, 1996. "Using Actual And Contingent Behavior Data With Differing Levels Of Time Aggregation To Model Recreation Demand," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(1), pages 1-20, July.
    4. Hans A. Holter & Dirk Krueger & Serhiy Stepanchuk, 2019. "How do tax progressivity and household heterogeneity affect Laffer curves?," Quantitative Economics, Econometric Society, vol. 10(4), pages 1317-1356, November.
    5. Michael Raper, 1999. "Self-selection bias and cost-of-living estimates," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 23(1), pages 64-77, March.
    6. Matthew Gentry & Tong Li & Jingfeng Lu, 2015. "Identification and estimation in first-price auctions with risk-averse bidders and selective entry," CeMMAP working papers 16/15, Institute for Fiscal Studies.
    7. Aizenman, Joshua & Ito, Hiro & Pasricha, Gurnain Kaur, 2022. "Central bank swap arrangements in the COVID-19 crisis," Journal of International Money and Finance, Elsevier, vol. 122(C).
    8. Trottmann, Maria & Zweifel, Peter & Beck, Konstantin, 2012. "Supply-side and demand-side cost sharing in deregulated social health insurance: Which is more effective?," Journal of Health Economics, Elsevier, vol. 31(1), pages 231-242.
    9. Banal-Estañol, Albert & Duso, Tomaso & Seldeslachts, Jo & Szücs, Florian, 2022. "R&D Spillovers through RJV Cooperation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(4), pages 1-10.
    10. Renuka Sane & Susan Thomas, 2020. "From Participation To Repurchase: Low Income Households And Micro‐insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(3), pages 783-814, September.
    11. Merz, Joachim & Rathjen, Tim, 2011. "Intensity of Time and Income Interdependent Multidimensional Poverty: Well-Being and Minimum 2DGAP – German Evidence," IZA Discussion Papers 6022, Institute of Labor Economics (IZA).
    12. Bodory, Hugo & Huber, Martin, 2018. "The causalweight package for causal inference in R," FSES Working Papers 493, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    13. Michael Ziegelmeyer & Julius Nick, 2013. "Backing out of private pension provision: lessons from Germany," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(3), pages 505-539, August.
    14. Joseph Mason, 2001. "Do Lender of Last Resort Policies Matter? The Effects of Reconstruction Finance Corporation Assistance to Banks During the Great Depression," Journal of Financial Services Research, Springer;Western Finance Association, vol. 20(1), pages 77-95, September.
    15. Torres, Marcelo de O. & Felthoven, Ronald G., 2014. "Productivity growth and product choice in catch share fisheries: The case of Alaska pollock," Marine Policy, Elsevier, vol. 50(PA), pages 280-289.
    16. Yuen Leng Chow & Isa E. Hafalir & Abdullah Yavas, 2015. "Auction versus Negotiated Sale: Evidence from Real Estate Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(2), pages 432-470, June.
    17. Xavier Ramos Morilla & Josep Lluís Raymond Bara & Josep Oliver Alonso, 1999. "Not All University Degrees Yield the Same Return: Private and Social Returns to Higher Education for Males in Spain," Working Papers wpdea9904, Department of Applied Economics at Universitat Autonoma of Barcelona.
    18. Fei Yang & Chunchen Wang, 2023. "Clean energy, emission trading policy, and CO2 emissions: Evidence from China," Energy & Environment, , vol. 34(5), pages 1657-1673, August.
    19. Lindelow, Magnus, 2002. "Health care demand in rural Mozambique," FCND discussion papers 126, International Food Policy Research Institute (IFPRI).
    20. Bauer, Rob & Cosemans, Mathijs & Eichholtz, Piet, 2009. "Option trading and individual investor performance," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 731-746, April.

    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:spr:hecrev:v:12:y:2022:i:1:d:10.1186_s13561-021-00353-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com/economics/journal/13561 .

    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.