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Original research
Medical costs and out-of-pocket expenditures associated with multimorbidity in China: quantile regression analysis
  1. Yang Zhao1,2,
  2. Rifat Atun3,4,
  3. Kanya Anindya5,
  4. Barbara McPake5,
  5. Tiara Marthias5,6,
  6. Tianxin Pan7,
  7. Alexander van Heusden5,
  8. Puhong Zhang1,8,
  9. Nadila Duolikun1,
  10. John Tayu Lee5,9
  1. 1The George Institute for Global Health at Peking University Health Science Centre, Beijing, China
  2. 2Collaborating Centre on Implementation Research for Prevention & Control of NCDs, WHO, Melbourne, Victoria, Australia
  3. 3Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
  4. 4Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, USA
  5. 5The Nossal Institute for Global Health, The University of Melbourne, Melbourne, Victoria, Australia
  6. 6Department of Public Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
  7. 7Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
  8. 8The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
  9. 9Public Health Policy Evaluation Unit, Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, UK
  1. Correspondence to Dr Yang Zhao; Wzhao{at}georgeinstitute.org.cn

Abstract

Objective Multimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution.

Methods Data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE.

Results Overall, 69.5% of middle-aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively).

Conclusion Multimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.

  • health policy
  • health economics
  • health systems
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjgh-2020-004042

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    Footnotes

    • Handling editor Lei Si

    • Twitter @RifatAtun

    • Contributors YZ and JL conceived and designed the study. YZ, RA and JL did the initial analysis and supervised data analysis. YZ wrote the first draft of the paper, and RA, KA, BM, TM, TP, AvH, PZ, ND and JL critically revised the first draft. All authors reviewed and approved the final version of the paper submitted for publication.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval The Biomedical Ethics Review Committee of Peking University approved the CHARLS study (approval number: IRB00001052–11015), and all interviewees were required to provide informed consent.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement No additional data are available.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.