IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0288035.html
   My bibliography  Save this article

Financial burden of heart failure in Malaysia: A perspective from the public healthcare system

Author

Listed:
  • Siew Chin Ong
  • Joo Zheng Low

Abstract

Background: Estimating and evaluating the economic burden of HF and its impact on the public healthcare system is necessary for devising improved treatment plans in the future. The present study aimed to determine the economic impact of HF on the public healthcare system. Method: The annual cost of HF per patient was estimated using unweighted average and inverse probability weighting (IPW). Unweight average estimated the annual cost by considering all observed cases regardless of the availability of all the cost data, while IPW calculated the cost by weighting against inverse probability. The economic burden of HF was estimated for different HF phenotypes and age categories at the population level from the public healthcare system perspective. Results: The mean (standard deviation) annual costs per patient calculated using unweighted average and IPW were USD 5,123 (USD 3,262) and USD 5,217 (USD 3,317), respectively. The cost of HF estimated using two different approaches did not differ significantly (p = 0.865). The estimated cost burden of HF in Malaysia was USD 481.9 million (range: USD 31.7 million– 1,213.2 million) per year, which accounts for 1.05% (range: 0.07%–2.66%) of total health expenditure in 2021. The cost of managing patients with heart failure with reduced ejection fraction (HFrEF) accounted for 61.1% of the total financial burden of HF in Malaysia. The annual cost burden increased from USD 2.8 million for patients aged 20–29 to USD 142.1 million for those aged 60–69. The cost of managing HF in patients aged 50–79 years contributed 74.1% of the total financial burden of HF in Malaysia. Conclusion: A large portion of the financial burden of HF in Malaysia is driven by inpatient costs and HFrEF patients. Long-term survival of HF patients leads to an increase in the prevalence of HF, inevitably increasing the financial burden of HF.

Suggested Citation

  • Siew Chin Ong & Joo Zheng Low, 2023. "Financial burden of heart failure in Malaysia: A perspective from the public healthcare system," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-14, July.
  • Handle: RePEc:plo:pone00:0288035
    DOI: 10.1371/journal.pone.0288035
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288035
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0288035&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0288035?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. Lawrence Liao & Larry Allen & David Whellan, 2008. "Economic Burden of Heart Failure in the Elderly," PharmacoEconomics, Springer, vol. 26(6), pages 447-462, June.
    2. O'Hagan, Anthony & Stevens, John W., 2004. "On estimators of medical costs with censored data," Journal of Health Economics, Elsevier, vol. 23(3), pages 615-625, May.
    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. Y. T. Hwang & C. H. Huang & W. L. Yeh & Y. D. Shen, 2017. "The weighted general linear model for longitudinal medical cost data – an application in colorectal cancer," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 288-307, January.
    2. Lu Deng & Wendy Lou & Nicholas Mitsakakis, 2019. "Modeling right-censored medical cost data in regression and the effects of covariates," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 143-155, March.
    3. Anirban Basu & Willard G. Manning, 2010. "Estimating lifetime or episode‐of‐illness costs under censoring," Health Economics, John Wiley & Sons, Ltd., vol. 19(9), pages 1010-1028, September.
    4. Liu, Lei & Conaway, Mark R. & Knaus, William A. & Bergin, James D., 2008. "A random effects four-part model, with application to correlated medical costs," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4458-4473, May.
    5. Maria Raikou & Alistair McGuire, 2012. "Estimating Costs for Economic Evaluation," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 43, Edward Elgar Publishing.
    6. Hyeonseok Cho & Sung-Hee Oh & Hankil Lee & Hyun-Jai Cho & Hye-Young Kang, 2018. "The incremental economic burden of heart failure: A population-based investigation from South Korea," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.
    7. Zhao, Xiaobing & Zhou, Xian, 2012. "Estimation of medical costs by copula models with dynamic change of health status," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 480-491.
    8. Jing‐Shiang Hwang & Tsuey‐Hwa Hu & Lukas Jyuhn‐Hsiarn Lee & Jung‐Der Wang, 2017. "Estimating lifetime medical costs from censored claims data," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 332-344, December.
    9. Maddi Olano‐Lizarraga & Cristina Oroviogoicoechea & Begoña Errasti‐Ibarrondo & Maribel Saracíbar‐Razquin, 2016. "The personal experience of living with chronic heart failure: a qualitative meta‐synthesis of the literature," Journal of Clinical Nursing, John Wiley & Sons, vol. 25(17-18), pages 2413-2429, September.
    10. Basu A & Manning WG, 2009. "Estimating Lifetime or Episode-of-illness Costs," Health, Econometrics and Data Group (HEDG) Working Papers 09/12, HEDG, c/o Department of Economics, University of York.
    11. Bernadette Li & John Cairns & James Fotheringham & Rommel Ravanan, 2016. "Predicting hospital costs for patients receiving renal replacement therapy to inform an economic evaluation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(6), pages 659-668, July.
    12. Manca, A & Austin, P. C, 2008. "Using propensity score methods to analyse individual patient-level cost-effectiveness data from observational studies," Health, Econometrics and Data Group (HEDG) Working Papers 08/20, HEDG, c/o Department of Economics, University of York.
    13. Mohamed El Alili & Johanna M. van Dongen & Jonas L. Esser & Martijn W. Heymans & Maurits W. van Tulder & Judith E. Bosmans, 2022. "A scoping review of statistical methods for trial‐based economic evaluations: The current state of play," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2680-2699, December.
    14. Anirban Basu & Willard G. Manning, 2011. "Erratum: Estimating lifetime or episode‐of‐illness costs under censoring," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 125-126, January.
    15. Jan B. Oostenbrink & Maiwenn J. Al, 2005. "The analysis of incomplete cost data due to dropout," Health Economics, John Wiley & Sons, Ltd., vol. 14(8), pages 763-776, August.
    16. Zhao, Xiaobing & Zhou, Xian, 2009. "Semiparametric modeling of medical cost data containing zeros," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1207-1214, May.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0288035. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.