IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i11p1170-d560027.html
   My bibliography  Save this article

The Classification of Profiles of Financial Catastrophe Caused by Out-of-Pocket Payments: A Methodological Approach

Author

Listed:
  • Maria-Carmen García-Centeno

    (Department of Applied Mathematics and Statistics, CEU San Pablo University, Julian Romea 23, 28003 Madrid, Spain)

  • Román Mínguez-Salido

    (Department of Public Economy, Statistics and Economic Policy, University of Castilla-La Mancha, Avenida Los Alfares 44, 16071 Cuenca, Spain)

  • Raúl del Pozo-Rubio

    (Department of Economics and Finance, University of Castilla-La Mancha, Avenida Los Alfares 44, 16071 Cuenca, Spain)

Abstract

The financial catastrophe resulting from the out-of-pocket payments necessary to access and use healthcare systems has been widely studied in the literature. The aim of this work is to predict the impact of the financial catastrophe a household will face as a result of out-of-pocket payments in long-term care in Spain. These predictions were made using machine learning techniques such as LASSO (Least Absolute Shrinkage and Selection Operator) penalized regression and elastic-net, as well as algorithms like k-nearest neighbors (KNN), MARS (Multivariate Adaptive Regression Splines), random forest, boosted trees and SVM (Support Vector Machine). The results reveal that all the classification methods performed well, with the complex models performing better than the simpler ones and showing no evidence of overfitting. Detecting and defining the profiles of individuals and families most likely to suffer from financial catastrophe is crucial in enabling the design of financial policies aimed at protecting vulnerable groups.

Suggested Citation

  • Maria-Carmen García-Centeno & Román Mínguez-Salido & Raúl del Pozo-Rubio, 2021. "The Classification of Profiles of Financial Catastrophe Caused by Out-of-Pocket Payments: A Methodological Approach," Mathematics, MDPI, vol. 9(11), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:11:p:1170-:d:560027
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/11/1170/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/11/1170/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Songul Cinaroglu, 2020. "Modelling unbalanced catastrophic health expenditure data by using machine‐learning methods," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 168-181, October.
    2. Felix Masiye & Oliver Kaonga & Joses M Kirigia, 2016. "Does User Fee Removal Policy Provide Financial Protection from Catastrophic Health Care Payments? Evidence from Zambia," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-15, January.
    3. Grigorakis, Nikolaos & Floros, Christos & Tsangari, Haritini & Tsoukatos, Evangelos, 2016. "Out of pocket payments and social health insurance for private hospital care: Evidence from Greece," Health Policy, Elsevier, vol. 120(8), pages 948-959.
    4. del Pozo-Rubio, Raúl & Jiménez-Rubio, Dolores, 2019. "Catastrophic risk associated with out-of-pocket payments for long term care in Spain," Health Policy, Elsevier, vol. 123(6), pages 582-589.
    5. Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
    6. Panos Kanavos & Olivier Wouters & Anna Zawada & Katarzyna Kolasa & Christian Kronborg & Daniel Rabczenko & Tomasz Rybnik & Jørgen T. Lauridsen & Urszula Ceglowska & Tomasz Hermanowski, 2017. "A Comparison of the Burden of Out-of-Pocket Health Payments in Denmark, Germany and Poland," Global Policy, London School of Economics and Political Science, vol. 8(s2), pages 123-130, March.
    7. Tim Muir, 2017. "Measuring social protection for long-term care," OECD Health Working Papers 93, OECD Publishing.
    8. Eddy van Doorslaer & Owen O'Donnell & Ravindra P. Rannan-Eliya & Aparnaa Somanathan & Shiva Raj Adhikari & Charu C. Garg & Deni Harbianto & Alejandro N. Herrin & Mohammed Nazmul Huq & Shamsia Ibragimo, 2007. "Catastrophic payments for health care in Asia," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1159-1184.
    9. Shah Mohammad Fahim & Tofayel Ahmed Bhuayan & Md. Zakiul Hassan & Abu Hena Abid Zafr & Farhana Begum & Md. Mizanur Rahman & Shahinul Alam, 2019. "Financing health care in Bangladesh: Policy responses and challenges towards achieving universal health coverage," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(1), pages 11-20, January.
    10. Raúl Pozo-Rubio & Román Mínguez-Salido & Isabel Pardo-García & Francisco Escribano-Sotos, 2019. "Catastrophic long-term care expenditure: associated socio-demographic and economic factors," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 691-701, July.
    11. Xenia Scheil‐Adlung & Jacopo Bonan, 2013. "Gaps in social protection for health care and long‐term care in Europe: Are the elderly faced with financial ruin?," International Social Security Review, John Wiley & Sons, vol. 66(1), pages 25-48, January.
    12. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    13. Yerramilli, Pooja & Fernández, Óscar & Thomson, Sarah, 2018. "Financial protection in Europe: a systematic review of the literature and mapping of data availability," Health Policy, Elsevier, vol. 122(5), pages 493-508.
    14. Eddy van Doorslaer & Owen O'Donnell & Ravindra P. Rannan‐Eliya & Aparnaa Somanathan & Shiva Raj Adhikari & Charu C. Garg & Deni Harbianto & Alejandro N. Herrin & Mohammed Nazmul Huq & Shamsia Ibragimo, 2007. "Catastrophic payments for health care in Asia," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1159-1184, November.
    15. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
    16. Adam Wagstaff & Eddy van Doorslaer, 2003. "Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993–1998," Health Economics, John Wiley & Sons, Ltd., vol. 12(11), pages 921-933, November.
    17. Cylus, Jonathan & Thomson, Sarah & Evetovits, Tamás, 2018. "Catastrophic health spending in Europe: equity and policy implications of different calculation methods," LSE Research Online Documents on Economics 89062, London School of Economics and Political Science, LSE Library.
    18. Kim, Sujin & Kwon, Soonman, 2015. "Impact of the policy of expanding benefit coverage for cancer patients on catastrophic health expenditure across different income groups in South Korea," Social Science & Medicine, Elsevier, vol. 138(C), pages 241-247.
    19. Antonello Maruotti, 2009. "Fairness of the national health service in Italy: a bivariate correlated random effects model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 709-722.
    20. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    21. Kronenberg, Christoph & Barros, Pedro Pita, 2014. "Catastrophic healthcare expenditure – Drivers and protection: The Portuguese case," Health Policy, Elsevier, vol. 115(1), pages 44-51.
    22. Jelena Arsenijevic & Milena Pavlova & Bernd Rechel & Wim Groot, 2016. "Catastrophic Health Care Expenditure among Older People with Chronic Diseases in 15 European Countries," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    23. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    24. Karatzoglou, Alexandros & Smola, Alexandros & Hornik, Kurt & Zeileis, Achim, 2004. "kernlab - An S4 Package for Kernel Methods in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i09).
    25. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    26. repec:bla:glopol:v:8:y:2017:i::p:123-130 is not listed on IDEAS
    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. Samuel López-López & Raúl del Pozo-Rubio & Marta Ortega-Ortega & Francisco Escribano-Sotos, 2021. "Catastrophic Household Expenditure Associated with Out-of-Pocket Healthcare Payments in Spain," IJERPH, MDPI, vol. 18(3), pages 1-18, January.
    2. Yerramilli, Pooja & Fernández, Óscar & Thomson, Sarah, 2018. "Financial protection in Europe: a systematic review of the literature and mapping of data availability," Health Policy, Elsevier, vol. 122(5), pages 493-508.
    3. Aleksandra Kolasa & Ewa Weychert, 2022. "The causal effect of catastrophic health expenditure on poverty in Poland," Working Papers 2022-23, Faculty of Economic Sciences, University of Warsaw.
    4. Kyriopoulos, Ilias & Nikoloski, Zlatko & Mossialos, Elias, 2021. "Financial protection in health among the middle-aged and elderly: Evidence from the Greek economic recession," Health Policy, Elsevier, vol. 125(9), pages 1256-1266.
    5. Raúl Del Pozo-Rubio & Isabel Pardo-García & Francisco Escribano-Sotos, 2020. "Financial Catastrophism Inherent with Out-of-Pocket Payments in Long Term Care for Households: A Latent Impoverishment," IJERPH, MDPI, vol. 17(1), pages 1-19, January.
    6. Samuel López-López & Raúl Pozo-Rubio & Marta Ortega-Ortega & Francisco Escribano-Sotos, 2022. "Catastrophic household expenditure associated with out-of-pocket payments for dental healthcare in Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1187-1201, September.
    7. Chantzaras, Athanasios E. & Yfantopoulos, John N., 2018. "Financial protection of households against health shocks in Greece during the economic crisis," Social Science & Medicine, Elsevier, vol. 211(C), pages 338-351.
    8. Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Chen, Mingsheng & Xu, Lizheng & Si, Lei & Wang, Zhonghua & Jan, Stephen, 2023. "Examining the level and distribution of catastrophic health expenditure from 2013 to 2018: A province-level study in China," Economic Modelling, Elsevier, vol. 121(C).
    10. Raúl Pozo-Rubio & Román Mínguez-Salido & Isabel Pardo-García & Francisco Escribano-Sotos, 2019. "Catastrophic long-term care expenditure: associated socio-demographic and economic factors," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 691-701, July.
    11. Colombo, Emilio & Pelagatti, Matteo, 2020. "Statistical learning and exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1260-1289.
    12. Athey, Susan & Imbens, Guido W., 2019. "Machine Learning Methods Economists Should Know About," Research Papers 3776, Stanford University, Graduate School of Business.
    13. Muaz Sayuti & Surianti Sukeri, 2022. "Assessing progress towards Sustainable Development Goal 3.8.2 and determinants of catastrophic health expenditures in Malaysia," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-12, February.
    14. Fitzpatrick, Trevor & Mues, Christophe, 2021. "How can lenders prosper? Comparing machine learning approaches to identify profitable peer-to-peer loan investments," European Journal of Operational Research, Elsevier, vol. 294(2), pages 711-722.
    15. Konrad Bogner & Florian Pappenberger & Massimiliano Zappa, 2019. "Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts," Sustainability, MDPI, vol. 11(12), pages 1-22, June.
    16. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
    17. Thuong, Nguyen Thi Thu, 2021. "Catastrophic health expenditure and impoverishment in Vietnam: Evidence from national Household Living Standards Surveys 2008–2018," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 668-684.
    18. Kim, Sujin & Kwon, Soonman, 2023. "Has South Korea achieved the goals of national health insurance? Trends in financial protection of households between 2011 and 2018," Social Science & Medicine, Elsevier, vol. 326(C).
    19. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    20. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.

    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:jmathe:v:9:y:2021:i:11:p:1170-:d:560027. 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.