IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i7p1206-d219882.html
   My bibliography  Save this article

An Examination of the Determination of Medical Capacity under a National Health Insurance Program

Author

Listed:
  • Yi-Tui Chen

    (Department of Health Care Management, National Taipei University of Nursing and Health Sciences, 89, Nei-Chiang St. Wan-Hua Dist. Taipei 108, Taiwan)

Abstract

This paper examines the capacity determination factors of medical services at a national level through the analysis of a mathematical model that maximizes social welfare, which consists of the consumption of private goods and the medical capacity provided by the society. A sensitivity analysis is conducted to investigate the impact of these factors on the medical capacity provided. Furthermore, a case example based on the data provided by the government is presented to discuss the results derived from the theoretical analysis. The results of the sensitivity analysis indicate that individual disposable income, the medical expenditure for each treatment, the level of premium payments, and substitution parameters have a positive impact on medical capacity, while the medical costs and preference parameter negatively affect medical capacity. The results of the correlation analysis based on the data of the case example are consistent with the findings of the theoretical analysis.

Suggested Citation

  • Yi-Tui Chen, 2019. "An Examination of the Determination of Medical Capacity under a National Health Insurance Program," IJERPH, MDPI, vol. 16(7), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1206-:d:219882
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/7/1206/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/7/1206/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yi, Pengfei & George, Santhosh K. & Paul, Jomon Aliyas & Lin, Li, 2010. "Hospital capacity planning for disaster emergency management," Socio-Economic Planning Sciences, Elsevier, vol. 44(3), pages 151-160, September.
    2. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    3. Robert E. Hall & Charles I. Jones, 2007. "The Value of Life and the Rise in Health Spending," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 39-72.
    4. James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.
    5. Lawrence Brown & Noah Gans & Avishai Mandelbaum & Anat Sakov & Haipeng Shen & Sergey Zeltyn & Linda Zhao, 2005. "Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 36-50, March.
    6. A Antipov & N Meade, 2002. "Forecasting call frequency at a financial services call centre," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 953-960, September.
    7. Russo, Giuliano & Rego, Inês & Perelman, Julian & Barros, Pedro Pita, 2016. "A tale of loss of privilege, resilience and change: the impact of the economic crisis on physicians and medical services in Portugal," Health Policy, Elsevier, vol. 120(9), pages 1079-1086.
    8. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
    9. Evrim Didem Güneş & Stefan Nickel, 2015. "Location Problems in Healthcare," Springer Books, in: Gilbert Laporte & Stefan Nickel & Francisco Saldanha da Gama (ed.), Location Science, edition 127, chapter 0, pages 555-579, Springer.
    10. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    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. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    2. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    3. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Taylor, James W. & Snyder, Ralph D., 2012. "Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing," Omega, Elsevier, vol. 40(6), pages 748-757.
    6. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    7. Rouba Ibrahim & Pierre L'Ecuyer, 2013. "Forecasting Call Center Arrivals: Fixed-Effects, Mixed-Effects, and Bivariate Models," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 72-85, May.
    8. Roberto Aringhieri & Giuliana Carello & Daniela Morale, 2016. "Supporting decision making to improve the performance of an Italian Emergency Medical Service," Annals of Operations Research, Springer, vol. 236(1), pages 131-148, January.
    9. Karl Schneeberger & Karl Doerner & Andrea Kurz & Michael Schilde, 2016. "Ambulance location and relocation models in a crisis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 1-27, March.
    10. Kinshuk Jerath & Anuj Kumar & Serguei Netessine, 2015. "An Information Stock Model of Customer Behavior in Multichannel Customer Support Services," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 368-383, July.
    11. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    12. Degel, Dirk & Wiesche, Lara & Rachuba, Sebastian & Werners, Brigitte, 2014. "Reorganizing an existing volunteer fire station network in Germany," Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 149-157.
    13. Martin van Buuren & Caroline Jagtenberg & Thije van Barneveld & Rob van der Mei & Sandjai Bhulai, 2018. "Ambulance Dispatch Center Pilots Proactive Relocation Policies to Enhance Effectiveness," Interfaces, INFORMS, vol. 48(3), pages 235-246, June.
    14. Nelas, José & Dias, Joana, 2020. "Optimal Emergency Vehicles Location: An approach considering the hierarchy and substitutability of resources," European Journal of Operational Research, Elsevier, vol. 287(2), pages 583-599.
    15. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2021. "Forecasting time-varying arrivals: Impact of direct response advertising on call center performance," Journal of Business Research, Elsevier, vol. 131(C), pages 227-240.
    16. Eichenbaum, Martin S. & Rebelo, Sergio & Trabandt, Mathias, 2022. "The macroeconomics of testing and quarantining," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    17. Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022. "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, vol. 92(4), pages 675-706, May.
    18. Mohri, Seyed Sina & Akbarzadeh, Meisam & Sayed Matin, Seyed Hamed, 2020. "A Hybrid model for locating new emergency facilities to improve the coverage of the road crashes," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    19. Smirnov, Dmitry & Huchzermeier, Arnd, 2020. "Analytics for labor planning in systems with load-dependent service times," European Journal of Operational Research, Elsevier, vol. 287(2), pages 668-681.
    20. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.

    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:16:y:2019:i:7:p:1206-:d:219882. 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.