IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v52y2024ics1755534524000411.html
   My bibliography  Save this article

The interdependence between hospital choice and waiting time — with a case study in urban China

Author

Listed:
  • van de Klundert, Joris
  • Cominetti, Roberto
  • Liu, Yun
  • Kong, Qingxia

Abstract

Hospital choice models often employ random utility theory and include waiting time as a choice determinant. When applied to evaluate health system improvement interventions, these models disregard that hospital choice in turn is a determinant of waiting time. We present a novel, general model capturing the endogeneous relationship between waiting time and hospital choice, including the choice to opt out, and characterize the unique equilibrium solution of the resulting convex problem. We apply the general model in a case study on the urban Chinese health system, specifying that patient choice follows a multinomial logit (MNL) model and waiting times are determined by M/M/1 queues. The results reveal that analyses which solely rely on MNL models overestimate the effectiveness of present policy interventions and that this effectiveness is limited. We explore alternative, more effective, improvement interventions.

Suggested Citation

  • van de Klundert, Joris & Cominetti, Roberto & Liu, Yun & Kong, Qingxia, 2024. "The interdependence between hospital choice and waiting time — with a case study in urban China," Journal of choice modelling, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:eejocm:v:52:y:2024:i:c:s1755534524000411
    DOI: 10.1016/j.jocm.2024.100509
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534524000411
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jocm.2024.100509?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sergiu Hart, 2013. "Adaptive Heuristics," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 11, pages 253-287, World Scientific Publishing Co. Pte. Ltd..
    2. Young, H. Peyton, 2004. "Strategic Learning and its Limits," OUP Catalogue, Oxford University Press, number 9780199269181.
    3. John Antonakis & Samuel Bendahan & Philippe Jacquart & Rafael Lalive, 2010. "On making causal claims : A review and recommendations," Post-Print hal-02313119, HAL.
    4. Brown, Paul & Panattoni, Laura & Cameron, Linda & Knox, Stephanie & Ashton, Toni & Tenbensel, Tim & Windsor, John, 2015. "Hospital sector choice and support for public hospital care in New Zealand: Results from a labeled discrete choice survey," Journal of Health Economics, Elsevier, vol. 43(C), pages 118-127.
    5. Ta, Yuqi & Zhu, Yishan & Fu, Hongqiao, 2020. "Trends in access to health services, financial protection and satisfaction between 2010 and 2016: Has China achieved the goals of its health system reform?," Social Science & Medicine, Elsevier, vol. 245(C).
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    7. Yina Lu & Andrés Musalem & Marcelo Olivares & Ariel Schilkrut, 2013. "Measuring the Effect of Queues on Customer Purchases," Management Science, INFORMS, vol. 59(8), pages 1743-1763, August.
    8. Rouyard, Thomas & Attema, Arthur & Baskerville, Richard & Leal, José & Gray, Alastair, 2018. "Risk attitudes of people with ‘manageable’ chronic disease: An analysis under prospect theory," Social Science & Medicine, Elsevier, vol. 214(C), pages 144-153.
    9. Marianov, Vladimir & Rí­os, Miguel & Icaza, Manuel José, 2008. "Facility location for market capture when users rank facilities by shorter travel and waiting times," European Journal of Operational Research, Elsevier, vol. 191(1), pages 32-44, November.
    10. Kucukyazici, Beste & Zhang, Yue & Ardestani-Jaafari, Amir & Song, Lijie, 2020. "Incorporating patient preferences in the design and operation of cancer screening facility networks," European Journal of Operational Research, Elsevier, vol. 287(2), pages 616-632.
    11. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    12. Cominetti, Roberto & Melo, Emerson & Sorin, Sylvain, 2010. "A payoff-based learning procedure and its application to traffic games," Games and Economic Behavior, Elsevier, vol. 70(1), pages 71-83, September.
    13. de Bekker-Grob, E.W. & Donkers, B. & Bliemer, M.C.J. & Veldwijk, J. & Swait, J.D., 2020. "Can healthcare choice be predicted using stated preference data?," Social Science & Medicine, Elsevier, vol. 246(C).
    14. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    15. Honora Smith & Christine Currie & Pornpimol Chaiwuttisak & Andreas Kyprianou, 2018. "Patient choice modelling: how do patients choose their hospitals?," Health Care Management Science, Springer, vol. 21(2), pages 259-268, June.
    16. Stolk-Vos, Aline C. & Attema, Arthur E. & Manzulli, Michele & van de Klundert, Joris J., 2022. "Do patients and other stakeholders value health service quality equally? A prospect theory based choice experiment in cataract care," Social Science & Medicine, Elsevier, vol. 294(C).
    17. Yun Liu & Qingxia Kong & Shasha Yuan & Joris van de Klundert, 2018. "Factors influencing choice of health system access level in China: A systematic review," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-21, August.
    18. Zhang, Yue & Atkins, Derek, 2019. "Medical facility network design: User-choice and system-optimal models," European Journal of Operational Research, Elsevier, vol. 273(1), pages 305-319.
    19. Hau Leung Lee & Morris A. Cohen, 1985. "Equilibrium Analysis of Disaggregate Facility Choice Systems Subject to Congestion-Elastic Demand," Operations Research, INFORMS, vol. 33(2), pages 293-311, April.
    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. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    2. Germano, Fabrizio & Lugosi, Gabor, 2007. "Global Nash convergence of Foster and Young's regret testing," Games and Economic Behavior, Elsevier, vol. 60(1), pages 135-154, July.
    3. Page, Kenneth & Pérez, Juan & Telha, Claudio & García-Echalar, Andrés & López-Ospina, Héctor, 2021. "Optimal bundle composition in competition for continuous attributes," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1168-1187.
    4. Cominetti, Roberto & Melo, Emerson & Sorin, Sylvain, 2010. "A payoff-based learning procedure and its application to traffic games," Games and Economic Behavior, Elsevier, vol. 70(1), pages 71-83, September.
    5. Sergiu Hart & Andreu Mas-Colell, 2013. "Stochastic Uncoupled Dynamics And Nash Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 8, pages 165-189, World Scientific Publishing Co. Pte. Ltd..
    6. Philippe Jehiel & Aviman Satpathy, 2024. "Learning to be Indifferent in Complex Decisions: A Coarse Payoff-Assessment Model," Papers 2412.09321, arXiv.org, revised Dec 2024.
    7. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).
    8. Sacha Bourgeois-Gironde, 2017. "How regret moves individual and collective choices towards rationality," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 11, pages 188-204, Edward Elgar Publishing.
    9. Jalili Marand, Ata & Hoseinpour, Pooya, 2024. "A congested facility location problem with strategic customers," European Journal of Operational Research, Elsevier, vol. 318(2), pages 442-456.
    10. Benaïm, Michel & Hofbauer, Josef & Hopkins, Ed, 2009. "Learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1694-1709, July.
    11. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    12. Watanabe, Hajime & Maruyama, Takuya, 2024. "A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership," Journal of choice modelling, Elsevier, vol. 51(C).
    13. Viossat, Yannick, 2008. "Evolutionary dynamics may eliminate all strategies used in correlated equilibrium," Mathematical Social Sciences, Elsevier, vol. 56(1), pages 27-43, July.
    14. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
    15. Guevara, C. Angelo & Tang, Yue & Gao, Song, 2018. "The initial condition problem with complete history dependency in learning models for travel choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 850-861.
    16. Watanabe, Hajime & Maruyama, Takuya, 2023. "A Bayesian instrumental variable model for multinomial choice with correlated alternatives," Journal of choice modelling, Elsevier, vol. 46(C).
    17. Breitmoser, Yves, 2019. "Knowing me, imagining you: Projection and overbidding in auctions," Games and Economic Behavior, Elsevier, vol. 113(C), pages 423-447.
    18. Karl Schlag & Andriy Zapechelnyuk, 2009. "Decision Making in Uncertain and Changing Environments," Discussion Papers 19, Kyiv School of Economics.
    19. Cason, Timothy N. & Friedman, Daniel & Hopkins, Ed, 2010. "Testing the TASP: An experimental investigation of learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 145(6), pages 2309-2331, November.
    20. Funai Naoki, 2014. "An Adaptive Learning Model with Foregone Payoff Information," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 14(1), pages 149-176, January.

    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:eee:eejocm:v:52:y:2024:i:c:s1755534524000411. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    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.