IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v24y2021i2d10.1007_s10729-020-09543-z.html
   My bibliography  Save this article

An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency

Author

Listed:
  • Andrés Miniguano-Trujillo

    (The University of Edinburgh, Bayes Centre)

  • Fernanda Salazar

    (Department of Mathematics – Escuela Politécnica Nacional)

  • Ramiro Torres

    (Department of Mathematics – Escuela Politécnica Nacional)

  • Patricio Arias

    (Ecuadorian Association of Evidence-Based Psychology and Psychotherapy (AEPPBE))

  • Koraima Sotomayor

    (The University of Edinburgh)

Abstract

The Covid–19 pandemic challenges healthcare systems worldwide while severely impacting mental health. As a result, the rising demand for psychological assistance during crisis times requires early and effective intervention. This contributes to the well-being of the public and front-line workers and prevents mental health disorders. Many countries are offering diverse and accessible services of tele-psychological intervention; Ecuador is not the exception. The present study combines statistical analyses and discrete optimization techniques to solve the problem of assigning patients to therapists for crisis intervention with a single tele-psychotherapy session. The statistical analyses showed that professionals and healthcare workers in contact with Covid–19 patients or with a confirmed diagnosis had a significant relationship with suicide risk, sadness, experiential avoidance, and perception of severity. Moreover, some Covid–19-related variables were found to be predictors of sadness and suicide risk as unveiled via path analysis. This allowed categorizing patients according to their screening and grouping therapists according to their qualifications. With this stratification, a multi-periodic optimization model and a heuristic are proposed to find an adequate assignment of patients to therapists over time. The integer programming model was validated with real-world data, and its results were applied in a volunteer program in Ecuador.

Suggested Citation

  • Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.
    • Handle: RePEc:kap:hcarem:v:24:y:2021:i:2:d:10.1007_s10729-020-09543-z
    DOI: 10.1007/s10729-020-09543-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-020-09543-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10729-020-09543-z?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. Sarah Dryhurst & Claudia R. Schneider & John Kerr & Alexandra L. J. Freeman & Gabriel Recchia & Anne Marthe van der Bles & David Spiegelhalter & Sander van der Linden, 2020. "Risk perceptions of COVID-19 around the world," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 994-1006, August.
    2. Kuiper, Alex & Mandjes, Michel, 2015. "Appointment scheduling in tandem-type service systems," Omega, Elsevier, vol. 57(PB), pages 145-156.
    3. Zainudin Awang & Asyraf Afthanorhan & Mustafa Mamat, 2016. "The Likert scale analysis using parametric based Structural Equation Modeling (SEM)," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 4(1), pages 13-21, June.
    4. Murray Côté & Siddhartha Syam & W. Vogel & Diane Cowper, 2007. "A mixed integer programming model to locate traumatic brain injury treatment units in the Department of Veterans Affairs: a case study," Health Care Management Science, Springer, vol. 10(3), pages 253-267, September.
    5. Vieira, Bruno & Demirtas, Derya & van de Kamer, Jeroen B. & Hans, Erwin W. & van Harten, Wim, 2018. "A mathematical programming model for optimizing the staff allocation in radiotherapy under uncertain demand," European Journal of Operational Research, Elsevier, vol. 270(2), pages 709-722.
    6. Belií«n, Jeroen & Demeulemeester, Erik, 2008. "A branch-and-price approach for integrating nurse and surgery scheduling," European Journal of Operational Research, Elsevier, vol. 189(3), pages 652-668, September.
    7. Schoenfelder, Jan & Bretthauer, Kurt M. & Wright, P. Daniel & Coe, Edwin, 2020. "Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience," European Journal of Operational Research, Elsevier, vol. 283(1), pages 390-403.
    8. Eduardo Pérez & Lewis Ntaimo & César Malavé & Carla Bailey & Peter McCormack, 2013. "Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine," Health Care Management Science, Springer, vol. 16(4), pages 281-299, December.
    9. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    10. D. Michael Warner & Juan Prawda, 1972. "A Mathematical Programming Model for Scheduling Nursing Personnel in a Hospital," Management Science, INFORMS, vol. 19(4-Part-1), pages 411-422, December.
    11. Bellanti, F. & Carello, G. & Della Croce, F. & Tadei, R., 2004. "A greedy-based neighborhood search approach to a nurse rostering problem," European Journal of Operational Research, Elsevier, vol. 153(1), pages 28-40, February.
    12. Van-Anh Truong, 2015. "Optimal Advance Scheduling," Management Science, INFORMS, vol. 61(7), pages 1584-1597, July.
    13. Bard, Jonathan F. & Purnomo, Hadi W., 2005. "A column generation-based approach to solve the preference scheduling problem for nurses with downgrading," Socio-Economic Planning Sciences, Elsevier, vol. 39(3), pages 193-213, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alec Morton & Ebru Bish & Itamar Megiddo & Weifen Zhuang & Roberto Aringhieri & Sally Brailsford & Sarang Deo & Na Geng & Julie Higle & David Hutton & Mart Janssen & Edward H Kaplan & Jianbin Li & Món, 2021. "Introduction to the special issue: Management Science in the Fight Against Covid-19," Health Care Management Science, Springer, vol. 24(2), pages 251-252, June.

    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. Hyun-Jung Alvarez-Oh & Hari Balasubramanian & Ekin Koker & Ana Muriel, 2018. "Stochastic Appointment Scheduling in a Team Primary Care Practice with Two Flexible Nurses and Two Dedicated Providers," Service Science, INFORMS, vol. 10(3), pages 241-260, September.
    2. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    3. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    4. Reihaneh, Mohammad & Ansari, Sina & Farhadi, Farbod, 2023. "Patient appointment scheduling at hemodialysis centers: An exact branch and price approach," European Journal of Operational Research, Elsevier, vol. 309(1), pages 35-52.
    5. Wright, P. Daniel & Mahar, Stephen, 2013. "Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction," Omega, Elsevier, vol. 41(6), pages 1042-1052.
    6. Isabel Kaluza & Guido Voigt & Knut Haase & Antonia Dietze, 2024. "Control of Online-Appointment Systems When the Booking Status Signals Quality of Service," Schmalenbach Journal of Business Research, Springer, vol. 76(3), pages 397-432, September.
    7. Eduardo Pérez, 2022. "An Appointment Planning Algorithm for Reducing Patient Check-In Waiting Times in Multispecialty Outpatient Clinics," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    8. Tito Homem-de-Mello & Qingxia Kong & Rodrigo Godoy-Barba, 2022. "A Simulation Optimization Approach for the Appointment Scheduling Problem with Decision-Dependent Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2845-2865, September.
    9. Jiang, Yangzi & Abouee-Mehrizi, Hossein & Diao, Yuhe, 2020. "Data-driven analytics to support scheduling of multi-priority multi-class patients with wait time targets," European Journal of Operational Research, Elsevier, vol. 281(3), pages 597-611.
    10. Paola Cappanera & Filippo Visintin & Carlo Banditori & Daniele Feo, 2019. "Evaluating the long-term effects of appointment scheduling policies in a magnetic resonance imaging setting," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 212-254, March.
    11. Christos Zacharias & Tallys Yunes, 2020. "Multimodularity in the Stochastic Appointment Scheduling Problem with Discrete Arrival Epochs," Management Science, INFORMS, vol. 66(2), pages 744-763, February.
    12. Alex Kuiper & Robert H. Lee, 2022. "Appointment Scheduling for Multiple Servers," Management Science, INFORMS, vol. 68(10), pages 7422-7440, October.
    13. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    14. Liping Zhou & Na Geng & Zhibin Jiang & Shan Jiang, 2022. "Integrated Multiresource Capacity Planning and Multitype Patient Scheduling," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 129-149, January.
    15. Baş, Seda & Carello, Giuliana & Lanzarone, Ettore & Yalçındağ, Semih, 2018. "An appointment scheduling framework to balance the production of blood units from donation," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1124-1143.
    16. Sharan Srinivas & A. Ravi Ravindran, 2020. "Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers," Health Care Management Science, Springer, vol. 23(3), pages 360-386, September.
    17. Miao Bai & Bjorn Berg & Esra Sisikoglu Sir & Mustafa Y. Sir, 2023. "Partially partitioned templating strategies for outpatient specialty practices," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 301-318, January.
    18. Bowen Jiang & Jiafu Tang & Chongjun Yan, 2019. "A comparison of fixed and variable capacity-addition policies for outpatient capacity allocation," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 150-182, January.
    19. Creemers, Stefan & Lambrecht, Marc R. & Beliën, Jeroen & Van den Broeke, Maud, 2021. "Evaluation of appointment scheduling rules: A multi-performance measurement approach," Omega, Elsevier, vol. 100(C).
    20. Deborah L. Kellogg & Steven Walczak, 2007. "Nurse Scheduling: From Academia to Implementation or Not?," Interfaces, INFORMS, vol. 37(4), pages 355-369, August.

    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:kap:hcarem:v:24:y:2021:i:2:d:10.1007_s10729-020-09543-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.