IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v43y2013i5p449-461.html
   My bibliography  Save this article

Improving Patient Access to Chemotherapy Treatment at Duke Cancer Institute

Author

Listed:
  • Jonathan C. Woodall

    (Duke Medicine, Durham, North Carolina 27710)

  • Tracy Gosselin

    (Duke Cancer Institute, Durham, North Carolina 27710)

  • Amy Boswell

    (Duke Cancer Institute, Durham, North Carolina 27710)

  • Michael Murr

    (Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina 27695)

  • Brian T. Denton

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

This paper describes how we applied simulation and optimization in combination to improve patient flow within the Duke Cancer Institute, a large cancer center. We first developed a discrete-event simulation model to predict patient waiting time and resource utilization throughout various parts of the center, including the outpatient clinic, radiology, the pharmacy, laboratory services, and the oncology treatment facility. Simulation model studies showed that nurse unavailability during oncology treatment causes a serious bottleneck in patient flow. Next, we developed a mixed-integer programming model to relieve the bottleneck by optimizing weekly and monthly scheduling of different types of nurses. Finally, we developed a novel simulation-optimization model to further relieve the bottleneck by optimizing the starting times of nurse shifts. Our paper summarizes our main findings and the resulting recommendations that Duke Cancer Institute implemented.

Suggested Citation

  • Jonathan C. Woodall & Tracy Gosselin & Amy Boswell & Michael Murr & Brian T. Denton, 2013. "Improving Patient Access to Chemotherapy Treatment at Duke Cancer Institute," Interfaces, INFORMS, vol. 43(5), pages 449-461, October.
  • Handle: RePEc:inm:orinte:v:43:y:2013:i:5:p:449-461
    DOI: 10.1287/inte.2013.0695
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2013.0695
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2013.0695?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. Pablo Santibáñez & Vincent Chow & John French & Martin Puterman & Scott Tyldesley, 2009. "Reducing patient wait times and improving resource utilization at British Columbia Cancer Agency’s ambulatory care unit through simulation," Health Care Management Science, Springer, vol. 12(4), pages 392-407, December.
    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. Guillaume Lamé & Oualid Jouini & Julie Stal-Le Cardinal, 2016. "Outpatient Chemotherapy Planning: a Literature Review with Insights from a Case Study," Post-Print hal-01324488, HAL.
    2. Bohui Liang & Ayten Turkcan & Mehmet Erkan Ceyhan & Keith Stuart, 2015. "Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7177-7190, December.
    3. Menel Benzaid & Nadia Lahrichi & Louis-Martin Rousseau, 2020. "Chemotherapy appointment scheduling and daily outpatient–nurse assignment," Health Care Management Science, Springer, vol. 23(1), pages 34-50, March.
    4. David Scheinker & Margaret L. Brandeau, 2020. "Implementing Analytics Projects in a Hospital: Successes, Failures, and Opportunities," Interfaces, INFORMS, vol. 50(3), pages 176-189, May.
    5. Alireza F. Hesaraki & Nico P. Dellaert & Ton Kok, 2020. "Integrating nurse assignment in outpatient chemotherapy appointment scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 935-963, December.
    6. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.
    7. Hadid, Majed & Elomri, Adel & Mekkawy, Tarek El & Jouini, Oualid & Kerbache, Laoucine & Hamad, Anas, 2022. "Operations management of outpatient chemotherapy process: An optimization-oriented comprehensive review," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Kibaek Kim & Sanjay Mehrotra, 2015. "A Two-Stage Stochastic Integer Programming Approach to Integrated Staffing and Scheduling with Application to Nurse Management," Operations Research, INFORMS, vol. 63(6), pages 1431-1451, December.
    9. M. Heshmat & A. Eltawil, 2021. "Solving operational problems in outpatient chemotherapy clinics using mathematical programming and simulation," Annals of Operations Research, Springer, vol. 298(1), pages 289-306, March.
    10. Alireza F. Hesaraki & Nico P. Dellaert & Ton Kok, 2023. "Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration," Health Care Management Science, Springer, vol. 26(1), pages 117-137, March.

    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. Jaime González & Juan-Carlos Ferrer & Alejandro Cataldo & Luis Rojas, 2019. "A proactive transfer policy for critical patient flow management," Health Care Management Science, Springer, vol. 22(2), pages 287-303, June.
    2. Brian Zoll & Pratik J. Parikh & Jennie Gallimore & Stephen Harrell & Brian Burke, 2015. "Impact of Diabetes E-Consults on Outpatient Clinic Workflow," Medical Decision Making, , vol. 35(6), pages 745-757, August.
    3. A. G. Leeftink & I. M. H. Vliegen & E. W. Hans, 2019. "Stochastic integer programming for multi-disciplinary outpatient clinic planning," Health Care Management Science, Springer, vol. 22(1), pages 53-67, March.
    4. Proudlove, N.C. & Bisogno, S. & Onggo, B.S.S. & Calabrese, A. & Levialdi Ghiron, N., 2017. "Towards fully-facilitated discrete event simulation modelling: Addressing the model coding stage," European Journal of Operational Research, Elsevier, vol. 263(2), pages 583-595.
    5. Xiuli Qu & Yidong Peng & Nan Kong & Jing Shi, 2013. "A two-phase approach to scheduling multi-category outpatient appointments – A case study of a women’s clinic," Health Care Management Science, Springer, vol. 16(3), pages 197-216, September.
    6. Tugba Cayirli & Kum Khiong Yang, 2019. "Altering the Environment to Improve Appointment System Performance," Service Science, INFORMS, vol. 11(2), pages 138-154, June.
    7. Agnetis, Alessandro & Bianciardi, Caterina & Iasparra, Nicola, 2019. "Integrating lean thinking and mathematical optimization: A case study in appointment scheduling of hematological treatments," Operations Research Perspectives, Elsevier, vol. 6(C).
    8. Ming Lv & Yi Li & Bo Kou & Zhili Zhou, 2017. "Integer programming for improving radiotherapy treatment efficiency," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-9, July.
    9. Angelica Zazzera & Francesco Longo, 2018. "Operations management delle cure primarie: quali standard di servizio per servire l?intera popolazione cronica?," MECOSAN, FrancoAngeli Editore, vol. 2018(108), pages 55-73.
    10. Chong Pan & Dali Zhang & Audrey Kon & Charity Wai & Woo Ang, 2015. "Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment," Health Care Management Science, Springer, vol. 18(2), pages 137-155, June.
    11. P. Troy & N. Lahrichi & D. Porubska & L. Rosenberg, 2020. "Fine-grained simulation optimization for the design and operations of a multi-activity clinic," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 599-628, September.
    12. Dimitrios Stathopoulos & Eva Ekvall Hansson & Kjerstin Stigmar, 2021. "Exploring the Environment behind In-Patient Falls and Their Relation to Hospital Overcrowdedness—A Register-Based Observational Study," IJERPH, MDPI, vol. 18(20), pages 1-10, October.
    13. Baril, Chantal & Gascon, Viviane & Miller, Jonathan & Côté, Nadine, 2016. "Use of a discrete-event simulation in a Kaizen event: A case study in healthcare," European Journal of Operational Research, Elsevier, vol. 249(1), pages 327-339.
    14. Guillaume Lamé & Oualid Jouini & Julie Stal-Le Cardinal, 2016. "Outpatient Chemotherapy Planning: a Literature Review with Insights from a Case Study," Post-Print hal-01324488, HAL.

    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:inm:orinte:v:43:y:2013:i:5:p:449-461. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.