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Dynamic multi-appointment patient scheduling for radiation therapy

Author

Listed:
  • Sauré, Antoine
  • Patrick, Jonathan
  • Tyldesley, Scott
  • Puterman, Martin L.

Abstract

Seeking to reduce the potential impact of delays on radiation therapy cancer patients such as psychological distress, deterioration in quality of life and decreased cancer control and survival, and motivated by inefficiencies in the use of expensive resources, we undertook a study of scheduling practices at the British Columbia Cancer Agency (BCCA). As a result, we formulated and solved a discounted infinite-horizon Markov decision process for scheduling cancer treatments in radiation therapy units. The main purpose of this model is to identify good policies for allocating available treatment capacity to incoming demand, while reducing wait times in a cost-effective manner. We use an affine architecture to approximate the value function in our formulation and solve an equivalent linear programming model through column generation to obtain an approximate optimal policy for this problem. The benefits from the proposed method are evaluated by simulating its performance for a practical example based on data provided by the BCCA.

Suggested Citation

  • Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
    • Handle: RePEc:eee:ejores:v:223:y:2012:i:2:p:573-584
    DOI: 10.1016/j.ejor.2012.06.046
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    References listed on IDEAS

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    1. Mehmet A. Begen & Maurice Queyranne, 2011. "Appointment Scheduling with Discrete Random Durations," Mathematics of Operations Research, INFORMS, vol. 36(2), pages 240-257, May.
    2. Kim, Minsun & Ghate, Archis & Phillips, Mark H., 2012. "A stochastic control formalism for dynamic biologically conformal radiation therapy," European Journal of Operational Research, Elsevier, vol. 219(3), pages 541-556.
    3. Lamiri, Mehdi & Xie, Xiaolan & Dolgui, Alexandre & Grimaud, Frederic, 2008. "A stochastic model for operating room planning with elective and emergency demand for surgery," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1026-1037, March.
    4. Daniel Adelman & Diego Klabjan, 2012. "Computing Near-Optimal Policies in Generalized Joint Replenishment," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 148-164, February.
    5. Yigal Gerchak & Diwakar Gupta & Mordechai Henig, 1996. "Reservation Planning for Elective Surgery Under Uncertain Demand for Emergency Surgery," Management Science, INFORMS, vol. 42(3), pages 321-334, March.
    6. Conforti, D. & Guerriero, F. & Guido, R., 2010. "Non-block scheduling with priority for radiotherapy treatments," European Journal of Operational Research, Elsevier, vol. 201(1), pages 289-296, February.
    7. Edward J. Rising & Robert Baron & Barry Averill, 1973. "A Systems Analysis of a University-Health-Service Outpatient Clinic," Operations Research, INFORMS, vol. 21(5), pages 1030-1047, October.
    8. Schütz, Hans-Jörg & Kolisch, Rainer, 2012. "Approximate dynamic programming for capacity allocation in the service industry," European Journal of Operational Research, Elsevier, vol. 218(1), pages 239-250.
    9. D. P. de Farias & B. Van Roy, 2003. "The Linear Programming Approach to Approximate Dynamic Programming," Operations Research, INFORMS, vol. 51(6), pages 850-865, December.
    10. Daniel Adelman & Adam J. Mersereau, 2008. "Relaxations of Weakly Coupled Stochastic Dynamic Programs," Operations Research, INFORMS, vol. 56(3), pages 712-727, June.
    11. Misic, V.V. & Aleman, D.M. & Sharpe, M.B., 2010. "Neighborhood search approaches to non-coplanar beam orientation optimization for total marrow irradiation using IMRT," European Journal of Operational Research, Elsevier, vol. 205(3), pages 522-527, September.
    12. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    13. Lim, Gino J. & Cao, Wenhua, 2012. "A two-phase method for selecting IMRT treatment beam angles: Branch-and-Prune and local neighborhood search," European Journal of Operational Research, Elsevier, vol. 217(3), pages 609-618.
    14. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    15. Alexander Erdelyi & Huseyin Topaloglu, 2009. "Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods," IISE Transactions, Taylor & Francis Journals, vol. 41(6), pages 498-510.
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