Advertisement

Health Care Management Science

, Volume 17, Issue 1, pp 60–76 | Cite as

Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking

  • Yasin GocgunEmail author
  • Martin L. Puterman
Article

Abstract

We study a scheduling problem in which arriving patients require appointments at specific future days within a treatment specific time window. This research is motivated by a study of chemotherapy scheduling practices at the British Columbia Cancer Agency (Canada). We formulate this problem as a Markov Decision Process (MDP). Since the resulting MDPs are intractable to exact methods, we employ linear-programming-based Approximate Dynamic Programming (ADP) to obtain approximate solutions. Using simulation, we compare the performance of the resulting ADP policies to practical and easy-to-use heuristic decision rules under diverse scenarios. The results indicate that ADP is promising in several scenarios, and that a specific easy-to-use heuristic performs well in the idealized chemotherapy scheduling setting we study.

Keywords

Chemotherapy scheduling Markov decision processes Approximate dynamic programming 

Notes

Acknowledgments

This research was supported by Martin L. Puterman’s NSERC Discovery Grant and the NSERC CREATE Program in Healthcare Operations and Information Management program. We wish to also thank Antoine Saure for providing us the ADP GAMS code he wrote for solving the kind of problem studied in this research.

References

  1. Adelman D, Klabjan D (2011) Computing near-optimal policies in generalized joint replenishment. INFORMS J Comput, doi: 10.1287/ijoc.1100.0433
  2. Bailey NT (1952) A study of queues and appointment systems in hospital out-patient departments, with special reference to waiting-times. J R Stat Soc B14:185–99Google Scholar
  3. Bertsekas D, Tsitsiklis J (1996) Neuro-dynamic programming. Athena ScientificGoogle Scholar
  4. Cayirli T, Veral E (2003) Outpatient scheduling in health care: a review of literature. Prod Oper Manag 12:519–549CrossRefGoogle Scholar
  5. Diedrich J, Plank DP (2003) Efficient system to schedule chemotherapy and support therapies for oncology nurses. Oncol Nurs Soc Congr Abstr, 76Google Scholar
  6. Fries BE, Marathe VP (1981) Determination of optimal variable-sized multiple-block appointment systems. Oper Res 29:324–45CrossRefGoogle Scholar
  7. Gerchak Y, Gupta D, Henig M (1996) Reservation planning for elective surgery under uncertain demand for emergency surgery. Manag Sci 42(3):321–334CrossRefGoogle Scholar
  8. Gocgun Y, Bresnahan B, Ghate A, Gunn M (2011) A markov decision process approach to multi-category patient scheduling in a diagnostic facility. Artif Intell Med 53:73–81CrossRefGoogle Scholar
  9. Gocgun Y, Ghate A (2012) Lagrangian relaxation and constraint generation for allocation and advanced scheduling. Comput Oper Res 39:2323–2336CrossRefGoogle Scholar
  10. Green LV, Savin S, Wang B (2008) Managing patient service in a diagnostic medical facility. Oper Res 54:11–25CrossRefGoogle Scholar
  11. Hawley E, Carter NG (2009) An acuity rating system for infusion center nurse staffing: the cleveland clinic cancer center at hillcrest hospital experience. Oncol Issues November/December, 34–37Google Scholar
  12. Klassen KJ, Rohleder TR (2004) Outpatient appointment scheduling with urgent clients in a dynamic, multi-period environment. Int J Serv Ind Manag 15(2):167–186CrossRefGoogle Scholar
  13. Kleywegt AJ, Papastavrou JD (1998) The dynamic and stochastic knapsack problem. Oper Res 46(1):17–35CrossRefGoogle Scholar
  14. Kolisch R, Sickinger S (2008) Providing radiology health care services to stochastic demand of different customer classes. OR Spectrum 30:375–395CrossRefGoogle Scholar
  15. Lamiri M, Xie X, Dolgui A, Grimaud F (2008) A stochastic model for operating room planning with elective and emergency demand for surgery. Eur J Oper Res 185(3):1026–1037CrossRefGoogle Scholar
  16. Langhorn M, Morrison C (2001) Redesigning processes in ambulatory chemotherapy: creating a patient appointment scheduling system: part II. Can Oncol Nurs J 11(3):157–159Google Scholar
  17. Lindley DV (1952) The theory of queues with a single server. Math Proc Camb Philos Soc 48:277–289CrossRefGoogle Scholar
  18. Liu N, Ziya S, Kulkarni VG (2010) Dynamic scheduling of outpatient appointments under patient no-shows and cancellations. Manuf Serv Oper Manag 12(2):347–364Google Scholar
  19. Min D, Yih Y (2010) An elective surgery scheduling problem considering patient priority. Comput Oper Res 37:1091–1099CrossRefGoogle Scholar
  20. Mondschein SV, Weintraub GY (2003) Appointment policies in service operations: a critical analysis of the economic framework. Prod Oper Manag 12:266–286CrossRefGoogle Scholar
  21. Patrick J, Puterman M, Queyranne M (2008) Dynamic multipriority patient scheduling for a diagnostic resource. Oper Res 56(6):1507–1525CrossRefGoogle Scholar
  22. Patrick J (2012) A Markov decision model for determining optimal outpatient scheduling. Health Care Manag Sci 15(2):91–102. doi: 10.1007/s10729-011-9185-4 CrossRefGoogle Scholar
  23. Powell WB (2007) Approximate dynamic programming: solving the curses of dimensionality. WileyGoogle Scholar
  24. Powell WB (2008) Approximate dynamic programming: lessons from the field. In: Proceedings of the 2008 winter simulation conference, pp. 205–214Google Scholar
  25. Puterman M (1994) Markov decision processes. Wiley, New JerseyCrossRefGoogle Scholar
  26. Santibanez P, Aristizabal R, Chow VS, Huangh W, Kollmannsberger C, Nordin T, Runzer N, Puterman ML, Tyldesley S (2012) Improving chemotheraphy scheduling and delivery through process redesign and advanced analytics. Jt Comm J Qual Patient Saf 34(12):541–553Google Scholar
  27. Saure A, Patrick J, Tyldesley S, Puterman ML (2012) Dynamic multi-appointment patient scheduling for radiation therapy. Eur J Oper Res 223:573–584CrossRefGoogle Scholar
  28. Turkcan A, Zeng B, Lawley M, Chemotherapy operations planning and scheduling. IIE Trans on Healthc Sys Eng, to appearGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Centre for Maintenance Optimization Reliability Engineering, Department of Mechanical Industrial EngineeringUniversity of TorontoTorontoCanada
  2. 2.Operations and Logistics Division, Sauder School of BusinessUniversity of British ColumbiaVancouverCanada

Personalised recommendations