Journal of the Operational Research Society

, Volume 64, Issue 6, pp 912–924 | Cite as

Determination of number of dedicated OR's and supporting pricing mechanisms for emergent surgeries

General Paper


Inefficient management of emergent surgeries in hospitals can, in part, be attributed to a lack of rigorous analysis appropriate to capturing the underlying uncertainties inherent to this process and a pricing mechanism to ensure its financial viability. We develop a non-preemptive multi-priority queueing model that optimally manages emergent surgeries and supports the resource allocation decision-making process. Specifically, we utilize queueing and discrete event simulation to develop empirical models for determining the required number of emergent operating rooms for a hospital surgical department. We also present algorithms that estimate the appropriate pricing for patient surgeries differentiated by priority level given the patient demand and the resources reserved to meet this demand.


hospitals practice of operations research emergent surgeries simulation queueing decision support systems 


  1. Albright SC, Winston WL and Zappe CJ (2009). Data Analysis and Decision Making, 4/e. South-Western Cengage Learning: Mason, OH.Google Scholar
  2. Blake JT, Dexter F and Donald J (2002). Operating rooms managers’ use of integer programming for assigning block time to surgical groups: A case study. Anesthesia & Analgesia 94 (1): 143–148.Google Scholar
  3. Cardoen B, Demeulemeester E and Beliën J (2010). Operating room planning and scheduling: A literature review. European Journal of Operational Research 201 (3): 921–932.CrossRefGoogle Scholar
  4. Cohen J (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates: Hillsdale, NJ.Google Scholar
  5. Denton B, Rahman AS, Nelson H and Bailey AC (2006). Simulation of a multiple operating room surgical suite. In: Perrone LF, Wieland FP, Liu J, Lawson BG, Nicol DM and Fujimoto RM (eds). Proceedings of the 2006 Winter Simulation Conference, Monterey, pp 414–424.Google Scholar
  6. Denton B, Viapiano J and Vogl A (2007). Optimization of surgery sequencing and scheduling decisions under uncertainty. Health Care Management Science 10 (1): 13–24.CrossRefGoogle Scholar
  7. Gerchak Y, Gupta D and Henig M (1996). Reservation planning for elective surgery under uncertain demand for emergency surgery. Management Science 42 (3): 321–334.CrossRefGoogle Scholar
  8. Goldman J and Knappenberger H (1968). How to determine the optimum number of operating rooms. Modern Hospital 111 (3): 114–116.Google Scholar
  9. Guerriero F and Guido R (2011). Operational research in the management of the operating theatre: A survey. Health Care Management Science 14 (1): 89–114.CrossRefGoogle Scholar
  10. HFMA (2003). Achieving operating room efficiency through process integration. Health Care Financial Management 57 (3): S1–S7.Google Scholar
  11. HFMA (2004). Strategic price setting: ensuring your financial viability through price modeling. Health Care Financial Management 58 (7): 1–7.Google Scholar
  12. Jebali A, Hadj Alouane AB and Ladet P (2006). Operating rooms scheduling. International Journal of Production Economics 99 (1–2): 52–62.CrossRefGoogle Scholar
  13. Lamiri ML, Xie D and Zhang S (2008). Column generation approach to operating theater planning with elective and emergency patients. IIE Transactions 40 (9): 838–852.CrossRefGoogle Scholar
  14. Levtzion-Korach O, Murphy KG, Madden S and Dempsey C (2010). For urgent and emergent cases, which one goes to the OR first? OR Manager 26 (7): 1,11–13.Google Scholar
  15. Litvak E and Long MC (2000). Cost and quality under managed care: Irreconcilable differences? American Journal of Managed Care 6 (3): 305–312.Google Scholar
  16. Litvak E, Long MC, Cooper AB and McManus ML (2001). Emergency department diversion: causes and solutions. Academic Emergency Medicine 8 (11): 1108–1110.Google Scholar
  17. Ozkarahan I (2000). Allocation of surgeries to operating rooms by goal programming. Journal of Medical Systems 24 (6): 339–378.CrossRefGoogle Scholar
  18. Pai J-Y, Petry F and Fos P (1997). Employing simulation to optimize the number of operating rooms in hospitals. Technical Report. In: Proceedings of the Medical Sciences Simulation Conference. The Society for Computer Simulation International (SCS): Phoenix, pp 36–42.Google Scholar
  19. Persson MJ and Persson JA (2010). Analysing management policies for operating room planning using simulation. Health Care Management Science 13 (2): 182–191.CrossRefGoogle Scholar
  20. ProModel (2010). Software website,, accessed May 2010.
  21. Sier D, Tobin P and McGurk C (1997). Scheduling surgical procedures. Journal of the Operational Research Society 48 (9): 884–891.CrossRefGoogle Scholar
  22. Stanciu A, Vargas L and May J (2010). A revenue management approach for managing operating room capacity. In: Johansson B, Jain S, Montoya-Torres J, Hugan J, and Yücesan E (eds). Proceedings of the 2010 Winter Simulation Conference. Baltimore, pp 2444–2454.CrossRefGoogle Scholar
  23. Ross SM (2003). Introduction to Probability Models, 8/e. Academic Press: San Diego, CA.Google Scholar
  24. Tucker JB, Barone JE, Cecere J, Blabey RG and Rha CK (1999). Using queueing theory to determine operating room staffing needs. Journal of Trauma 46 (1): 71–79.CrossRefGoogle Scholar
  25. van Oostrum JM, et al (2008). A simulation model for determining the optimal size of emergency teams on call in the operating room at night. Anesthesia & Analgesia 107 (5): 1655–1662.CrossRefGoogle Scholar
  26. Wullink G, Houdenhoven MV, Hans EW, Oostrum JM, van der Lans M and Kazemier G (2007). Closing emergency operating rooms improves efficiency. Journal of Medical Systems 31 (6): 543–546.CrossRefGoogle Scholar
  27. Zhang B, Murali P, Dessouky MM and Belson D (2009). A mixed integer programming approach for allocating operating room capacity. Journal of the Operational Research Society 60 (5): 663–673.CrossRefGoogle Scholar
  28. Zonderland ME, Boucherie RJ, Litvak N and Vleggeert-Lankamp C (2010). Planning and scheduling of semi-urgent surgeries. Health Care Management Science 13 (3): 256–267.CrossRefGoogle Scholar

Copyright information

© Operational Research Society 2012

Authors and Affiliations

  1. 1.Kennesaw State UniversityUSA

Personalised recommendations