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Scheduling operating rooms: achievements, challenges and pitfalls

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Abstract

In hospitals, the operating room (OR) is a particularly expensive facility and thus efficient scheduling is imperative. This can be greatly supported by using advanced methods that are discussed in the academic literature. In order to help researchers and practitioners to select new relevant articles, we classify the recent OR planning and scheduling literature into tables regarding patient type, used performance measures, decisions made, OR up- and downstream facilities, uncertainty, research methodology and testing phase. Based on these classifications, we identify trends and promising topics. Additionally, we recognize three common pitfalls that hamper the adoption of research results by stakeholders: the lack of a clear choice of authors on whether to target researchers (contributing advanced methods) or practitioners (providing managerial insights), the use of ill-fitted performance measures in models and the failure to understandably report on the hospital setting and method-related assumptions. We provide specific guidelines that help to avoid these pitfalls. First, we show how to build up an article based on the choice of the target group (i.e., researchers or practitioners). Making a clear distinction between target groups impacts the problem setting, the research task, the reported findings, and the conclusions. Second, we discuss points that need to be considered by researchers when deciding on the used performance measures. Third, we list the assumptions that need to be included in articles in order to enable readers to decide whether the presented research is relevant to them.

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References

  1. Abdelrasol, Z., Harraz, N., & Eltawil, A. (2014). Operating room scheduling problems: A survey and a proposed solution framework. Netherlands: Springer.

    Google Scholar 

  2. Adan, I., Bekkers, J., Dellaert, N., Vissers, J., & Yu, X. T. (2009). Patient mix optimisation and stochastic resource requirements: A case study in cardiothoracic surgery planning. Health Care Management Science, 12, 129–141.

    Article  Google Scholar 

  3. Adan, I., Bekkers, J., Dellaert, N., Jeunet, J., & Vissers, J. (2011). Improving operational effectiveness of tactical master plans for emergency and elective patients under stochastic demand and capacitated resources. European Journal of Operational Research, 213, 290–308.

    Article  Google Scholar 

  4. Agnetis, A., Coppi, A., Corsini, M., Dellino, G., Meloni, C., & Pranzo, M. (2012). Long term evaluation of operating theater planning policies. Operations Research for Health Care, 1, 95–104.

    Article  Google Scholar 

  5. Agnetis, A., Coppi, A., Corsini, M., Dellino, G., Meloni, C., & Pranzo, M. (2014). A decomposition approach for the combined master surgical schedule and surgical case assignment problems. Health Care Management Science, 17, 49–59.

    Article  Google Scholar 

  6. AIHW. (2013). Australian hospital statistics: National emergency access and elective surgery targets 2012. Australian Institute of Health and Welfare: Tech. Rep.

    Google Scholar 

  7. Al-Amin, M., & Housman, M. (2012). Ambulatory surgery center and general hospital competition: Entry decisions and strategic choices. Health Care Management Review, 37, 223–234.

    Article  Google Scholar 

  8. Antonelli, D., & Taurino, T. (2010). Application of a patient flow model to a surgery department. In 2010 IEEE Workshop on Health Care Management (WHCM).

  9. Argo, J. L., Vick, C. C., Graham, L. A., Itani, K. M. F., Bishop, M. J., & Hawn, M. T. (2009). Elective surgical case cancellation in the veterans health administration system: Identifying areas for improvement. American Journal of Surgery, 198, 600–606.

    Article  Google Scholar 

  10. Arnaout, J. P. M., & Kulbashian, S. (2008). Maximizing the utilization of operating rooms with stochastic times using simulation. In Proceedings of the 2008 Winter Simulation Conference (pp. 1617–1623).

  11. Augusto, V., Xie, X., & Perdomo, V. (2008). Operating theatre scheduling using lagrangian relaxation. European Journal of Industrial Engineering, 2, 172–189.

    Article  Google Scholar 

  12. Augusto, V., Xie, X., & Perdomo, V. (2010). Operating theatre scheduling with patient recovery in both operating rooms and recovery beds. Computers & Industrial Engineering, 58, 231–238.

    Article  Google Scholar 

  13. Azari-Rad, S., Yontef, A. L., Aleman, D. M., & Urbach, D. R. (2013). Reducing elective general surgery cancellations at a Canadian hospital. Canadian Journal of Surgery, 56, 113–118.

    Article  Google Scholar 

  14. Ballard, S. M., Kuhl, M. E. (2006). The use of simulation to determine maximum capacity in the surgical suite operating room. In Proceedings of the 2006 Winter Simulation Conference (pp. 433–438).

  15. Banditori, C., Cappanera, P., & Visintin, F. (2013). A combined optimization-simulation approach to the master surgical scheduling problem. IMA Journal of Management Mathematics, 24, 155–187.

    Article  Google Scholar 

  16. Banditori, C., Cappanera, P., & Visintin, F. (2014). Investigating the relationship between resources balancing and robustness in master surgical scheduling. Proceedings of the International Conference on Health Care Systems Engineering, 61, 149–162.

    Article  Google Scholar 

  17. Barkaoui, K., Dechambre, P., & Hachicha, R. (2002). Verification and optimisation of an operating room workflow. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences (pp. 2581–2590).

  18. Barua, B., & Esmail, N. (2013). Waiting your turn: Wait times for health care in Canada. Fraser Institute: Tech. Rep.

    Google Scholar 

  19. Basson, M. D., & Butler, T. (2006). Evaluation of operating room suite efficiency in the veterans health administration system by using data-envelopment analysis. American Journal of Surgery, 192, 649–656.

    Article  Google Scholar 

  20. Batun, S., Denton, B. T., Huschka, T. R., & Schaefer, A. J. (2011). Operating room pooling and parallel surgery processing under uncertainty. INFORMS Journal on Computing, 23, 220–237.

    Article  Google Scholar 

  21. Baumgart, A., Zoeller, A., Denz, C., Bender, H. J., Heinzl, A., & Badreddin, E. (2007). Using computer simulation in operating room management: Impacts on process engineering and performance. In Proceedings of the 40th Annual Hawaii International Conference on System Sciences (p. 10).

  22. Beliën, J., & Demeulemeester, E. (2007). Building cyclic master surgery schedules with leveled resulting bed occupancy. European Journal of Operational Research, 176, 1185–1204.

    Article  Google Scholar 

  23. Beliën, J., & Demeulemeester, E. (2008). A branch-and-price approach for integrating nurse and surgery scheduling. European Journal of Operational Research, 189, 652–668.

    Article  Google Scholar 

  24. Beliën, J., Demeulemeester, E., & Cardoen, B. (2006). Visualizing the demand for various resources as a function of the master surgery schedule: A case study. Journal of Medical Systems, 30, 343–50.

    Article  Google Scholar 

  25. Beliën, J., Demeulemeester, E., & Cardoen, B. (2009). A decision support system for cyclic master surgery scheduling with multiple objectives. Journal of Scheduling, 12, 147–161.

    Article  Google Scholar 

  26. Berg, B., Denton, B. T., Erdogan, S. A., Rohleder, T., & Huschka, T. R. (2014). Optimal booking and scheduling in outpatient procedure centers. Computers & Operations Research, 50, 24–37.

    Article  Google Scholar 

  27. Blake, J. T. (2011). Capacity planning in operating rooms (pp. 34.1–34.12). Boca Raton: CRC Press.

  28. Blake, J. T., & Carter, M. W. (1997). Surgical process scheduling: A structured review. Journal of Society for Health Systems, 5, 17–30.

    Google Scholar 

  29. Blake, J. T., & Carter, M. W. (2002). A goal programming approach to strategic resource allocation in acute care hospitals. European Journal of Operational Research, 140, 541–561.

    Article  Google Scholar 

  30. Blake, J. T., & Donald, J. (2002). Mount Sinai hospital uses integer programming to allocate operating room time. Interfaces, 32, 63–73.

    Article  Google Scholar 

  31. Blake, J. T., Dexter, F., & Donald, J. (2002). Operating room managers’ use of integer programming for assigning block time to surgical groups: A case study. Anesthesia and Analgesia, 94, 143–148.

    Google Scholar 

  32. Blazewicz, J., Lenstra, J. K., & Rinnooy Kan, A. H. G. (1983). Scheduling subject to resource constraints: Classification and complexity. Discrete Applied Mathematics, 5, 11–24.

    Article  Google Scholar 

  33. Boldy, D. (1976). Review of application of mathematical-programming to tactical and strategic health and social-services problems. Operational Research Quarterly, 27, 439–448.

    Article  Google Scholar 

  34. Bowers, J. (2013). Balancing operating theatre and bed capacity in a cardiothoracic centre. Health Care Management Science, 16, 236–244.

    Article  Google Scholar 

  35. Bowers, J., & Mould, G. (2004). Managing uncertainty in orthopaedic trauma theatres. European Journal of Operational Research, 154, 599–608.

    Article  Google Scholar 

  36. Bowers, J., & Mould, G. (2005). Ambulatory care and orthopaedic capacity planning. Health Care Management Science, 8, 41–47.

    Article  Google Scholar 

  37. Brailsford, S. C., & Vissers, J. (2011). OR in healthcare: A European perspective. European Journal of Operational Research, 212, 223–234.

    Article  Google Scholar 

  38. Brailsford, S. C., Bolt, T. B., Bucci, G., Chaussalet, T. M., Connell, N. A., Harper, P. R., et al. (2013). Overcoming the barriers: A qualitative study of simulation adoption in the NHS. Journal of the Operational Research Society, 64, 157–168.

    Article  Google Scholar 

  39. Bruni, M. E., Beraldi, P., & Conforti, D. (2014). A stochastic programming approach for operating theatre scheduling under uncertainty. IMA Journal of Management Mathematics, 26, 99–119.

    Article  Google Scholar 

  40. Calichman, M. V. (2005). Creating an optimal operating room schedule. AORN Journal, 81, 580–588.

    Article  Google Scholar 

  41. Cappanera, P., Visintin, F., & Banditori, C. (2014). Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach. International Journal of Production Economics, 158, 179–196.

    Article  Google Scholar 

  42. Cardoen, B., & Demeulemeester, E. (2008). Capacity of clinical pathways: A strategic multi-level evaluation tool. Journal of Medical Systems, 32, 443–452.

    Article  Google Scholar 

  43. Cardoen, B., & Demeulemeester, E. (2010). Operating room planning and scheduling: A classification scheme. International Journal of Health Management and Information, 1, 71–83.

    Google Scholar 

  44. Cardoen, B., & Demeulemeester, E. (2011). A decision support system for surgery sequencing at UZ leuven’s day-care department. International Journal of Information Technology & Decision Making, 10, 435–450.

    Article  Google Scholar 

  45. Cardoen, B., Demeulemeester, E., & Beliën, J. (2009a). Optimizing a multiple objective surgical case sequencing problem. International Journal of Production Economics, 119, 354–366.

    Article  Google Scholar 

  46. Cardoen, B., Demeulemeester, E., & Beliën, J. (2009b). Sequencing surgical cases in a day-care environment: An exact branch-and-price approach. Computers & Operations Research, 36, 2660–2669.

    Article  Google Scholar 

  47. Cardoen, B., Demeulemeester, E., & Beliën, J. (2010a). Operating room planning and scheduling: A literature review. European Journal of Operational Research, 201, 921–932.

    Article  Google Scholar 

  48. Cardoen, B., Demeulemeester, E., & Van der Hoeven, J. (2010b). On the use of planning models in the operating theatre: Results of a survey in Flanders. International Journal of Health Planning and Management, 25, 400–414.

    Article  Google Scholar 

  49. Carter, M. W., & Ketabi, S. (2013). Bed balancing in surgical wards via block scheduling. Journal of Minimally Invasive Surgical Sciences, 2, 129–137.

    Google Scholar 

  50. Cayirli, T., & Veral, E. (2003). Outpatient scheduling in health care: A review of literature. Production and Operations Management, 12, 519–549.

    Article  Google Scholar 

  51. Ceschia, S., & Schaerf, A. (2014). Dynamic patient admission scheduling with operating room constraints, flexible horizons, and patient delays. Journal of Scheduling, 1–13.

  52. Chaabane, S., Meskens, N., Guinet, A., & Laurent, M. (2006). Comparison of two methods of operating theatre planning: Application in Belgian hospital. In 2006 International Conference on Service Systems and Service Management (pp. 386–392).

  53. Chang, J. H., Chen, K. W., Chen, K. B., Poon, K. S., & Liu, S. K. (2014). Case review analysis of operating room decisions to cancel surgery. BMC Surgery, 14, 47.

    Article  Google Scholar 

  54. Choi, S., & Wilhelm, W. E. (2014a). An approach to optimize block surgical schedules. European Journal of Operational Research, 235, 138–148.

    Article  Google Scholar 

  55. Choi, S., & Wilhelm, W. E. (2014b). On capacity allocation for operating rooms. Computers & Operations Research, 44, 174–184.

    Article  Google Scholar 

  56. Conforti, D., Guerriero, F., & Guido, R. (2010). A multi-objective block scheduling model for the management of surgical operating rooms: New solution approaches via genetic algorithms. In 2010 IEEE Workshop on Health Care Management (WHCM) (p. 5).

  57. Creemers, S., Beliën, J., & Lambrecht, M. (2012). The optimal allocation of server time slots over different classes of patients. European Journal of Operational Research, 219, 508–521.

    Article  Google Scholar 

  58. Day, R., Garfinkel, R., & Thompson, S. (2012). Integrated block sharing: A win-win strategy for hospitals and surgeons. M&Som-Manufacturing & Service Operations Management, 14, 567–583.

    Article  Google Scholar 

  59. Dekhici, L., & Belkadi, K. (2010). Operating theatre scheduling under constraints. Journal of Applied Sciences, 14, 1380–1388.

    Google Scholar 

  60. Dellaert, N., & Jeunet, J. (2008). Hospital admission planning to optimize major resources utilization under uncertainty. In 3rd World Conference on Production and Operations Management (p. 16).

  61. Demeulemeester, E., Beliën, J., Cardoen, B., & Samudra, M. (2013). Operating room planning and scheduling. New York: Springer.

    Book  Google Scholar 

  62. Denton, B. T., & Gupta, D. (2003). A sequential bounding approach for optimal appointment scheduling. IIE Transactions, 35, 1003–1016.

    Article  Google Scholar 

  63. Denton, B. T., Rahman, A. S., Nelson, H., & Bailey, A. C. (2006). Simulation of a multiple operating room surgical suite. In Proceedings of the 2006 Winter Simulation Conference (pp. 414–424).

  64. Denton, B. T., Viapiano, J., & Vogl, A. (2007). Optimization of surgery sequencing and scheduling decisions under uncertainty. Health Care Management Science, 10, 13–24.

    Article  Google Scholar 

  65. Denton, B. T., Miller, A. J., Balasubramanian, H. J., & Huschka, T. R. (2010). Optimal allocation of surgery blocks to operating rooms under uncertainty. Operations Research, 58, 802–816.

    Article  Google Scholar 

  66. Dexter, F. (2000). A strategy to decide whether to move the last case of the day in an operating room to another empty operating room to decrease overtime labor costs. Anesthesia and Analgesia, 91, 925–928.

    Article  Google Scholar 

  67. Dexter, F., & Epstein, R. H. (2009). Typical savings from each minute reduction in tardy first case of the day starts. Anesthesia and Analgesia, 108, 1262–1267.

    Article  Google Scholar 

  68. Dexter, F., & Traub, R. D. (2002). How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time. Anesthesia and Analgesia, 94, 933–942.

    Article  Google Scholar 

  69. Dexter, F., Macario, A., & O’Neill, L. (2000). Scheduling surgical cases into overflow block time: Computer simulation of the effects of scheduling strategies on operating room labor costs. Anesthesia and Analgesia, 90, 980–988.

    Article  Google Scholar 

  70. Dexter, F., Macario, A., & Lubarsky, D. A. (2001). The impact on revenue of increasing patient volume at surgical suites with relatively high operating room utilization. Anesthesia and Analgesia, 92, 1215–1221.

    Article  Google Scholar 

  71. Dexter, F., Blake, J. T., Penning, D. H., Sloan, B., Chung, P., & Lubarsky, D. A. (2002a). Use of linear programming to estimate impact of changes in a hospital’s operating room time allocation on perioperative variable costs. Anesthesiology, 96, 718–724.

    Article  Google Scholar 

  72. Dexter, F., Lubarsky, D. A., & Blake, J. T. (2002b). Sampling error can significantly affect measured hospital financial performance of surgeons and resulting operating room time allocations. Anesthesia and Analgesia, 95, 184–188.

    Article  Google Scholar 

  73. Dexter, F., Traub, R. D., & Macario, A. (2003). How to release allocated operating room time to increase efficiency: Predicting which surgical service will have the most underutilized operating room time. Anesthesia and Analgesia, 96, 507–512.

    Google Scholar 

  74. Dexter, F., Epstein, R. H., Traub, R. D., & Xiao, Y. (2004). Making management decisions on the day of surgery based on operating room efficiency and patient waiting times. Anesthesiology, 101, 1444–1453.

    Article  Google Scholar 

  75. Dexter, F., Ledolter, J., & Wachtel, R. E. (2005). Tactical decision making for selective expansion of operating room resources incorporating financial criteria and uncertainty in subspecialties’ future workloads. Anesthesia and Analgesia, 100, 1425–1432.

    Article  Google Scholar 

  76. Dexter, F., Macario, A., & Ledolter, J. (2007). Identification of systematic underestimation (bias) of case durations during case scheduling would not markedly reduce overutilized operating room time. Journal of Clinical Anesthesia, 19, 198–203.

    Article  Google Scholar 

  77. Dexter, F., Birchansky, L., Bernstein, J. M., & Wachtel, R. E. (2009). Case scheduling preferences of one surgeon’s cataract surgery patients. Anesthesia and Analgesia, 108, 579–582.

    Article  Google Scholar 

  78. Dexter, F., Wachtel, R. E., Epstein, R. H., Ledolter, J., & Todd, M. M. (2010). Analysis of operating room allocations to optimize scheduling of specialty rotations for anesthesia trainees. Anesthesia and Analgesia, 111, 520–524.

    Article  Google Scholar 

  79. Di Martinelly, C., Baptiste, P., & Maknoon, M. Y. (2014). An assessment of the integration of nurse timetable changes with operating room planning and scheduling. International Journal of Production Research, 52, 7239–7250.

    Article  Google Scholar 

  80. Does, R., Vermaat, T. M. B., Verver, J. P. S., Bisgaard, S., & Van den Heuvel, J. (2009). Reducing start time delays in operating rooms. Journal of Quality Technology, 41, 95–109.

    Google Scholar 

  81. Epstein, R. H., & Dexter, F. (2015). Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery. Anesthesia and Analgesia, 121, 206–18.

    Article  Google Scholar 

  82. Erdem, E., Qu, X., & Shi, J. (2012). Rescheduling of elective patients upon the arrival of emergency patients. Decision Support Systems, 54, 551–563.

    Article  Google Scholar 

  83. Erdogan, S. A., & Denton, B. T. (2010). Surgery planning and scheduling. New York: Wiley.

    Google Scholar 

  84. van Essen, J. T., Hans, E. W., Hurink, J. L., & Oversberg, A. (2012a). Minimizing the waiting time for emergency surgery. Operations Research for Health Care, 1, 34–44.

    Article  Google Scholar 

  85. van Essen, J. T., Hurink, J. L., Hartholt, W., & van den Akker, B. J. (2012b). Decision support system for the operating room rescheduling problem. Health Care Management Science, 15, 355–372.

    Article  Google Scholar 

  86. van Essen, J. T., Bosch, J. M., Hans, E. W., Van Houdenhoven, M., & Hurink, J. L. (2014). Reducing the number of required beds by rearranging the OR-schedule. OR Spectrum, 36, 585–605.

    Google Scholar 

  87. Everett, J. E. (2002). A decision support simulation model for the management of an elective surgery waiting system. Health Care Management Science, 5, 89–95.

    Article  Google Scholar 

  88. Ewen, H., & Mönch, L. (2014). A simulation-based framework to schedule surgeries in an eye hospital. IIE Transactions on Healthcare Systems Engineering, 4, 191–208.

    Article  Google Scholar 

  89. Ewing, J. (2014). Revenue growth and cash flow margins hit all-time lows in 2013 US not-for-profit hospital medians. Tech: Rep., Moody’s.

    Google Scholar 

  90. Fei, H., Meskens, N., & Chu, C. (2007). An operating theatre planning and scheduling problem in the case of a “block scheduling” strategy. In 2006 International Conference on Service Systems and Service Management.

  91. Fei, H., Chu, C., Meskens, N., & Artiba, A. (2008). Solving surgical cases assignment problem by a branch-and-price approach. International Journal of Production Economics, 112, 96–108.

    Article  Google Scholar 

  92. Fei, H., Chu, C., & Meskens, N. (2009a). Solving a tactical operating room planning problem by a column-generation-based heuristic procedure with four criteria. Annals of Operations Research, 166, 91–108.

    Article  Google Scholar 

  93. Fei, H., Meskens, N., Combes, C., & Chu, C. (2009b). The endoscopy scheduling problem: A case study with two specialised operating rooms. International Journal of Production Economics, 120, 452–462.

    Article  Google Scholar 

  94. Fei, H., Meskens, N., & Chu, C. (2010). A planning and scheduling problem for an operating theatre using an open scheduling strategy. Computers & Industrial Engineering, 58, 221–230.

    Article  Google Scholar 

  95. Ferrand, Y., Magazine, M., & Rao, U. (2010). Comparing two operating-room-allocation policies for elective and emergency surgeries. In Proceedings of the 2010 Winter Simulation Conference (pp. 2364–2374).

  96. Ferrand, Y., Magazine, M., & Rao, U. (2014a). Partially flexible operating rooms for elective and emergency surgeries. Decision Sciences, 45, 819–847.

    Article  Google Scholar 

  97. Ferrand, Y. B., Magazine, M. J., & Rao, U. S. (2014b). Managing operating room efficiency and responsiveness for emergency and elective surgeries: A literature survey. IIE Transactions on Healthcare Systems Engineering, 4, 49–64.

    Article  Google Scholar 

  98. Ferrin, D. M., Miller, M. J., Wininger, S., & Neuendorf, M. S. (2004). Analyzing incentives and scheduling in a major metropolitan hospital operating room through simulation. In Proceedings of the 2004 Winter Simulation Conference (pp. 1975–1980).

  99. Fügener, A., Hans, E. W., Kolisch, R., Kortbeek, N., & Vanberkel, P. T. (2014). Master surgery scheduling with consideration of multiple downstream units. European Journal of Operational Research, 239, 227–236.

    Article  Google Scholar 

  100. Fischetti, M., & Monaci, M. (2009). Light robustness (Vol. 5866, pp. 61–84). Berlin: Springer.

  101. Gartner, D., & Kolisch, R. (2014). Scheduling the hospital-wide flow of elective patients. European Journal of Operational Research, 233, 689–699.

    Article  Google Scholar 

  102. Ghazalbash, S., Sepehri, M. M., Shadpour, P., & Atighehchian, A. (2012). Operating room scheduling in teaching hospitals. Advances in Operations Research, 2012, 16.

    Article  Google Scholar 

  103. Gocgun, Y., & Ghate, A. (2012). Lagrangian relaxation and constraint generation for allocation and advanced scheduling. Computers & Operations Research, 39, 2323–2336.

    Article  Google Scholar 

  104. Gomes, C., Almada-Lobo, B., Borges, J., & Soares, C. (2012). Integrating data mining and optimization techniques on surgery scheduling (Vol. 7713, pp. 589–602). Berlin: Springer.

  105. Gonzalez, P., & Herrero, C. (2004). Optimal sharing of surgical costs in the presence of queues. Mathematical Methods of Operations Research, 59, 435–446.

    Article  Google Scholar 

  106. Guda, H., Dawande, M., Janakiraman, G., & Jung, K. S. (2016). Optimal policy for a stochastic scheduling problem with applications to surgical scheduling. Production and Operations Management.

  107. Guerriero, F., & Guido, R. (2011). Operational research in the management of the operating theatre: A survey. Health Care Management Science, 14, 89–114.

    Article  Google Scholar 

  108. Guinet, A., & Chaabane, S. (2003). Operating theatre planning. International Journal of Production Economics, 85, 69–81.

    Article  Google Scholar 

  109. Gul, S., Denton, B. T., Fowler, J. W., & Huschka, T. R. (2011). Bi-criteria scheduling of surgical services for an outpatient procedure center. Production and Operations Management, 20, 406–417.

    Article  Google Scholar 

  110. Gul, S., Denton, B., & Fowler, J. W. (2012). A multi-stage stochastic integer programming model for surgery planning. Michigan Engineering.

  111. Gupta, D. (2007). Surgical suites’ operations management. Production and Operations Management, 16, 689–700.

    Article  Google Scholar 

  112. Gupta, D., & Denton, B. T. (2008). Appointment scheduling in health care: Challenges and opportunities. IIE Transactions, 40, 800–819.

    Article  Google Scholar 

  113. Gupta, D., Natarajan, M. K., Gafni, A., Wang, L., Shilton, D., Holder, D., et al. (2007). Capacity planning for cardiac catheterization: A case study. Health Policy, 82, 1–11.

    Article  Google Scholar 

  114. Hans, E. W., & Vanberkel, P. T. (2012). Operating theatre planning and scheduling (Vol. 168, pp. 105–130). New York: Springer.

  115. Hans, E. W., Nieberg, T., & van Oostrum, J. M. (2007). Optimization in surgery planning. Medium Econometrische Toepassingen, 15, 20–28.

    Google Scholar 

  116. Hans, E. W., Wullink, G., Van Houdenhoven, M., & Kazemier, G. (2008). Robust surgery loading. European Journal of Operational Research, 185, 1038–1050.

    Article  Google Scholar 

  117. Hanset, A., Meskens, N., & Duvivier, D. (2010). Using constraint programming to schedule an operating theatre. In 2010 IEEE Workshop on Health Care Management (WHCM).

  118. Harper, P. R. (2002). A framework for operational modelling of hospital resources. Health Care Management Science, 5, 165–173.

    Article  Google Scholar 

  119. Hashemi, D., Seyed, H., Rousseau, L. M., & Pesant, G. (2014). A constraint programming-based column generation approach for operating room planning and scheduling (Vol. 8451, pp. 455–463). New York: Springer.

  120. Heng, M., & Wright, J. G. (2013). Dedicated operating room for emergency surgery improves access and efficiency. Canadian Journal of Surgery, 56, 167–174.

    Article  Google Scholar 

  121. Herring, W. L., & Herrmann, J. W. (2012). The single-day surgery scheduling problem: Sequential decision-making and threshold-based heuristics. OR Spectrum, 34, 429–459.

    Article  Google Scholar 

  122. HFMA. (2003). Achieving operating room efficiency through process integration. Healthcare Financial Management Association: Tech. Rep.

    Google Scholar 

  123. HFMA. (2011). Value in health care: Current state and future directions. Healthcare Financial Management Association: Tech. Rep.

    Google Scholar 

  124. Holte, M., & Mannino, C. (2013). The implementor/adversary algorithm for the cyclic and robust scheduling problem in health-care. European Journal of Operational Research, 226, 551–559.

    Article  Google Scholar 

  125. Hongying, F., Meskens, N., & El-Darzi, E. (2010). Evaluating alternative surgery plans with discrete-event simulation model. In 2010 IEEE Workshop on Health Care Management (WHCM) (pp. 1–6).

  126. Hosseini, N., & Taaffe, K. M. (2014). Allocating operating room block time using historical caseload variability. Health Care Management Science, 18, 419–430.

    Article  Google Scholar 

  127. Hsu, V. N., de Matta, R., & Lee, C. Y. (2003). Scheduling patients in an ambulatory surgical center. Naval Research Logistics, 50, 218–238.

    Article  Google Scholar 

  128. Huh, W. T., Liu, N., & Van-Anh, T. (2013). Multiresource allocation scheduling in dynamic environments. M&Som-Manufacturing & Service Operations Management, 15, 280–291.

    Article  Google Scholar 

  129. Hulshof, P., Boucherie, R. J., van Essen, J. T., Hans, E. W., Hurink, J. L., Kortbeek, N., et al. (2011). ORchestra: An online reference database of OR/MS literature in health care. Health Care Management Science, 14, 383–384.

    Article  Google Scholar 

  130. Hulshof, P., Kortbeek, N., Boucherie, R. J., Hans, E. W., & Bakker, P. (2012). Taxonomic classification of planning decisions in health care: A structured review of the state of the art in OR/MS. Health Systems, 1, 129–175.

    Article  Google Scholar 

  131. Hulshof, P., Boucherie, R. J., Hans, E. W., & Hurink, J. L. (2013). Tactical resource allocation and elective patient admission planning in care processes. Health Care Management Science, 16, 152–166.

    Article  Google Scholar 

  132. Huschka, T. R., Denton, B. T., Gul, S., & Fowler, J. W. (2007). Bi-criteria evaluation of an outpatient procedure center via simulation. In Proceedings of the 2007 Winter Simulation Conference (pp. 1489–1497).

  133. Iser, J. H., Denton, B. T., & King, R. E. (2008). Heuristics for balancing operating room and post-anesthesia resources under uncertainty. In Proceedings of the 2008 Winter Simulation Conference (pp. 1601–1608).

  134. Jeang, A., & Chiang, A. J. (2012). Economic and quality scheduling for effective utilization of operating rooms. Journal of Medical Systems, 36, 1205–1222.

    Article  Google Scholar 

  135. Jebali, A., Hadj-Alouane, A., & Ladet, P. (2003). Performance comparison of two strategies for operating room scheduling. In International Symposium on Computational Intelligence and Intelligent Informatics.

  136. Jebali, A., Hadj-Alouane, A. B., & Ladet, P. (2006). Operating rooms scheduling. International Journal of Production Economics, 99, 52–62.

    Article  Google Scholar 

  137. Jittamai, P., & Kangwansura, T. (2011). A hospital admission planning model for emergency and elective patients under stochastic resource requirements and no-shows. In 2011 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 166–170).

  138. Joustra, P. E., de Wit, J., Van Dijk, N. M., & Bakker, P. J. M. (2011). How to juggle priorities? An interactive tool to provide quantitative support for strategic patient-mix decisions: An ophthalmology case. Health Care Management Science, 14, 348–360.

    Article  Google Scholar 

  139. Jun, J. B., Jacobson, S. H., & Swisher, J. R. (1999). Application of discrete-event simulation in health care clinics: A survey. The Journal of the Operational Research Society, 50, 109–123.

    Article  Google Scholar 

  140. Keren, B., & Pliskin, J. (2011). Optimal timing of joint replacement using mathematical programming and stochastic programming models. Health Care Management Science, 14, 361–369.

    Article  Google Scholar 

  141. Kharraja, S., Albert, P., & Chaabane, S. (2006). Block scheduling: Toward a master surgical schedule. In Proceedings of 2006 International Conference on Service Systems and Service Management (pp. 429–435).

  142. Kim, S. C., & Horowitz, I. (2002). Scheduling hospital services: The efficacy of elective-surgery quotas. Omega-International Journal of Management Science, 30, 335–346.

    Article  Google Scholar 

  143. Kodali, B. S., Kim, D., Bleday, R., Flanagan, H., & Urman, R. D. (2014). Successful strategies for the reduction of operating room turnover times in a tertiary care academic medical center. Journal of Surgical Research, 187, 403–411.

    Article  Google Scholar 

  144. Koenig, L., & Gu, Q. (2013). Growth of ambulatory surgical centers, surgery volume, and savings to Medicare. American Journal of Gastroenterology, 108, 10–15.

    Article  Google Scholar 

  145. Kolker, A. (2009). Process modeling of ICU patient flow: Effect of daily load leveling of elective surgeries on ICU diversion. Journal of Medical Systems, 33, 27–40.

    Article  Google Scholar 

  146. van der Kooij, R., Mes, M., & Hans, E. W. (2014). Simulation framework to analyze operating room release mechanisms. In Proceedings of the 2014 Winter Simulation Conference (pp. 1144–1155).

  147. Krempels, K. H., & Panchenko, A. (2006). An approach for automated surgery scheduling. In Sixth International Conference on the Practice and Theory of Automated Timetabling.

  148. Kuo, P. C., Schroeder, R. A., Mahaffey, S., & Bollinger, R. R. (2003). Optimization of operating room allocation using linear programming techniques. Journal of the American College of Surgeons, 197, 889–895.

    Article  Google Scholar 

  149. Lagergren, M. (1998). What is the role and contribution of models to management and research in the health services? A view from Europe. European Journal of Operational Research, 105, 257–266.

    Article  Google Scholar 

  150. Lamiri, M., Dreo, J., & Xiaolan, X. (2007). Operating room planning with random surgery times. In Proceedings of the 3th IEEE Conference on Automation Science and Engineering (pp. 521–526).

  151. Lamiri, M., Augusto, V., & Xie, X. (2008a). Patients scheduling in a hospital operating theatre. In 2008 IEEE International Conference on Automation Science and Engineering (pp. 627–632).

  152. Lamiri, M., Xie, X., Dolgui, A., & Grimaud, F. (2008b). A stochastic model for operating room planning with elective and emergency demand for surgery. European Journal of Operational Research, 185, 1026–1037.

    Article  Google Scholar 

  153. Lamiri, M., Xie, X., & Zhang, S. G. (2008c). Column generation approach to operating theater planning with elective and emergency patients. IIE Transactions, 40, 838–852.

    Article  Google Scholar 

  154. Lamiri, M., Grimaud, F., & Xie, X. (2009). Optimization methods for a stochastic surgery planning problem. International Journal of Production Economics, 120, 400–410.

    Article  Google Scholar 

  155. van der Lans, M., Hans, E. W., Hurink, J. L., Wullink, G., Van Houdenhoven, M., & Kazemier, G. (2006). Anticipating urgent surgery in operating room departments. University of Twente.

  156. Lebowitz, P. (2003). Schedule the short procedure first to improve or efficiency. AORN Journal, 78, 651–654.

    Article  Google Scholar 

  157. Lee, S., & Yih, Y. (2014). Reducing patient-flow delays in surgical suites through determining start-times of surgical cases. European Journal of Operational Research, 238, 620–629.

    Article  Google Scholar 

  158. Lehtonen, J. M., Torkki, P., Peltokorpi, A., & Moilanen, T. (2013). Increasing operating room productivity by duration categories and a newsvendor model. International Journal of Health Care Quality Assurance, 26, 80–92.

    Article  Google Scholar 

  159. Leppäniemi, A., & Jousela, I. (2014). A traffic-light coding system to organize emergency surgery across surgical disciplines. The British Journal of Surgery, 101, 134–140.

    Article  Google Scholar 

  160. Leslie, R. J., Beiko, D., Van Vlymen, J., & Siemens, D. R. (2012). Day of surgery cancellation rates in urology: Identification of modifiable factors. Canadian Urological Association Journal, 1–8.

  161. Lewis, H. F., Sexton, T. R., & Dolan, M. A. (2011). An efficiency-based multicriteria strategic planning model for ambulatory surgery centers. Journal of Medical Systems, 35, 1029–1037.

    Article  Google Scholar 

  162. Litvak, N., van Rijsbergen, M., Boucherie, R. J., & Van Houdenhoven, M. (2008). Managing the overflow of intensive care patients. European Journal of Operational Research, 185, 998–1010.

    Article  Google Scholar 

  163. Liu, Y., Chu, C., & Wang, K. (2011). A new heuristic algorithm for the operating room scheduling problem. Computers & Industrial Engineering, 61, 865–871.

    Article  Google Scholar 

  164. Lovejoy, W. S., & Li, Y. (2002). Hospital operating room capacity expansion. Management Science, 48, 1369–1387.

    Article  Google Scholar 

  165. Luangkesorn, K. L., Bountourelis, T., Schaefer, A., Nabors, S., & Clermont, G. (2012). The case against utilization: Deceptive performance measures in inpatient care capacity models. In Proceedings of the 2012 Winter Simulation Conference (p. 76).

  166. Ma, G., & Demeulemeester, E. (2010). Assessing the performance of hospital capacity planning through simulation analysis. Leuven: KU Leuven.

    Google Scholar 

  167. Ma, G., & Demeulemeester, E. (2013). A multilevel integrative approach to hospital case mix and capacity planning. Computers & Operations Research, 40, 2198–2207.

    Article  Google Scholar 

  168. Ma, G., Beliën, J., Demeulemeester, E., & Wang, L. (2011). Solving the case mix problem optimally by using branch-and-price algorithms. Leuven: KU Leuven.

    Google Scholar 

  169. Magerlein, J. M., & Martin, J. B. (1978). Surgical demand scheduling: A review. Health Services Research, 13, 418–433.

    Google Scholar 

  170. Mancilla, C., & Storer, R. H. (2013). Stochastic sequencing of surgeries for a single surgeon operating in parallel operating rooms. IIE Transactions on Healthcare Systems Engineering, 3, 127–138.

    Article  Google Scholar 

  171. Mannino, C., Nilssen, E. J., & Nordlander, T. E. (2012). A pattern based, robust approach to cyclic master surgery scheduling. Journal of Scheduling, 15, 553–563.

    Article  Google Scholar 

  172. Marcon, E., & Dexter, F. (2006). Impact of surgical sequencing on post anesthesia care unit staffing. Health Care Management Science, 9, 87–98.

    Article  Google Scholar 

  173. Marcon, E., & Dexter, F. (2007). An observational study of surgeons’ sequencing of cases and its impact on postanesthesia care unit and holding area staffing requirements at hospitals. Anesthesia and Analgesia, 105, 119–126.

    Article  Google Scholar 

  174. Marcon, E., Kharraja, S., & Simonnet, G. (2003a). The operating theatre planning by the follow-up of the risk of no realization. International Journal of Production Economics, 85, 83–90.

    Article  Google Scholar 

  175. Marcon, E., Kharraja, S., Smolski, N., Luquet, B., & Viale, J. P. (2003b). Determining the number of beds in the postanesthesia care unit: A computer simulation flow approach. Anesthesia and Analgesia, 96, 1415–1423.

    Article  Google Scholar 

  176. Marjamaa, R. A., Torkki, P. M., Hirvensalo, E. J., & Kirvela, O. A. (2009). What is the best workflow for an operating room? A simulation study of five scenarios. Health Care Management Science, 12, 142–146.

    Article  Google Scholar 

  177. Marques, I., Captivo, M. E., & Vaz Pato, M. (2012). An integer programming approach to elective surgery scheduling. OR Spectrum, 34, 407–427.

    Article  Google Scholar 

  178. Marques, I., Captivo, M. E., & Vaz Pato, M. (2014a). A bicriteria heuristic for an elective surgery scheduling problem. Health Care Management Science, 18, 251–266.

    Article  Google Scholar 

  179. Marques, I., Captivo, M. E., & Vaz Pato, M. (2014b). Scheduling elective surgeries in a Portuguese hospital using a genetic heuristic. Operations Research for Health Care, 3, 59–72.

    Article  Google Scholar 

  180. Masursky, D., Dexter, F., O’Leary, C. E., Applegeet, C., & Nussmeier, N. A. (2008). Long-term forecasting of anesthesia workload in operating rooms from changes in a hospital’s local population can be inaccurate. Anesthesia and Analgesia, 106, 1223–1231.

    Article  Google Scholar 

  181. May, J. H., Spangler, W. E., Strum, D. P., & Vargas, L. G. (2011). The surgical scheduling problem: Current research and future opportunities. Production and Operations Management, 20, 392–405.

    Article  Google Scholar 

  182. Medpac., (2010). Report to congress: Medicare payment policy. Medicare Payment Advisory Commission: Tech. Rep.

  183. Meskens, N., Duvivier, D., & Lianset, A. (2013). Multi-objective operating room scheduling considering desiderata of the surgical team. Decision Support Systems, 55, 650–659.

    Article  Google Scholar 

  184. MHallah, R., & Al-Roomi, A. H., (2014). The planning and scheduling of operating rooms: A simulation approach. Computers & Industrial Engineering, 78, 235–248.

  185. Milliman., (2011). 2011 Milliman Medical Index. Milliman: Tech. Rep.

  186. Min, D., & Yih, Y. (2010a). An elective surgery scheduling problem considering patient priority. Computers & Operations Research, 37, 1091–1099.

    Article  Google Scholar 

  187. Min, D., & Yih, Y. (2010b). Scheduling elective surgery under uncertainty and downstream capacity constraints. European Journal of Operational Research, 206, 642–652.

    Article  Google Scholar 

  188. Min, D., & Yih, Y. (2014). Managing a patient waiting list with time-dependent priority and adverse events. RAIRO-Operations Research, 48, 53–74.

    Article  Google Scholar 

  189. Molina, J. M., & Framinan, J. M. (2009). Testing planning policies for solving the elective case scheduling phase: A real application. In 35th International Conference on Operational Research Applied to Health Services.

  190. Mulholland, M. W., Abrahamse, P., & Bahl, V. (2005). Linear programming to optimize performance in a department of surgery. Journal of the American College of Surgeons, 200, 861–868.

    Article  Google Scholar 

  191. Niu, Q., Peng, Q., ElMekkawy, T., & Tan, Y. Y. (2007). Performance analysis of the operating room using simulation. In CDEN and CCEE Conference.

  192. Niu, Q., Peng, Q., & ElMekkawy, T. Y. (2013). Improvement in the operating room efficiency using tabu search in simulation. Business Process Management Journal, 19, 799–818.

    Article  Google Scholar 

  193. Nouaouri, I., Nicolas, J. C., & Jolly, D. (2009). Scheduling of stabilization surgical cares in case of a disaster. In 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1974–1978).

  194. Noyan Ogulata, S., & Erol, R. (2003). A hierarchical multiple criteria mathematical programming approach for scheduling general surgery operations in large hospitals. Journal of Medical Systems, 27, 259–270.

    Article  Google Scholar 

  195. Olivares, M., Terwiesch, C., & Cassorla, L. (2008). Structural estimation of the newsvendor model: An application to reserving operating room time. Management Science, 54, 41–55.

    Article  Google Scholar 

  196. van Oostrum, J. M., Van Houdenhoven, M., Hurink, J. L., Hans, E. W., Wullink, G., & Kazemier, G. (2008). A master surgical scheduling approach for cyclic scheduling in operating room departments. OR Spectrum, 30, 355–374.

    Article  Google Scholar 

  197. van Oostrum, J. M., Bredenhoff, E., & Hans, E. W. (2010). Suitability and managerial implications of a master surgical scheduling approach. Annals of Operations Research, 178, 91–104.

    Article  Google Scholar 

  198. van Oostrum, J. M., Parlevliet, T., Wagelmans, A. P. M., & Kazemier, G. (2011). A method for clustering surgical cases to allow master surgical scheduling. INFOR: Information Systems and Operational Research, 49, 254–260.

  199. Ozkarahan, I. (2000). Allocation of surgeries to operating rooms by goal programing. Journal of Medical Systems, 24, 339–378.

    Article  Google Scholar 

  200. Pandit, J. J., Abbott, T., Pandit, M., Kapila, A., & Abraham, R. (2012). Is ’starting on time’ useful (or useless) as a surrogate measure for ’surgical theatre efficiency’? Anaesthesia, 67, 823–832.

    Article  Google Scholar 

  201. Paoletti, X., & Marty, J. (2007). Consequences of running more operating theatres than anaesthetists to staff them: A stochastic simulation study. British Journal of Anaesthesia, 98, 462–469.

    Article  Google Scholar 

  202. Pariente, J. M. M., Torres, J. M. F., & Cia, T. G. (2009). Policies and decision models for solving elective case operating room scheduling. In International Conference on Computers and Industrial Engineering (CIE 2009) (pp. 112–117).

  203. Paul, J. A., & MacDonald, L. (2013). Determination of number of dedicated OR’s and supporting pricing mechanisms for emergent surgeries. Journal of the Operational Research Society, 64, 912–924.

    Article  Google Scholar 

  204. Persson, M., & Persson, J. (2006). Optimization modelling of hospital operating room planning: analyszing strategies and problem settings. In Annual Conference of OR Applied to Health Services.

  205. Persson, M., & Persson, J. A. (2009). Health economic modeling to support surgery management at a swedish hospital. Omega-International Journal of Management Science, 37, 853–863.

    Article  Google Scholar 

  206. Persson, M., & Persson, J. A. (2010). Analysing management policies for operating room planning using simulation. Health Care Management Science, 13, 182–191.

    Article  Google Scholar 

  207. Pham, D. N., & Klinkert, A. (2008). Surgical case scheduling as a generalized job shop scheduling problem. European Journal of Operational Research, 185, 1011–1025.

    Article  Google Scholar 

  208. Pierskalla, W. P., & Brailer, D. J. (1994). Applications of operations research in health care delivery. Berlin: Springer.

    Google Scholar 

  209. Pinedo, M. L. (2012). Scheduling: Theory, algorithms, and systems. Berlin: Springer.

    Book  Google Scholar 

  210. Pérez Gladish, B., Arenas Parra, M., Bilbao Terol, A., & Rodriguez Uria, M. V. (2005). Management of surgical waiting lists through a possibilistic linear multiobjective programming problem. Applied Mathematics and Computation, 167, 477–495.

    Article  Google Scholar 

  211. Przasnyski, Z. H. (1986). Operating room scheduling: A literature review. AORN Journal, 44, 67–79.

    Article  Google Scholar 

  212. Pulido, R., Aguirre, A. M., Ortega-Mier, M., Garcia-Sanchez, A., & Mendez, C. A. (2014). Managing daily surgery schedules in a teaching hospital: A mixed-integer optimization approach. BMC Health Services Research, 14, 1.

    Article  Google Scholar 

  213. Rachuba, S., & Werners, B. (2014). A robust approach for scheduling in hospitals using multiple objectives. Journal of the Operational Research Society, 65, 546–556.

    Article  Google Scholar 

  214. Ramis, F. J., Palma, J. L., & Baesler, F. F. (2001). The use of simulation for process improvement at an ambulatory surgery center. In Proceedings of the 2001 Winter Simulation Conference.

  215. Riise, A., & Burke, E. (2011). Local search for the surgery admission planning problem. Journal of Heuristics, 17, 389–414.

    Article  Google Scholar 

  216. Rizk, C., & Arnaout, J. P. (2012). ACO for the surgical cases assignment problem. Journal of Medical Systems, 36, 1891–1899.

    Article  Google Scholar 

  217. Roland, B., Di Martinelly, C., & Riane, F. (2006). Operating theatre optimization: A resource-constrained based solving approach. In International Conference on Service Systems and Service Management (pp. 443–448).

  218. Roland, B., Di Martinelly, C., Riane, F., & Pochet, Y. (2010). Scheduling an operating theatre under human resource constraints. Computers & Industrial Engineering, 58, 212–220.

    Article  Google Scholar 

  219. Ruey-Kei, C., & Yu-Chen, Y. (2010). Fuzzy-based dynamic scheduling system for health examination. In 2010 International Conference on Machine Learning and Cybernetics (pp. 636–641).

  220. Samudra, M., Demeulemeester, E., & Cardoen, B. (2013). A closer view at the patient surgery planning and scheduling problem: A literature review. Review of Business and Economic Literature (ReBEL), 58, 115–140.

    Google Scholar 

  221. Samudra, M., Demeulemeester, E., Cardoen, B., Vansteenkiste, N., & Rademakers, F. E. (2016). Due time driven surgery scheduling. Health Care Management Science, 1–27.

  222. Sandbaek, B. E., Helgheim, B. I., & Larsen, O. I. (2014). Impact of changed management policies on operating room efficiency. BMC Health Services Research, 14, 1.

    Article  Google Scholar 

  223. Santibanez, P., Begen, M. A., & Atkins, D. (2007). Surgical block scheduling in a system of hospitals: An application to resource and wait list management in a british columbia health authority. Health Care Management Science, 10, 269–282.

    Article  Google Scholar 

  224. Saremi, A., Jula, P., ElMekkawy, T., & Wang, G. G. (2013). Appointment scheduling of outpatient surgical services in a multistage operating room department. International Journal of Production Economics, 141, 646–658.

    Article  Google Scholar 

  225. Schmid, V., & Doerner, K. F. (2014). Examination and operating room scheduling including optimization of intrahospital routing. Transportation Science, 48, 59–77.

    Article  Google Scholar 

  226. Schoenmeyr, T., Dunn, P. F., Garnarnik, D., Levi, R., Berger, D. L., Daily, B. J., et al. (2009). A model for understanding the impacts of demand and capacity on waiting time to enter a congested recovery room. Anesthesiology, 110, 1293–1304.

    Article  Google Scholar 

  227. Sciomachen, A., Tanfani, E., & Testi, A. (2005). Simulation models for optimal schedules of operating theatres. International Journal of Simulation, 6, 26–34.

    Google Scholar 

  228. Shylo, O. V., Luangkesorn, L., Prokopyev, O. A., Rajgopal, J., & Schaefer, A. (2011). Managing patient backlog in a surgical suite that uses a block-booking scheduling system. In Proceedings of the 2011 Winter Simulation Conference (pp. 1314–1324).

  229. Shylo, O. V., Prokopyev, O. A., & Schaefer, A. J. (2013). Stochastic operating room scheduling for high-volume specialties under block booking. INFORMS Journal on Computing, 25, 682–692.

    Article  Google Scholar 

  230. Sieber, T. J., & Leibundgut, D. L. (2002). Operating room management and strategies in Switzerland: Results of a survey. European Journal of Anaesthesiology, 19, 415–423.

    Article  Google Scholar 

  231. Slack, N. (1999). The Blackwell encyclopedic dictionary of operations management. Chichester: Wiley.

    Google Scholar 

  232. Smith-Daniels, V. L., Schweikhart, S. B., & Smith-Daniels, D. E. (1988). Capacity management in health care services: Review and future research directions. Decision Sciences, 19, 889–919.

    Article  Google Scholar 

  233. Sobolev, B. G., Sanchez, V., & Vasilakis, C. (2011). Systematic review of the use of computer simulation modeling of patient flow in surgical care. Journal of Medical Systems, 35, 1–16.

    Article  Google Scholar 

  234. Souki, M., & Rebai, A. (2009). Memetic differential evolution algorithm for operating room scheduling. In International Conference on Computers and Industrial Engineering (CIE 2009) (pp. 845–850).

  235. Souki, M., Ben Youssef, S., & Rebai, A. (2009). Memetic algorithm for operating room admissions. In International Conference on Computers and Industrial Engineering (CIE 2009) (pp. 519–524).

  236. Sperandio, F., Gomes, C., Borges, J., Carvalho Brito, A., & Almada-Lobo, B. (2014). An intelligent decision support system for the operating theater: A case study. IEEE Transactions on Automation Science and Engineering, 11, 265–273.

    Article  Google Scholar 

  237. Stanciu, A., Vargas, L. G., & May, J. H. (2010). A revenue management approach for managing operating room capacity. In Proceedings of the 2010 Winter Simulation Conference (pp. 2444–2454).

  238. Stanford, D., Taylor, P., & Ziedins, I. (2014). Waiting time distributions in the accumulating priority queue. Queueing Systems, 77, 297–330.

    Article  Google Scholar 

  239. Steins, K., Persson, F., & Holmer, M. (2010). Increasing utilization in a hospital operating department using simulation modeling. Simulation, 86, 463–480.

    Article  Google Scholar 

  240. Stuart, K., & Kozan, E. (2012). Reactive scheduling model for the operating theatre. Flexible Services and Manufacturing Journal, 24, 400–421.

    Article  Google Scholar 

  241. Tan, Y., El Mekkawy, T., Peng, Q., & Oppenheimer, L. (2007). Mathematical programming for the scheduling of elective patients in the operating room department. In Proceedings of the Canadian Engineering Education Association.

  242. Tancrez, J. S., Roland, B., Cordier, J. P., & Riane, F. (2009). How stochasticity and emergencies disrupt the surgical schedule (pp. 221–239). Berlin: Springer.

    Google Scholar 

  243. Tancrez, J. S., Roland, B., Cordier, J. P., & Riane, F. (2013). Assessing the impact of stochasticity for operating theater sizing. Decision Support Systems, 55, 616–628.

    Article  Google Scholar 

  244. Tanfani, E., & Testi, A. (2010a). Improving surgery department performance via simulation and optimization. In 2010 IEEE Workshop on Health Care Management (WHCM) (p. 6).

  245. Tanfani, E., & Testi, A. (2010b). A pre-assignment heuristic algorithm for the master surgical schedule problem (MSSP). Annals of Operations Research, 178, 105–119.

    Article  Google Scholar 

  246. Testi, A., & Tanfani, E. (2009). Tactical and operational decisions for operating room planning: Efficiency and welfare implications. Health Care Management Science, 12, 363–373.

    Article  Google Scholar 

  247. Testi, A., Tanfani, E., & Torre, G. (2007). A three-phase approach for operating theatre schedules. Health Care Management Science, 10, 163–172.

    Article  Google Scholar 

  248. Testi, A., Tanfani, E., Valente, R., Ansaldo, G., & Torre, G. (2008). Prioritizing surgical waiting lists. Journal of Evaluation in Clinical Practice, 14, 59–64.

    Article  Google Scholar 

  249. Tsoy, G., Arnaout, J. P., Smith, T., & Rabadi, G. (2004). A genetic algorithm approach for surgery operating rooms scheduling problem. In 25th National Conference of the American Society for Engineering Management (pp. 299–304).

  250. Tyler, D. C., Pasquariello, C. A., & Chen, C. H. (2003). Determining optimum operating room utilization. Anesthesia and Analgesia, 96, 1114–1121.

    Article  Google Scholar 

  251. Utley, M., & Worthington, D. (2012). Capacity planning (Vol. 168, pp. 11–30). New York: Springer.

  252. Van Houdenhoven, M., Hans, E. W., Klein, J., Wullink, G., & Kazemier, G. (2007). A norm utilisation for scarce hospital resources: Evidence from operating rooms in a Dutch university hospital. Journal of Medical Systems, 31, 231–236.

    Article  Google Scholar 

  253. Van Houdenhoven, M., van Oostrum, J. M., Wullink, G., Hans, E. W., Hurink, J. L., Bakker, J., et al. (2008). Fewer intensive care unit refusals and a higher capacity utilization by using a cyclic surgical case schedule. Journal of Critical Care, 23, 222–226.

    Article  Google Scholar 

  254. Van Huele, C., & Vanhoucke, M. (2014). Analysis of the integration of the physician rostering problem and the surgery scheduling problem. Journal of Medical Systems, 38, 1–16.

    Article  Google Scholar 

  255. Vanberkel, P. T., & Blake, J. T. (2007). A comprehensive simulation for wait time reduction and capacity planning applied in general surgery. Health Care Management Science, 10, 373–385.

    Article  Google Scholar 

  256. Vanberkel, P. T., Boucherie, R. J., Hans, E. W., Hurink, J. L., & Litvak, N. (2009). A survey of health care models that encompass multiple departments. Enschede: University of Twente.

    Google Scholar 

  257. Vanberkel, P. T., Boucherie, R. J., Hans, E. W., Hurink, J. L., van Lent, W. A. M., & van Harten, W. H. (2011a). Accounting for inpatient wards when developing master surgical schedules. Anesthesia and Analgesia, 112, 1472–1479.

    Article  Google Scholar 

  258. Vanberkel, P. T., Boucherie, R. J., Hans, E. W., Hurink, J. L., van Lent, W. A. M., & van Harten, W. H. (2011b). An exact approach for relating recovering surgical patient workload to the master surgical schedule. Journal of the Operational Research Society, 62, 1851–1860.

    Article  Google Scholar 

  259. Vanberkel, P. T., Boucherie, R. J., Hans, E. W., & Hurink, J. L. (2014). Optimizing the strategic patient mix combining queueing theory and dynamic programming. Computers & Operations Research, 43, 271–279.

    Article  Google Scholar 

  260. Vansteenkiste, N., Lamote, C., Vandersmissen, J., Luysmans, P., Monnens, P., De Voldere, G., et al. (2012). Reallocation of operating room capacity using the due-time model. Medical Care, 50, 779–784.

    Article  Google Scholar 

  261. Velasquez, R., Melo, T., & Kufer, K. H. (2008). Tactical operating theatre scheduling: Efficient appointment assignment. Operations Research Proceedings, 2007, 303–308.

    Google Scholar 

  262. Vijayakumar, B., Parikh, P. J., Scott, R., Barnes, A., & Gallimore, J. (2013). A dual bin-packing approach to scheduling surgical cases at a publicly-funded hospital. European Journal of Operational Research, 224, 583–591.

    Article  Google Scholar 

  263. Vissers, J., Bertrand, J., & De Vries, G. (2001). A framework for production control in health care organizations. Production Planning & Control, 12, 591–604.

    Article  Google Scholar 

  264. Vissers, J., Adan, I., & Bekkers, J. (2005). Patient mix optimization in tactical cardiothoracic surgery planning: A case study. IMA Journal of Management Mathematics, 16, 281–304.

    Article  Google Scholar 

  265. Wachtel, R. E., & Dexter, F. (2007). A simple method for deciding when patients should be ready on the day of surgery without procedure-specific data. Anesthesia and Analgesia, 105, 127–140.

    Article  Google Scholar 

  266. Wachtel, R. E., & Dexter, F. (2008). Tactical increases in operating room block time for capacity planning should not be based on utilization. Anesthesia and Analgesia, 106, 215–226.

    Article  Google Scholar 

  267. Wachtel, R. E., & Dexter, F. (2009a). Influence of the operating room schedule on tardiness from scheduled start times. Anesthesia and Analgesia, 108, 1889–1901.

    Article  Google Scholar 

  268. Wachtel, R. E., & Dexter, F. (2009b). Reducing tardiness from scheduled start times by making adjustments to the operating room schedule. Anesthesia and Analgesia, 108, 1902–1909.

    Article  Google Scholar 

  269. Wang, D., & Xu, J. P. (2008). A fuzzy multi-objective optimizing scheduling for operation room in hospital. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 614–618).

  270. Wang, Q. N. (2004). Modeling and analysis of high risk patient queues. European Journal of Operational Research, 155, 502–515.

    Article  Google Scholar 

  271. Wang, T., Meskens, N., & Duvivier, D. (2012). A comparison of mixed-integer programming and constraint programming models for scheduling problem in operating theatres. In 2012 International Conference on Information Systems, Logistics and Supply Chain.

  272. Wang, Y., Tang, J., & Fung, R. Y. K. (2014). A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk. International Journal of Production Economics, 158, 28–36.

    Article  Google Scholar 

  273. Wullink, G., Van Houdenhoven, M., Hans, E. W., van Oostrum, J. M., van der Lans, M., & Kazemier, G. (2007). Closing emergency operating rooms improves efficiency. Journal of Medical Systems, 31, 543–546.

    Article  Google Scholar 

  274. Xiang, W., Yin, J., & Lim, G. (2013). Modified ant colony algorithm for surgery scheduling under multiresource constraints. Advances in Information Sciences and Service Sciences, 5, 810.

    Article  Google Scholar 

  275. Xiang, W., Yin, J., & Lim, G. (2014). A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints. Artificial Intelligence in Medicine.

  276. Xue, W., Yan, Z., Barnett, R., Fleisher, L., & Liu, R. (2013). Dynamics of elective case cancellation for inpatient and outpatient in an academic center. Journal of Anesthesia & Clinical Research, 4, 314.

    Google Scholar 

  277. Ya, L., Chengbin, C., & Kanliang, W. (2010). Aggregated state dynamic programming for operating theater planning. In 2010 IEEE International Conference on Automation Science and Engineering (pp. 1013–1018).

  278. Yu, W., Jiafu, T., & Gang, Q. (2010). A genetic algorithm for solving patient-priority-based elective surgery scheduling problem. In Life System Modeling and Intelligent Computing. International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010 (pp. 297–304).

  279. Zhang, B., Murali, P., Dessouky, M. M., & Belson, D. (2009). A mixed integer programming approach for allocating operating room capacity. Journal of the Operational Research Society, 60, 663–673.

    Article  Google Scholar 

  280. Zheng, Z., Xiaolan, X., & Na, G. (2012). Promise surgery start times and implementation strategies. In 2012 IEEE International Conference on Automation Science and Engineering (pp. 143–149).

  281. Zheng, Z., Xiaolan, X., & Na, G. (2014a). Dynamic surgery assignment of multiple operating rooms with planned surgeon arrival times. IEEE Transactions on Automation Science and Engineering, 11, 680–691.

    Article  Google Scholar 

  282. Zheng, Z., Xiaolan, X., & Na, G. (2014b). Simulation-based surgery appointment sequencing and scheduling of multiple operating rooms. In 2014 IEEE International Conference on Automation Science and Engineering (pp. 399–404).

  283. Zonderland, M. E., Boucherie, R. J., Litvak, N., & Vleggeert-Lankamp, C. (2010). Planning and scheduling of semi-urgent surgeries. Health Care Management Science, 13, 256–267.

    Article  Google Scholar 

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Acknowledgments

We acknowledge the support given by the Research Fund - Flanders (FWO) as Aspirant (Carla Van Riet) and as project G-0309.10.

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Samudra, M., Van Riet, C., Demeulemeester, E. et al. Scheduling operating rooms: achievements, challenges and pitfalls. J Sched 19, 493–525 (2016). https://doi.org/10.1007/s10951-016-0489-6

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