Optimization, Simulation and Predictive Analytics in Healthcare

  • Janya Chanchaichujit
  • Albert Tan
  • Fanwen Meng
  • Sarayoot Eaimkhong


This chapter discusses the use of operations research techniques such as optimization, simulations and predictive analytics in healthcare. The chapter introduces optimization problems in healthcare, from strategic resources and capacity planning to operational and clinical issues such as resource scheduling and treatment planning. Case studies using operations research in healthcare in Singapore will be presented, followed by some insights into improved healthcare delivery.


Operations research Optimization Healthcare service planning Shift capacity planning Bed management Inpatient flow 


  1. AJPH. (1952). Operations research and public health. American Journal of Public Health and the Nations Health, 42(10), 1306–1307.Google Scholar
  2. Alagoz, O., Hus, H., Schaefer, A. J., & Roberts, M. S. (2010). Markov decision process: A tool for sequential decision making under uncertainty. Medical Decision Making, 30(4), 474–483.Google Scholar
  3. Asmussen, S., & Nerman, O. (1996). Fitting phase-type distributions via the EM algorithm. Scandinavian Journal of Statistics, 23(4), 419–441.Google Scholar
  4. Ben-Tal, A., & Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operations Research, 23(4), 769–805. Scholar
  5. Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53. Scholar
  6. Boyle, A., Beniuk, K., Higginson, I., & Atkinson, P. (2012). Emergency department crowding: Time for interventions and policy evaluations. Emergency Medicine International, 2012(2012), 838610–838610. Scholar
  7. Burke, E., De Causmaecker, P., Berghe, G., & Van Landeghem, H. (2004). The state of the art of nurse rostering. Journal of Scheduling, 7(6), 441–499. Scholar
  8. Bursch, B., Beezy, J., & Shaw, R. (1993). Emergency department satisfaction: What matters most? Annals of Emergency Medicine, 22(3), 586–591. Scholar
  9. Capan, M., Khojandi, A., Denton, B. T., Williams, K. D., Ayer, T., Chhatwal, J., … Zaric, G. (2017). From data to improved decisions: Operations research in healthcare delivery. Medical Decision Making, 37(8), 849–859.CrossRefGoogle Scholar
  10. Cayirli, T., & Veral, E. (2003). Outpatient scheduling in health care: A review of literature. Production and Operations Management, 12(4), 519–549. Scholar
  11. Cheang, B., Li, H., Lim, A., & Rodrigues, B. (2003). Nurse rostering problems––A bibliographic survey. European Journal of Operational Research, 151(3), 447–460. Scholar
  12. Chen, X., Sim, M., & Sun, P. (2007). A robust optimization perspective on stochastic programming. Operations Research, 55(6), 1058–1071, 1191, 1193. Scholar
  13. Chin, R., You, A. X., Meng, F., Zhou, J., & Sim, K. (2018). Recognition of schizophrenia with combinatorial regularized support vector machine and sequential region of interest selection using structural magnetic resonance imaging. Scientific Reports, 8, 13858.Google Scholar
  14. Delage, E., & Ye, Y. (2010). Distributionally robust optimization under moment uncertainty with application to data-driven problems. Operations Research, 58(3), 595–612, 768, 772. Scholar
  15. Denton, B. T., Alagoz, O., Holder, A., & Lee, E. K. (2011). Medical decision making: Open research challenges. IIE Transactions on Healthcare Systems Engineering, 1(3), 161–167. Scholar
  16. Denton, B., Murat, K., Nilay, S., Bryant, S., & Smith, S. (2009). Optimizing the start time of statin therapy for patients with diabetes. Medical Decision Making, 29(3), 351–367.Google Scholar
  17. Dowsland, K. A., & Thompson, J. M. (2000). Solving a nurse scheduling problem with knapsacks, networks and tabu search. Journal of the Operational Research Society, 51(7), 825. Scholar
  18. Fackrell, M. (2009). Modelling healthcare systems with phase-type distributions. Health Care Management Science, 12(1), 11–26. Scholar
  19. Faddy, M., & McClean, S. (1999). Analysing data on lengths of stay of hospital patients using phase-type distributions. Applied Stochastic Models in Business and Industry, 15(4), 311–317.CrossRefGoogle Scholar
  20. Goh, J., & Sim, M. (2010). Distributionally robust optimization and its tractable approximations. Operations Research, 58(4), 902–917, 1029, 1032. Scholar
  21. Harper, P. (2002). A framework for operational modelling of hospital resources. Health Care Management Science, 5(3), 165–173. Scholar
  22. Harper, P. R., & Gamlin, H. M. (2003). Reduced outpatient waiting times with improved appointment scheduling: A simulation modelling approach. Quantitative Approaches in Management, 25(2), 207–222. Scholar
  23. Harper, P. R., & Shahani, A. K. (2001). Modelling for the planning and management of bed capacities in hospitals. Journal of the Operational Research Society, 53(1), 11. Scholar
  24. Hu, Y. C., Chen, J. C., Chiu, H. T., Shen, H. C., & Chang, W. Y. (2010). Nurses’ perception of nursing workforce and its impact on the managerial outcomes in emergency departments. Journal of Clinical Nursing, 19(11–12), 1645–1653. Scholar
  25. Hwang, U., & Concato, J. (2004). Care in the emergency department: How crowded is overcrowded? Academic Emergency Medicine, 11(10), 1097–1101. Scholar
  26. Jaumard, B., Semet, F., & Vovor, T. (1998). A generalized linear programming model for nurse scheduling. European Journal of Operational Research, 107(1), 1–18. Scholar
  27. Kurt, M., Denton, B. T., Schaefer, A. J., Shah, N. D., & Smith, S. A. (2011). The structure of optimal statin initiation policies for patients with type 2 diabetes. IIE Transactions on Healthcare Systems Engineering, 1(1), 49–65. Scholar
  28. Librero, J., Marn, M., Peir, S., & Munujos, A. V. (2004). Exploring the impact of complications on length of stay in major surgery diagnosis-related groups. International Journal for Quality in Health Care, 16(1), 51–57. Scholar
  29. Mason, J. E., Denton, B. T., Shah, N. D., & Smith, S. A. (2014). Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients. European Journal of Operational Research, 233(3), 727–738. Scholar
  30. Meng, F., Teow, K. L., Ooi, C. K., Soh, C. K. K., & Tay, S. Y. (2016). Shift capacity planning for nursing staff in emergency department using mixed integer programming. Pacific Journal of Optimization, 12(3), 635–648.Google Scholar
  31. Meng, F., Teow, K. L., Teo, K. W. S., Ooi, C. K., & Tay, S. Y. (2019). Predicting 72-hour reattendance in emergency departments using mixed integer programming via discriminant analysis with electronic medical records. Journal of Industrial and Management Optimization, 15(2), 947–962.Google Scholar
  32. Mowen, J. C., Licata, J. W., & McPhail, J. (1993). Waiting in the emergency room: How to improve patient satisfaction. Journal of Health Care Marketing, 13(2), 26–33.Google Scholar
  33. Olsson, M. (1996). Estimation of phase-type distributions from censored data. Scandinavian Journal of Statistics, 23(4), 443–460.Google Scholar
  34. Rais, A., & Viana, A. (2010). Operations research in healthcare: A survey. International Transaction in Operational Research, 18(1), 1–31.Google Scholar
  35. Siciliani, L., & Hurst, J. (2005). Tackling excessive waiting times for elective surgery: A comparative analysis of policies in 12 OECD countries. Health Policy, 72(2), 201–215. Scholar
  36. Sinreich, D., & Marmor, Y. (2005). Ways to reduce patient turnaround time and improve service quality in emergency departments. Journal of Health Organization and Management, 19(2), 88–105. Scholar
  37. Sun, Y., Teow, K. L., Heng, B. H., Ooi, C. K., & Tay, S. Y. (2012). Real-time prediction of waiting time in the emergency department, using quantile regression. Annals of Emergency Medicine, 60(3), 299–308. Scholar
  38. Thompson, D. A., & Yarnold, P. R. (1995). Relating patient satisfaction to waiting time perceptions and expectations: The disconfirmation paradigm. Academic Emergency Medicine, 2(12), 1057–1062. Scholar
  39. Trinkoff, M. A., Johantgen, L. M., Storr, P. C., Gurses, P. A., Liang, P. Y., & Han, P. K. (2011). Nurses’ work schedule characteristics, nurse staffing, and patient mortality. Nursing Research, 60(1), 1–8. Scholar
  40. Vincent, A. K., & Paul, R. H. (2012). Modelling emergency medical services with phase-type distributions. Health Systems, 1(1), 58. Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  • Janya Chanchaichujit
    • 1
  • Albert Tan
    • 2
  • Fanwen Meng
    • 3
  • Sarayoot Eaimkhong
    • 4
  1. 1.School of ManagementWalailak UniversityThasalaThailand
  2. 2.Malaysia Institute for Supply Chain InnovationShah AlamMalaysia
  3. 3.Department of Health Services & Outcomes ResearchNational Healthcare GroupSingaporeSingapore
  4. 4.National Science and Technology Development AgencyPathum ThaniThailand

Personalised recommendations