Optimizing the Service Provision time in the Emergency Department Using Mathematical Modeling and Simulation (Case Study: Imam Reza Hospital)

Document Type : Original Article

Authors

1 Associate Prof., Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran

2 Associate Prof., Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran.

3 MSc, Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran.

Abstract

Patient waiting time, the costs, and nurses’ job satisfaction level are important criteria in providing services in hospital.  One of the main causes of long patient waiting times is the lack of sufficient expert staff in the hospital. Increased costs and low job satisfaction of nursing staff in hospitals are the result of applying traditional and nonscientific methods in assigning nurses to shifts. The emergency department is one of the special units in the hospital, in which studying the patient flow is highly important. In this study, the current status of Imam Reza Hospital emergency department in Tabriz, Iran is simulated using ARENA 14 software, in order to assess the costs and size of the waiting line. Then, the current status of this department is compared with three scenarios with different number of nurses. In order to evaluate the costs and nurse job satisfaction in each scenario, a nonlinear integer programming mathematical model is proposed. In this model, nurses are properly assigned to shifts and weekdays in order to minimize the costs and to increase nurse job satisfaction. Finally, analyzing both nonlinear programming and simulation model, the results show that the number of nurses in this department is not sufficient and that six nurses should be added to the staff.

Keywords

Main Subjects

References

  1. AUF'M HOFE, H. M. (2011). Solving rostering tasks by generic methods for constraint optimization. International Journal of Foundations of Computer Science, 12(05), 671-693.

    1. White, (2015) “World development report 2015: mind, society, and behavior, by the World Bank Group,” Can. J. Dev. Stud. / Rev. Can. d’études du développement, vol. 36, no. 4, pp. 581–584, Oct.

    Cochran, J. K., & Bharti, A. (2006). Stochastic bed balancing of an obstetrics hospital. Health care management science, 9(1), 31-45.

    Cochran, J. K., & Bharti, A. (2006). Stochastic bed balancing of an obstetrics hospital. Health care management science, 9(1), 31-45.

    Edwards, R. H., Clague, J. E., Barlow, J., Clarke, M., Reed, P. G., & Rada, R. (1994). Pragmatics. Health Care Analysis, 2(2), 164-169.

    El Adoly, A. A., Gheith, M., & Fors, M. N. (2018). A new formulation and solution for the nurse scheduling problem: A case study in Egypt. Alexandria Engineering Journal.

    García, M. L., Centeno, M. A., Rivera, C., & DeCario, N. (1995, December). Reducing time in an emergency room via a fast-track. In Proceedings of the 27th conference on Winter simulation (pp. 1048-1053). IEEE Computer Society.

     Ghaffari, S., Jackson, T. J., Doran, C. M., Wilson, A., & Aisbett, C. (2008). Describing Iranian hospital activity using Australian refined DRGs: A case study of the Iranian social security organisation. Health Policy, 87(1), 63-71.

    Kirtland, A., Lockwood, J., Poisker, K., Stamp, L., & Wolfe, P. (1995, December). Simulating an emergency department" is as much fun as...". In Simulation Conference Proceedings, 1995. Winter (pp. 1039-1042). IEEE.

    Kraitsik, M. J., & Bossmeyer, A. (1993, January). Simulation applied to planning an emergency department expansion. In Proceedings of the 1993 SCS Western Multiconference on Simulation: Simulation in Health Sciences and Services (pp. 19-27).

    McGuire, F. (1994, December). Using simulation to reduce length of stay in emergency departments. In Simulation Conference Proceedings, 1994. Winter (pp. 861-867). IEEE.

    Miller, M. J., Ferrin, D. M., & Szymanski, J. M. (2003, December). Emergency departments II: simulating Six Sigma improvement ideas for a hospital emergency department. In Proceedings of the 35th conference on Winter simulation: driving innovation (pp. 1926-1929). Winter Simulation Conference.

    Ritondo, M., & Freedman, R. W. (1993, January). The effects of procedure scheduling on emergency room throughput: A simulation study. In 1993 SCS Western Multiconference on Simulation: Simulation in the Health Sciences and Services. Society for Computer Simulation, La Jolla, California, USA (pp. 17-20).

    1. Mahapatra, C. Koelling, L. Patvivatsiri, B. Fraticelli, D. Eitel, and L. Grove,( 2003) Pairing emergency severity index5-level triage data with computer aided system design to improve emergency department access and throughput, in Simulation Conference, 2003. Proceedings of the 2003 Winter, , pp. 1917-1925.

    Samaha, S., Armel, W. S., & Starks, D. W. (2003, December). Emergency departments I: the use of simulation to reduce the length of stay in an emergency department. In Proceedings of the 35th conference on Winter simulation: driving innovation (pp. 1907-1911). Winter Simulation Conference.

    Sinreich, D., & Marmor, Y. N. (2004, December). A simple and intuitive simulation tool for analyzing emergency department operations. In Proceedings of the 36th conference on Winter simulation (pp. 1994-2002). Winter Simulation Conference.

    Takakuwa, S., & Shiozaki, H. (2004, December). Functional analysis for operating emergency department of a general hospital. In Simulation Conference, 2004. Proceedings of the 2004 Winter (Vol. 2, pp. 2003-2011). IEEE.

    Trybou, J., Gemmel, P., & Annemans, L. (2015). Provider accountability as a driving force towards physician–hospital integration: a systematic review. International journal of integrated care, 15(1).

    Tsai, C. C., & Li, S. H. (2009). A two-stage modeling with genetic algorithms for the nurse scheduling problem. Expert Systems with Applications, 36(5), 9506-9512.

Send comment about this article
CAPTCHA Image

Files

Share

How to cite

Statistics