Application of Simulation and Response Surface to Optimize Hospital Resources
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32813
Application of Simulation and Response Surface to Optimize Hospital Resources

Authors: Shamsuddin Ahmed, Francis Amagoh

Abstract:

This paper presents a case study that uses processoriented simulation to identify bottlenecks in the service delivery system in an emergency department of a hospital in the United Arab Emirates. Using results of the simulation, response surface models were developed to explain patient waiting time and the total time patients spend in the hospital system. Results of the study could be used as a service improvement tool to help hospital management in improving patient throughput and service quality in the hospital system.

Keywords: Simulation, Hospital Service, Resource Utilization, United Arab Emirates.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085365

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1456

References:


[1] B. Cardeon, and E. Demeulemeester, "Capacity of clinical pathways: a strategic multi-level evaluation tool," Journal of Medical Systems, vol. 32, pp. 443- 452, 2008.
[2] P. Dey, and S. Hariharan, "Integrated approach to healthcare quality management: a case study," The TQM Magazine, vol. 18, no. 6, pp. 583-597, 2006.
[3] J. Everett, "A decision support simulation model for the management of an elective surgery waiting system," Health Care Management Science, vol. 5, no. 2, pp. 89-95, 2002.
[4] J. Fitzgerald, and A. Dadich, "Using visual analytics to improve hospital scheduling and patient flow," Journal of Theoretical and Applied Electronic Commerce Research, vol. 4, no. 2, pp. 20-30, 2009.
[5] N. Fleischner, R. Gershwin, and L. Dick, " Improving observation status in a hospital" Physician Executive, vol. 36, no. 2, pp. 34-37, 2010.
[6] L. Green, P. Kolesar, and W. Whitt, "Coping with time-varying demand when setting staffing requirements for a service system," Production and Operations Management, vol. 16, no. 1, pp. 13-49. 2007.
[7] A. Jamal, and K. Anastasiadou, "Investing the effects of service quality dimensions and expertise on loyalty," European Journal of Marketing, vol. 43, no. 3/4, pp. 398-420, 2010.
[8] L. Jiang, L., and R. Giachetti, "A queueing network model to analyze the impact of parallelization of care on patient cycle time," Health Care Management Science, vol. 11, pp. 248-261, 2008.
[9] D. Mukamel, L. Glance, A. Dick, and O. Turner, "Measuring quality for product reporting of health provider quality: Making it meaningful to patients." American Journal of Public Health, vol. 100, no. 2, pp. 264- 269, 2010.
[10] C. Teng, Y. Dai, Y. Shyu, M. Wong, T. Chu, T, and Y. Tsai, "Professional commitment, patient safety, and patient-perceived care quality," Journal of Nursing Scholarship, vol. 41, no. 3, pp. 301-309, 2008.
[11] C. Wang, Y. Lee, and W. Lin, "Application of queuing model in healthcare administration with incorporation of human factors,"Journal of American Academy of Business, vol. 8, no. 1, pp. 304-310, 2006.
[12] J. Yeh, and W. Lin, (2007). Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department," Expert Systems with Applications, vol. 32, no. 4, pp. 1073- 1083, 2007.