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Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment

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Listed:
  • Chong Pan
  • Dali Zhang
  • Audrey Kon
  • Charity Wai
  • Woo Ang

Abstract

Continuous improvement in process efficiency for specialist outpatient clinic (SOC) systems is increasingly being demanded due to the growth of the patient population in Singapore. In this paper, we propose a discrete event simulation (DES) model to represent the patient and information flow in an ophthalmic SOC system in the Singapore National Eye Centre (SNEC). Different improvement strategies to reduce the turnaround time for patients in the SOC were proposed and evaluated with the aid of the DES model and the Design of Experiment (DOE). Two strategies for better patient appointment scheduling and one strategy for dilation-free examination are estimated to have a significant impact on turnaround time for patients. One of the improvement strategies has been implemented in the actual SOC system in the SNEC with promising improvement reported. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Chong Pan & Dali Zhang & Audrey Kon & Charity Wai & Woo Ang, 2015. "Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment," Health Care Management Science, Springer, vol. 18(2), pages 137-155, June.
    • Handle: RePEc:kap:hcarem:v:18:y:2015:i:2:p:137-155
    DOI: 10.1007/s10729-014-9291-1
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    References listed on IDEAS

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    1. Riitta Marjamaa & Paulus Torkki & Eero Hirvensalo & Olli Kirvelä, 2009. "What is the best workflow for an operating room? A simulation study of five scenarios," Health Care Management Science, Springer, vol. 12(2), pages 142-146, June.
    2. J B Jun & S H Jacobson & J R Swisher, 1999. "Application of discrete-event simulation in health care clinics: A survey," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(2), pages 109-123, February.
    3. N C Proudlove & S Black & A Fletcher, 2007. "OR and the challenge to improve the NHS: modelling for insight and improvement in in-patient flows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 145-158, February.
    4. Jacqueline Griffin & Shuangjun Xia & Siyang Peng & Pinar Keskinocak, 2012. "Improving patient flow in an obstetric unit," Health Care Management Science, Springer, vol. 15(1), pages 1-14, March.
    5. Pablo Santibáñez & Vincent Chow & John French & Martin Puterman & Scott Tyldesley, 2009. "Reducing patient wait times and improving resource utilization at British Columbia Cancer Agency’s ambulatory care unit through simulation," Health Care Management Science, Springer, vol. 12(4), pages 392-407, December.
    6. Qu, Xiuli & Shi, Jing, 2011. "Modeling the effect of patient choice on the performance of open access scheduling," International Journal of Production Economics, Elsevier, vol. 129(2), pages 314-327, February.
    7. Thomas Rohleder & Peter Lewkonia & Diane Bischak & Paul Duffy & Rosa Hendijani, 2011. "Using simulation modeling to improve patient flow at an outpatient orthopedic clinic," Health Care Management Science, Springer, vol. 14(2), pages 135-145, June.
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    Cited by:

    1. Barros, Oscar & Weber, Richard & Reveco, Carlos, 2021. "Demand analysis and capacity management for hospital emergencies using advanced forecasting models and stochastic simulation," Operations Research Perspectives, Elsevier, vol. 8(C).
    2. Jesús Isaac Vázquez-Serrano & Rodrigo E. Peimbert-García & Leopoldo Eduardo Cárdenas-Barrón, 2021. "Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
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    5. Tugba Cayirli & Kum Khiong Yang, 2019. "Altering the Environment to Improve Appointment System Performance," Service Science, INFORMS, vol. 11(2), pages 138-154, June.

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