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Evaluating multiple performance measures across several dimensions at a multi-facility outpatient center

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  • Marie Matta
  • Sarah Patterson

Abstract

Over the past several decades healthcare delivery systems have received increased pressure to become more efficient from both a managerial and patient perspective. Many researchers have turned to simulation to analyze the complex systems that exist within hospitals, but surprisingly few have published guidelines on how to analyze models with multiple performance measures. Moreover, the published literature has failed to address ways of analyzing performance along more than one dimension, such as performance by day of the week, patient type, facility, time period, or some combination of these attributes. Despite this void in the literature, understanding performance along these dimensions is critical to understanding the root of operational problems in almost any daily clinic operation. This paper addresses the problem of multiple responses in simulation experiments of outpatient clinics by developing a stratification framework and an evaluation construct by which managers can compare several operationally different outpatient systems across multiple performance measure dimensions. This approach is applied to a discrete-event simulation model of a real-life, large-scale oncology center to evaluate its operational performance as improvement initiatives affecting scheduling practices, process flow, and resource levels are changed. Our results show a reduction in patient wait time and resource overtime across multiple patient classes, facilities, and days of the week. This research has already proven to be successful as certain recommendations have been implemented and have improved the system-wide performance at the oncology center. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Marie Matta & Sarah Patterson, 2007. "Evaluating multiple performance measures across several dimensions at a multi-facility outpatient center," Health Care Management Science, Springer, vol. 10(2), pages 173-194, June.
    • Handle: RePEc:kap:hcarem:v:10:y:2007:i:2:p:173-194
    DOI: 10.1007/s10729-007-9010-2
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    References listed on IDEAS

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    Cited by:

    1. Bohui Liang & Ayten Turkcan & Mehmet Erkan Ceyhan & Keith Stuart, 2015. "Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7177-7190, December.
    2. 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.
    3. A. G. Leeftink & I. M. H. Vliegen & E. W. Hans, 2019. "Stochastic integer programming for multi-disciplinary outpatient clinic planning," Health Care Management Science, Springer, vol. 22(1), pages 53-67, March.
    4. Kit Simpson & Alvin Strassburger & Walter Jones & Birgitta Dietz & Rukmini Rajagopalan, 2009. "Comparison of Markov Model and Discrete-Event Simulation Techniques for HIV," PharmacoEconomics, Springer, vol. 27(2), pages 159-165, February.
    5. M. Heshmat & A. Eltawil, 2021. "Solving operational problems in outpatient chemotherapy clinics using mathematical programming and simulation," Annals of Operations Research, Springer, vol. 298(1), pages 289-306, March.
    6. Mielczarek, Bożena, 2014. "Simulation modelling for contracting hospital emergency services at the regional level," European Journal of Operational Research, Elsevier, vol. 235(1), pages 287-299.
    7. Ming Lv & Yi Li & Bo Kou & Zhili Zhou, 2017. "Integer programming for improving radiotherapy treatment efficiency," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-9, July.
    8. Bożena Mielczarek, 2016. "Review of modelling approaches for healthcare simulation," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 26(1), pages 55-72.
    9. Marynissen, Joren & Demeulemeester, Erik, 2019. "Literature review on multi-appointment scheduling problems in hospitals," European Journal of Operational Research, Elsevier, vol. 272(2), pages 407-419.
    10. 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.
    11. Li, Na & Pan, Jie & Xie, Xiaoqing, 2020. "Operational decision making for a referral coordination alliance- When should patients be referred and where should they be referred to?," Omega, Elsevier, vol. 96(C).
    12. Guillaume Lamé & Oualid Jouini & Julie Stal-Le Cardinal, 2016. "Outpatient Chemotherapy Planning: a Literature Review with Insights from a Case Study," Post-Print hal-01324488, HAL.
    13. Shoaib, Mohd & Mustafee, Navonil & Madan, Karan & Ramamohan, Varun, 2023. "Leveraging multi-tier healthcare facility network simulations for capacity planning in a pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    14. Mahmoud, Hussam & Kirsch, Thomas & O'Neil, Dan & Anderson, Shelby, 2023. "The resilience of health care systems following major disruptive events: Current practice and a path forward," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    15. Matta, Marie E. & Elmaghraby, Salah E., 2010. "Polynomial time algorithms for two special classes of the proportionate multiprocessor open shop," European Journal of Operational Research, Elsevier, vol. 201(3), pages 720-728, March.

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