Operating room scheduling by emphasising human factors and dynamic decision-making styles: a constraint programming method

ABSTRACT

As the most crucial component of a hospital, the operating room (OR) is the primary source of revenue generation and expenditures. The hospital’s overall performance will be enhanced if this ward’s scheduling is accurate. This study investigates a multi-objective mixed-integer programming model for daily OR scheduling of inpatient surgeries. A major consideration is the setup time (e.g. cleaning, sterilising, and preparing the necessary OR equipment) for the OR when commencing additional surgeries in the same OR. The surgical staff’s performance, interaction quality, and compatibility level play a significant role in the surgery’s quality, success, and safety. As individuals’ decision-making styles vary depending on the situation, one of the objectives increases the compatibility of surgical team members by considering their primary and backup decision-making styles. Another objective is to maximise the efficiency of the surgical team. To this end, this paper employs the TOPSIS method to calculate each person’s efficiency level. The final objective is to minimise OR costs (including the opening and overtime cost of OR and wait time cost for each person). To address problem’s computational complexity, this paper develops a constraint programming (CP) method, and also a novel hybrid mixed-integer linear programming-CP method to solve the real-world instances.

KEYWORDS:

• Operating room scheduling
• human factors
• sequence-dependent setup
• dynamic decision-making styles
• constraint programming method

Acknowledgements

The authors certify that this paper does not contain any studies or involvement with human participants or animals performed by any authors in any organisation or entity with any financial or non-financial interest in the subject matter or materials discussed in this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within this paper and supplementary material. Also, they are available from the authors upon reasonable request.

Additional information

Notes on contributors

Shirin Ghasemi

Shirin Ghasemi is a Ph.D. candidate in Industrial Engineering at Clemson University, located in Clemson, South Carolina, USA. She holds a Master's degree in Industrial Engineering from the University of Tehran, Iran (awarded in 2023), and a B.Sc. degree in Industrial Engineering from the K.N. Toosi University of Technology, Tehran, Iran (earned in 2019). Shirin's research interests primarily focus on healthcare systems, specifically in the areas of operating room scheduling and data analysis. She has made valuable contributions to the field of healthcare optimization, with her five papers being published in reputable journals and conference proceedings. Her dedication to advancing knowledge in this field is evident through her academic pursuits and research achievements.

Reza Tavakkoli-Moghaddam

Reza Tavakkoli-Moghaddam is a Professor of Industrial Engineering at College of Engineering, the University of Tehran, Iran. He obtained his Ph.D., M.Sc. and B.Sc. degrees in Industrial Engineering from the Swinburne University of Technology in Melbourne (1998), the University of Melbourne in Melbourne (1994), and the Iran University of Science and Technology in Tehran (1989), respectively. He serves as the Editor-in-Chief of the “Advances in Industrial Engineering” journal published by the University of Tehran and as the Editorial Board member of nine reputable academic journals. He is the recipient of the 2009 and 2011 Distinguished Researcher Awards and the 2010 and 2014 Distinguished Applied Research Awards at the University of Tehran, Iran. He has been selected as the National Iranian Distinguished Researcher in 2008 and 2010 by the MSRT (Ministry of Science, Research, and Technology) in Iran. He has obtained an outstanding rank as the top 1% scientist and researcher in the world elite group since 2014. He also received the Order of Academic Palms Award as a distinguished educator and scholar for the insignia of Chevalier dans l'Ordre des Palmes Academiques by the Ministry of National Education of France in 2019. He has published 5 books, 37 book chapters, and more than 1000 journal and conference papers.

Mahdi Hamid

Mahdi Hamid is a Ph.D. candidate in Industrial Engineering at College of Engineering, University of Tehran (UT), Iran. He obtained his M.Sc. degree from the School of Industrial Engineering at the UT in 2015. His research interests are mathematical modelling, operation research, logistics, simulation, data analysis, and healthcare engineering. Practical knowledge as a reviewer of several prestigious journals in the field of operations research, management science, data analysis, and healthcare engineering. He has published more than 30 papers in reputable conferences and academic journals.