Operating Room Simulation and Agent-Based Optimization

Operating Room Simulation and Agent-Based Optimization

Q. Peng, Q Niu, Y. Xie, T. ElMekkawy
DOI: 10.4018/978-1-60566-772-0.ch005
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Abstract

Healthcare systems are characterized by uncertainty, variability, complexity, and human roles. Simulation can test scenarios of changes in processes, resources, and schedules without major physical investment or risk. Agent-based technology can model systems with autonomous and interacting activities. This chapter introduces the method of using simulation and agent-based technologies to enable a better understanding of the patient flow to improve the process performance in healthcare. The proposed method is used to identify the existing problem and to evaluate proposed solutions for the problem of the operating room (OR) at Winnipeg Health Sciences Centre. Issues are identified including patient flows, operation schedules, demand and capacity of the system and the configuration of resources required. An optimum scheduling is proposed for the OR operation to shorten the patient waiting time.
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Introduction

Healthcare systems provide health-related services by the medical, nursing, and allied health professions. Healthcare is an enormous part of the economy as it consumes average 6.7 percent of GDP in the high-income countries (WHO, 2008). Healthcare in Canada is funded and delivered through a publicly funded healthcare system. Canada spent an estimated $142 billion on healthcare in 2005, or $4,411 per person. It was projected to reach $160 billion, or 10.6% of GDP, in 2007 (CBC, 2006). A common problem of Canadian healthcare systems is a long waiting list of patients, which may result from the inefficient utilization of human resources and facilities, or the failure to eliminate non-value added activities. It is critical to improve the performance and productivity of the national healthcare system.

Winnipeg Health Sciences Centre (WHSC) is a healthcare centre serving residents of Manitoba, Northwestern Ontario and Nunavut. The operating room (OR) department is one of the most demanding departments in WHSC based on the statistical data. The problems of the OR are the long waiting list of patients and the inefficient utilization of resources.

This chapter introduces the use of computer simulation and agent-based methods to analyze and improve performance of the OR department in WHSC. Computer simulation is an efficient way to imitate real-world problems over time for analyzing and describing the behaviour of the real-system (Mahapatra, 2003). One of the main capabilities using simulation is to analyze what-if scenarios, which allows a significant exploration of multiple options, without spending enormous amounts of expense on staff, training, and equipment (Barnes, 1997). The term agent has been used for an entity in a system with key properties autonomy, social ability, reactivity and pro-activeness. A multi-agent system is a group of agents that interact with each other to solve complex problems (Mes, 2007). Multi-agent technology offers a convenient platform to represent real units for optimization and visualization of flows of material, work, and information. It has features of scalability, modularity, flexibility, and online reconfigurability (Garcia, 2008). Therefore, the computer simulation and agent-based optimization are used in this research for the performance improvement of healthcare systems. The simulation model is used to identify existing problems and to evaluate proposed solutions. The agent-based optimization is applied to model the system and find solutions of the problems.

Following parts of this chapter will first describe the research background of healthcare system simulation and agent-based optimization. Details of the simulation modeling for the OR department at WHSC will then be discussed. Different healthcare variables and constraints are considered in the system modeling. The agent-based method is introduced based on the analysis of the simulation solution. The conclusion and further work will also be discussed.

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