Increased Surgical Capacity without Additional Resources: Generalized Operating Room Planning and Scheduling

Abstract

We study a generalized operating room planning and scheduling (GORPS) problem at the Toronto General Hospital (TGH) in Ontario, Canada. GORPS allocates elective patients and resources (i.e., operating rooms, surgeons, anesthetists) to days, assigns resources to patients, and sequences patients in each day. We consider patients’ due‐date, resource eligibility, heterogeneous performances of resources, downstream unit requirements, and lag times between resources. The goal is to create a weekly surgery schedule that minimizes fixed‐ and over‐time costs. We model GORPS using mixed‐integer and constraint programming models. To efficiently and effectively solve these models, we develop new‘ multi‐featured logic‐based Benders decomposition approaches. Using data from TGH, we demonstrate that our best algorithm solves GORPS with an average optimality gap of 2.71% which allows us to provide our practical recommendations. First, we can increase daily OR utilization to reach 80%—25% higher than the status quo in TGH. Second, we do not require to optimize for the daily selection of anesthetists—this finding allows for the development of effective dominance rules that significantly mitigate intractability. Third, solving GORPS without downstream capacities (like many papers in literature) makes GORPS easier to solve, but such OR schedules are only feasible in 24% of instances. Finally, with existing ORs’ safety capacities, TGH can manage 40% increase in its surgical volumes. We provide recommendations on how TGH must adjust its downstream capacities for varying levels of surgical volume increases (e.g., current urgent need for more capacity due to the current Covid‐19 pandemic).

Decomposition of the Knapsack Problem for Increasing the Capacity of Operating Rooms

“…The authors apply an open scheduling strategy for assigning operating rooms to surgeons and a Lagrangian relaxation method for finding promising solutions. Consider another article, namely [10] from 2021, which is similar to ours. In this paper, the authors allocate elective patients and resources (i.e., operating rooms, surgeons, and anesthetists) to days, assign resources to patients, and sequence patients in each day.…”

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

“…In another study, they solved the generalized operating room planning and scheduling (GORPS) problem in a hospital in Toronto with the aim of creating a weekly schedule and the primary goal of reducing fixed and overtime costs by modeling and Banders algorithm. Regarding the outbreak of COVID-19, the intended problem was highly optimal [53], and in the next study, they presented the integrated planning and scheduling of the operating room with the development of the Benders solution method for maximizing the total planned surgery time that the efficiency of it was properly validated [54]. Tsai et al [55] developed a stochastic optimization model for the operating room planning by considering a two -step integer model in uncertain conditions.…”

How does the hospital make a safe and stable elective surgery plan during COVID-19 pandemic?

“…There are two common ways to deal with resource shortages. One is at the operational level, where patients are scheduled to make full use of resources ( Gul et al, 2015 , Naderi et al, 2021 , Vancroonenburg et al, 2016 ), and the other is at the strategy level, where reasonable allocate resources to achieve resource balance ( Best et al, 2015 , Izady and Israa, 2021 , Pinker and Tezcan, 2013 ). this paper focuses on the problem of resource shortages both upstream and downstream by two methods as previously mentioned.…”

“…During the COVID-19 period, a large number of patients flooded into hospitals, and limited resources (especially staffing beds) were occupied ( Muthuswamy 2021 ).Elective surgery cannot be performed normally. For instance, many hospitals are therefore forced to postpone or even cancel elective surgery ( Naderi et al 2021 ). Therefore, the elective patients had to wait for a long time.…”