01:30 PM - 02:00 PM
A Mixed Offline and Online Approach to Manage Elective and Non-Elective Patients
At the operational decision level, the Operating Room (OR) management is also called "surgery process scheduling" and is generally separated into two sub-problems referred to as "advanced scheduling" and "allocation scheduling". Usually, the two sub-problems have different and conflictual objectives, that is to maximize the OR utilization and to minimize the number of patient delayed or cancelled, respectively.
The management of non-elective patients is a really complex task: actually, delaying an urgent non-elective surgery may increase the risk of postoperative complications and morbidity. Therefore, the speed at which an OR is available for that surgery, is the crucial factor to guarantee a positive final outcome. A common approach is to reserve OR capacity since it is believed to increase the responsiveness. This approach poses a question, that is if it is better to have dedicated ORs or, alternatively, to reserve capacity in the elective ORs.
We discuss the problem of dealing with a joint flow of elective and non-elective patients within a surgical pathway. In literature, different solutions (dedicated operating room vs. flexible policy) have been proposed determining opposed results. Furthermore, to the best of our knowledge, online optimization is never been applied to the context of the Operating Room Planning.
In this paper, we propose a mixed offline and online approach to improve the management of elective and non-elective patients. The solution framework is built on a DES methodology in order to model the patient flows and to deal with the inherent stochasticity of the problem. Further, we will address the analysis of the trade-offs between the use of dedicated operating rooms and a flexible policy.
02:00 PM - 02:30 PM
Rescheduling of Elective Patients
We study in two phases how to build the schedule of elective patients in a unit of a hospital. We have to choose some patients from a waiting list and assign them a session in one of several operating rooms. The planning period is two weeks. In the first phase we study how to calculate a first schedule, two-three weeks before the actual planning period, with the goals of minimizing the percentage of late patients – operated on after their due dates – and maximising the utilisation of the operating rooms. The biggest problem in this part of the study is that the first goal is a long-term goal, not easily grasped in a two-week optimisation problem. This first schedule is built to be able to inform the chosen patients and to make any special preparations needed for the operations. Few days before the planning period, this first schedule is revisited. Usually some of the operations cannot be performed, due to unavailability of patients, doctors or necessary equipment. It is necessary to calculate a new schedule, which is done in the second phase of the study. The idea is to calculate a new schedule with the same goals as the original one, but similar to that schedule. We study how to define similarities between two schedules. Finally, we present the decision maker several possible solutions so that s/he chooses one. Some of these solutions are closer to the original one, and others are better in terms of the goals.
02:30 PM - 03:00 PM
Trade-offs in operating room planning for electives and emergencies
The planning of the operating rooms (ORs) is a difficult process due to the different stakeholders involved. The real complexity, however, results from various sources of variability. This variability cannot be ignored since it greatly influences the trade-offs between the hospital costs and the patient waiting times. As a result, a need for policies guiding the OR manager in handling the trade-offs arises. Therefore, researchers have investigated different possibilities to incorporate non-elective patients in the schedule with the goal of maximizing both patient- and hospital-related measures. The literature on OR planning, where both elective and non-elective patient categories are involved, shows various policies. Due to the differences in the research settings however, contradicting results on measures such as overtime and the patient waiting time are reported. Decisions on both operational policies as well as on capacity are required to assure timely access and efficiency, which are the two main drivers for the problem at hand. Trough discrete event simulation, we show the impact of capacity allocation decisions on various performance measures and include patient categories with different due times, the variability in the arrival process and rescheduling actions. For this, we use data of a large OR complex of a university hospital in Belgium.