4 présentations

• 
  15h30 - 15h55

  Master Surgery Scheduling Problem Considering Uncertainty in Time of Stay in Downstream Units

  • Erfaneh Nikzad, prés., polytechnique montréal
  • Nadia Lahrichi, Polytechnique Montréal

  This study presents a novel mathematical model for the master surgery scheduling problem, taking into consideration uncertainties in the duration of stay in downstream units, such as wards and ICU beds, which patients utilize during their post-surgery recovery. Without accounting for wards and ICU beds availability, determining master surgery schedules may lead to impractical scheduling, resulting in surgery cancellations or premature discharge, ultimately impacting patient satisfaction. The length of stay post-surgery, both in the surgical unit and ICU, is uncertain and influences bed availability. Therefore, this study incorporates the post-surgery length of stay as stochastic parameters, defined within a limited set of scenarios. A two-stage stochastic programming model is employed to address uncertainties. Furthermore, a matheuristic algorithm is developed to effectively solve the proposed model within a reasonable time.

• 
  15h55 - 16h20

  Optimization of Nurse Scheduling: Case Study at Maisonneuve-Rosemont Hospital

  • Nohaila Ahssinou, prés., Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal

  Effectively managing nurses' schedules is crucial, especially in the face of the ongoing nurse shortage. It is essential to optimize resources and retain skilled personnel to prevent increased turnover and professional burnout. Our focus is on improving nurse scheduling within the obstetric care unit of Maisonneuve-Rosemont Hospital (HMR). We aim to develop an optimal plan that takes into account both nurse preferences and operational requirements, a challenge commonly known as the Nurse Rostering Problem (NRP) or Nurse Scheduling Problem (NSP). While existing literature often discusses hospital scheduling challenges using operations research, few practical solutions are implemented due to the unique characteristics of each organization. To tackle this, we use a mixed integer linear programming (MILP) approach, using an open-source solver due to budget constraints. We analyze the solution with various indicators and feedback from hospital staff. This collaborative effort underscores critical success factors like internal leadership and comprehension of organizational dynamics. Challenges encountered during implementation are addressed through ongoing collaboration, with enhancements planned for subsequent project phases. Thus, our project aims to deliver a practical solution for nurse schedule management at Maisonneuve-Rosemont Hospital, blending theoretical rigor with a collaborative approach tailored to meet specific organizational needs.

• 
  16h20 - 16h45

  Optimization of Patient Assignment in Hemodialysis

  • Marie-Claude Normand, prés., Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal

  The challenges of hemodialysis treatment, which require multiple weekly hospital visits lasting several hours, emphasize the critical need for efficient assignment planning and scheduling. Resolving assignment and scheduling challenges proves difficult due to the variability in appointment durations, equipment needs, and patient workloads, which often conflict with the goals of minimizing patient wait times and ensuring equitable division of workloads among nurses. In collaboration with a hemodialysis center, our study proposes a mathematical approach to address assignment and scheduling challenges. Our primary objectives include optimizing patient-to-nurse-to-chair assignments considering equity and distance between the patients' chairs and scheduling patient arrival times. An interface is also designed to enable hemodialysis center managers to generate weekly patient assignments and arrival times. We develop a multi-objective mathematical model based on consultations with healthcare professionals. Real-world data, including patient characteristics, staff availability, and the spatial organization of a hemodialysis clinic, serve as inputs to our mathematical model. Methodologically, our approach involves rigorous testing and validation procedures, including simulation studies utilizing historical data. Preliminary results demonstrate promising enhancements in the quality of assignments. The developed interface helps our hospital partner mitigate personnel shortages by increasing the time dedicated to patient care for nurses freed from the administrative burden of scheduling and assignment planning.

• 
  16h45 - 17h10

  Optimizing Chemotherapy Clinic Pharmacy Operations: A Scheduling Approach for Efficient Medication Preparation

  • Camille Pinçon, prés., Polytechnique Montréal
  • Antoine Legrain, Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal

  The quality of service in a chemotherapy clinic is contingent upon the meticulous preparation of medicines, which must be served in the right quantities and on time. Considering the high hazards and costs associated with chemotherapy drugs, it becomes imperative to optimize their preparation. A scheduling method was therefore developed for the manufacture of drugs in a chemotherapy clinic, aimed at reducing patient waiting times and minimizing preparation costs. This involves the utilization of a linear programming model for scheduling approximation, coupled with a lexicographical approach. The objective is to minimize both the maximum task delay during a production day and the associated costs of raw materials and overall delays. The obtained solution is then reconstructed to explicate the scheduling details and establish a timetable in adherence to clinic constraints. This reconstruction facilitates not only the reduction of delays but also enhances productivity at reduced costs. This scheduling method contributes to a more efficient and cost-effective workflow in chemotherapy clinics, ultimately leading to improved patient care and resource utilization.