Journées de l'optimisation 2017

HEC Montréal, 8-10 mai 2017

1er Atelier Canadien sur l'optimisation des soins de santé (CHOW)

HEC Montréal, 10-11 mai 2017

JOPT2017

HEC Montréal, 8 — 11 mai 2017

Horaire Auteurs Mon horaire

TB8 Ordonnancement en santé / Scheduling in Healthcare

9 mai 2017 10h30 – 12h10

Salle: TAL Gestion globale d'actifs inc.

Présidée par Dina Ben Tayeb

3 présentations

  • 10h30 - 10h55

    Chemotherapy Outpatient Scheduling Problem - A Practical Case

    • Menel Benzaid, prés., Polytechnique
    • Nadia Lahrichi, Polytechnique Montréal
    • Louis-Martin Rousseau, Polytechnique Montréal

    In this project, we study the practical case of the Outpatient Oncology Center of Notre-Dame Hospital in Montreal. Observations have been made to extricate which elements of the real process (cyclic nature of treatment plans, variability in resource requirements, patient characteristics, uncertainty due to cancellations, arrival time, add-ons, treatments duration, staff satisfaction, overtime) need to be integrated in a mathematical model which includes workload features to solve the Chemotherapy Scheduling Problem. We focus on determining the best scheduling for patients in order to allow chemotherapy caregivers to add extra capacity without compromising on staff satisfaction, and on the quality of care offered.

  • 10h55 - 11h20

    Modeling and optimization of patient flows in radiotherapy centers

    • Yosra El Abed, prés., Polytechnique Montréal
    • Nadia Lahrichi, Polytechnique Montréal
    • Louis-Martin Rousseau, Polytechnique Montréal

    The objective of this work is to develop a flexible simulation platform that model several trajectories of patients in a radiotherapy center. Their interactions with resources are detailed and all processes are described. We aim to evaluate several organisation strategies: booking of patients, scheduling of resources and prioritization of tasks.

  • 11h20 - 11h45

    Patient classification for appointment scheduling in ambulatory clinics

    • Dina Ben Tayeb, prés., Polytechnique Montréal
    • Nadia Lahrichi, Polytechnique Montréal
    • Louis-Martin Rousseau, Polytechnique Montréal

    The main objective of this work is to design a patient scheduling algorithm for a radiotherapy center. In this project, we use machine learning techniques to estimate the time required to complete each treatment and possibly to classify patients. The objective is to maximize the number of patients served per day, i.e improve patient access to healthcare.

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