Viviane Gascon

Generalized Assignment Type Goal Programming Problem: Application to Nurse Scheduling

The notion of the Generalized Assignment Type Goal Programming Problem is introduced to consider the additional side constraints of an Assignment Type problem as goal functions. A short term Tabu Search method together with diversification strategies are used to deal with this model. The methods are tested on real-world Nurse Scheduling Problems.

Use of a discrete-event simulation in a Kaizen event: A case study in healthcare

To improve service delivery, healthcare facilities look toward operations research techniques, discrete event simulation and continuous improvement approaches such as Lean manufacturing. Lean management often includes a Kaizen event to facilitate the acceptance of the project by the employees. Business game is also used as a tool to increase understanding of Lean management concepts. In this paper, we study how a business game can be used jointly with discrete event simulation to test scenarios defined by team members during a Kaizen event. The aim is to allow a rapid and successful implementation of the solutions developed during the Kaizen. Our approach has been used to improve patients’ trajectory in an outpatient hematology–oncology clinic. Patient delays before receiving their treatment were reduced by 74 percent after 19 weeks.

Mathematical programming approach for routing home care nurses

Nowadays more patients need to receive medical treatments at home. Sequencing home care nurses visits shows similarities with the multiple vehicle routing problem with time windows (MVRPTW). Additional constraints make this problem much more complex. These refer to medical requirements and to the importance of continuity of care. In this paper, we present a mathematical model describing the problem of determining routes for home care nurses which takes into account constraints from the MVRPTW along with medical and continuity of care constraints. We also provide some numerical results.

Scheduling the flying squad nurses of a hospital using a multi-objective programming model

In this paper, we address the problem of scheduling nurses working on the flying squad of a hospital. Considering the large number of constraints, many of them being conflicting, the problem is formulated as a multi-objective programming problem with binary variables, where the objective function consists of a vector of objectives and penalty variables (deviation measures) provided by the soft constraints. Two approaches are considered to solve the problem: the weighted method and the sequential method. The best results are obtained with a mix of the two solving methods. Numerical results are presented.

Design and analysis of an outpatient orthopaedic clinic performance with discrete event simulation and design of experiments

This paper evaluates different patient flows (one, two or three-step trajectories).Our model is a more realistic representation than theoretical queuing models.The model shows that 2 exam rooms instead of 3 can be used for all patient flows.Modifying appointment scheduling rules reduces significantly patient lead time.Appointment scheduling rules must be determined according to patient flow types. Considering that demand for healthcare services is constantly increasing, outpatient services must improve their performance. Being able to satisfy the demand with a limited outpatient service capacity is an important operational challenge. The objective of our research consists in studying the relationships and interactions between patient flows, resource capacity (number of consulting rooms and number of nurses) and appointment scheduling rules in order to improve an outpatient orthopaedic clinic performance. Discrete event simulation is used to model outpatient flows. An experimental design was developed to test how to assign consulting rooms and nurses to each orthopedist considering four appointment scheduling rules and three patient flow types of varied complexity. Analysis of variance and the Tukey test are used to evaluate the simulation results. Our conclusion is that in order to improve the outpatient orthopaedic clinic performance, resources (consulting rooms, nurses) and appointment scheduling rules must be adapted to the different patient flows.

The importance of considering resource’s tasks when modeling healthcare services with discrete-event simulation: an approach using work sampling method

Discrete event simulation (DES) is increasingly used to model and analyse healthcare systems processes. Unlike the manufacturing industry, healthcare personnel benefits from a professional independence allowing them to choose the next task to accomplish. Because of this characteristic modelling healthcare systems with DES is more complex. This paper introduces a work sampling method to model nurses’ direct and indirect tasks in a haematology-oncology clinic. We show how this method helps to obtain a more realistic DES model.

Heuristics to solve appointment scheduling in chemotherapy

This paper studies meta-heuristic methods in solving an appointment-scheduling problem in a hospital in Canada. Our paper proposes a two-step algorithm: The first step creates an initial solution with a Greedy Algorithm considering many strategies. The second step consists in choosing the best strategy and improving it with Tabu Search. Our algorithm performed well for the appointment-scheduling problem. The data used was collected from a hematology-oncology department in a hospital. It includes information about patients, nurses, treatments and fixed appointments. Patients must be assigned to nurses with specific treatment seats. We focus on 3 main objectives: maximize the number of patients scheduled over a planning horizon, minimize overtime and provide a more balanced workload between nurses. Our algorithm succeeds in scheduling more patients over a planning horizon without overtime and with a better balanced workload between nurses.

Heuristics to Solve a Real-world Asymmetric Vehicle Routing Problem with Side Constraints

To maintain patients at home as most as possible, healthcare services are nowadays quite diversified. We present the case of a public medical clinic offering activities, mostly to the elderly, at a daycare center. Users are brought into the daycare center by bus or by taxi. The global problem consists in defining routes to pick up users while assigning them to time slots in the week. At first sight this problem could be viewed as an asymmetric multiple vehicle routing problem. However many additional constraints must be considered. In this paper, we propose a metaheuristic including two phases to solve the problem. In the first phase, the initial solution is determined using one of two proposed constructed algorithms and is improved using tabu search in the second phase. These algorithms are tested on 10 problem instances. Experimental results are presented.

Iterated local search in nurse rostering problem

This paper presents how to solve a nurse rostering problem over the real datasets of Centre hospitalier régional de Trois-Rivières hospital in Canada. Due to the complexity of this problem with plenty of hard constraints, we propose an advanced Iterated Local Search, combining Tabu Search with 2 moves: Single Shift Move and Worst-Scheduled Nurse Swap. Greedy Shuffling with Steepest Descent is also used to improve the solution. Experimental results of our proposed algorithm on 5 real datasets improve the current schedules provided by the hospital. Our experimental results satisfy all of the hard constraints and objectives.

Apport de la simulation à l’amélioration de la performance d’une unité de prélèvements d’un centre hospitalier régional

Traditionnellement utilisée dans le secteur manufacturier, la simulation informatique est mise à contribution pour analyser le fonctionnement de l’unité de prélèvements sanguins du Centre hospitalier régional de Trois-Rivières. Après une collecte de données, le fonctionnement de l’unité a été modélisé afin de reproduire les opérations dans leur forme initiale et de tester différents scénarios d’amélioration de la performance. Un de ces scénarios a été recommandé à la direction qui l’a implanté au printemps 20111. Après 9 mois, les résultats prévus sont au rendez-vous. L’expérience a été jugée des plus positives par les gestionnaires et par les participants au projet.