Organisation et planification de la main-d'oeuvre : applications en santé et en industrie

Revue de la littérature sur l'organisation et la planification de la main-d'oeuvre -- Analysis of a territorial approach to the delivery of nursing home care services based on historical data -- A patient assignment algorithm for home care services -- A flexible milp model multiple-shift workforce planning under annualized hours112

Agent-based simulation patient model for colon and colorectal cancer care trajectory

ABSTRACT: Colon and Colorectal cancer are a diagnosis of particular concern for older Canadians. They are the second cancer in terms of rate of incidence and mortality among Canadians after lung cancer. Treatment of colon and colorectal cancer requires a complex decision-making process of treatment. These treatments may involve surgery and either pre- or post-operative radiation or chemotherapy, which can have a great impact on the quality of life of patients due to the rigorous requirements of treatment and the inconvenient side effects. This paper is the first developmental step of an agent-based simulation platform aiming at simulating colon and colorectal cancer patient care trajectories in a hospital. In this study, we describe a virtual patient agent, which includes a cancer evolution model, capable of replicating cancer behavior in response to treatment. Simulation results show promising interpolation results with respect to chemotherapy dosage and radiotherapy dosage. However, the model ability to interpolate different administration protocols is still limited, and therefore require calibration for each protocol

Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

ABSTRACT: Testing is critical to mitigating the COVID-19 pandemic, but testing capacity has fallen short of the need in the United States and elsewhere, and long wait times have impeded rapid isolation of cases. Operational challenges such as supply problems and personnel shortages have led to these bottlenecks and inhibited the scale-up of testing to needed levels. This paper uses operational simulations to facilitate rapid scale-up of testing capacity during this public health emergency. Specifically, discrete event simulation models were developed to represent the RT-PCR testing process in a large University of Maryland testing center, which retrofitted high-throughput molecular testing capacity to meet pandemic demands in a partnership with the State of Maryland. The simulation models support analyses that identify process steps which create bottlenecks, and evaluate “what-if” scenarios for process changes that could expand testing capacity. This enables virtual experimentation to understand the trade-offs associated with different interventions that increase testing capacity, allowing the identification of solutions that have high leverage at a feasible and acceptable cost. For example, using a virucidal collection medium which enables safe discarding of swabs at the point of collection removed a time-consuming “deswabbing” step (a primary bottleneck in this laboratory) and nearly doubled the testing capacity. The models are also used to estimate the impact of demand variability on laboratory performance and the minimum equipment and personnel required to meet various target capacities, assisting in scale-up for any laboratories following the same process steps. In sum, the results demonstrate that by using simulation modeling of the operations of SARS-CoV-2 RT-PCR testing, preparedness planners are able to identify high-leverage process changes to increase testing capacity

Patient model for colon and colorectal cancer care trajectory simulation

Almost half Canadians (41% women and 46% men) will develop cancer during their lifetime and 88% of them are older than fifty [1]. Lung, breast, colon, colorectal and prostate cancers represent more than half of all new cancer cases (52%). Breast cancer is the leading type of cancer among women, while colon and colorectal cancer are the third most common cancer among men and women. Cancer is the leading cause of death in Canada and in the world with 29.8% of the population affected, compared to 26.6% for cardiovascular diseases [2]. Furthermore, in 2000, cancer was the fourth most expensive disease in Canada with $17.4 billion spent. Colon and Colorectal cancer are considered the second leading cause of cancer death among men and the third among women. Cancer treatment is characterized by the convergence of many services including ambulatory, hospitals, clinical, nutritional, psychological, and sports medicine, which coordination and integration condition treatment success and patient quality of life. In order to reduce the impact of this disease and increase the cure rate and the patient quality of life, it is necessary to develop and evaluate new therapeutic and organizational approaches. This study deals with this goal and is the first methodological step toward creating a simulation platform of care trajectories of colorectal cancer patients. This simulation platform aims at simulating many elements of the hospital environment, from care resources to patient physiology and psychology profiles, in order to evaluate the many impacts of organizational changes of care trajectories. First, this paper describes the general scope of this simulation project and presents a state of the art of agentbased simulation. Next, the general conceptual model of the simulation is described. Then, we present our cancer evolution, which is then tested and validated using two separate experiments

Planning for resilience in screening operations using discrete event simulation modeling: example of HPV testing in Peru

ABSTRACT: Background: The World Health Organization (WHO) has called for the elimination of cervical cancer. Unfortunately, the implementation of cost-effective prevention and control strategies has faced significant barriers, such as insufficient guidance on best practices for resource and operations planning. Therefore, we demonstrate the value of discrete event simulation (DES) in implementation science research and practice, particularly to support the programmatic and operational planning for sustainable and resilient delivery of healthcare interventions. Our specific example shows how DES models can inform planning for scale-up and resilient operations of a new HPV-based screen and treat program in Iquitos, an Amazonian city of Peru. Methods: Using data from a time and motion study and cervical cancer screening registry from Iquitos, Peru, we developed a DES model to conduct virtual experimentation with “what-if” scenarios that compare different workflow and processing strategies under resource constraints and disruptions to the screening system. Results: Our simulations show how much the screening system’s capacity can be increased at current resource levels, how much variability in service times can be tolerated, and the extent of resilience to disruptions such as curtailed resources. The simulations also identify the resources that would be required to scale up for larger target populations or increased resilience to disruptions, illustrating the key tradeoff between resilience and efficiency. Thus, our results demonstrate how DES models can inform specific resourcing decisions but can also highlight important tradeoffs and suggest general “rules” for resource and operational planning. Conclusions: Multilevel planning and implementation challenges are not unique to sustainable adoption of cervical cancer screening programs but represent common barriers to the successful scale-up of many preventative health interventions worldwide. DES represents a broadly applicable tool to address complex implementation challenges identified at the national, regional, and local levels across settings and health interventions—how to make effective and efficient operational and resourcing decisions to support program adaptation to local constraints and demands so that they are resilient to changing demands and more likely to be maintained with fidelity over time

Etude de la production resonante de graviton de Kaluza-Klein dans ses desintegrations en paires de muons dans le modele de Ramdall-Sundrum aupres de l'experience D0 au Tevatron

In this thesis we have put the first constraints on the fundamental parameters of the Randall-Sundrum model of extra dimensions, k/M_Pl which is proportional to the coupling of the graviton to the standard model fields and M$_G$ which is the mass of the first excited state of the Kaluza-Klein graviton. The analysis performed on Monte carlo sample of the signal allowed to find an error in the PYTHIA generator. The elaboration of an independent generator dedicated for this special analysis helped to find out and correct the error. The data sample used for the analysis covers the period running from november 2002 up to july 2003 taken by the Dzero collaboration at Tevatron, which corresponds to an accumulated luminosity of 107,8 pb-1. The search for the graviton in the dimuon channel allowed to measure the Z production cross-section times the branching ratio in dimuons.Dans cette thèse nous avons posé les premières contraintes sur les paramètres du modèle de dimensions supplémentaires de Randall-Sundrum, à savoir k/M_Pl qui est proportionnel au couplage du graviton aux champs du modèle standard et M_G qui est la masse du premier état excité du graviton. L'analyse du signal Monte Carlo est basée sur le générateur PYTHIA. Cette étude a permis de mettre en évidence et de rectifier une erreur dans le générateur PYTHIA grâce à l'élaboration d'un générateur indépendant dédié à cette analyse. Le lot de données utilisées pour l'analyse correspond à la période de prise des données effectuée par la collaboration Dzero au Tevatron allant de novembre 2002 à juillet 2003, qui correspond à une luminosité totale de 107,8 pb-1. La recherche du graviton dans ses désintégrations en paires de muons a permis de mesurer dans un premier temps la section efficace de production du boson Z multiplié par le rapport d'embranchement du Z en deux muons