Despite major investments in healthcare, access to front line health services (family doctors, walk-in clinics) is still difficult. If front line healthcare services remain insufficient, emergency departments will have to offer non-urgent patients appropriate services. More than half of emergency patients are ambulatory patients and their medical condition is not usually as serious as for patients on stretchers (Thibeault, 2014 Thibeault, J . (2014). Le «vrai» temps d’attente moyen aux urgences est de 4 heures, Ici Radio-Canada, Consulté le 11 février 2016, Tiré de: http://ici.radiocanada.ca/nouvelles/societe/2014/06/11/009-temps-attente-urgences-hopitaux-quebec-patients-ambulatoires-quatre-heures.shtml [Google Scholar] ). This paper is devoted to the analysis of ambulatory patient length of stay in an emergency department of a hospital in the province of Quebec. The average length of stay for ambulatory patients in that hospital is slightly more than 7 hours which exceeds the average 4 hours observed for all emergency departments in Quebec. To identify the factors and their interactions affecting the performance of the hospital emergency, measured by the average length of stay for ambulatory patients, experimental design and discrete-event simulation were used. This research aims at verifying how nurses can contribute to reduce emergency department overcrowding. Our results show that giving more responsibility to nurses (collective prescriptions, review patients) reduce greatly the average patient length of stay with less financial effort than adding new doctors. This allows doctors to focus on the more acute patients.

Small and medium enterprises (SME) face various challenges in order to remain competitive in a global market. Industry 4.0 (I4.0) is increasingly presented as the new paradigm for improving productivity, ensuring economic growth, and guaranteeing the sustainability of manufacturing companies. However, SMEs are ill equipped and lack resources to undertake this digital shift. This paper presents the digital shift process of an SME in a personalized mass production context. Our work provides a better understanding of the interaction between Lean and I4.0. It contributes to the development of Lean 4.0 implementation strategies that are better adapted to manufacturing SMEs in a personalized mass production context. We also demonstrate the usefulness of simulation as a decision-making assistance tool when implementing I4.0. A practical case is documented to fill a gap in the scientific literature identified by several researchers.

Due to the increasing number of cases of cancer, medical clinics specialized in cancer treatments must operate differently to meet demand. Besides growth in demand, research on cancer treatment has led to more complex chemotherapy protocols. The literature lists more than 170 chemotherapy protocols. However, in practice only a few are administered. In oncology, nurse-patients ratios and the treatment protocol to administer have an impact on nurse workload. The nurse-patients ratio is usually one nurse for four patients (1:4); meaning that the nurse administers treatments to four patients simultaneously. Delivering a chemotherapy treatment requires that the nurse performs different tasks according to the protocol. This research studies nurse workload related to the administration of chemotherapy treatments. Both physical and mental nurse workload are studied. We present an original quantitative approach based on discrete event simulation to measure nurse workload. It demonstrates that all protocols do not result in similar workloads. Our study shows that both physical and mental nurse workload should be taken into account in determining the nurse-patient ratio for the administration of chemotherapy treatment.

Our study is performed in a hematology-oncology clinic in Québec. This clinic experienced a 20% increase for hematology treatments and a 131% increase for oncology treatments. Clinic managers and personnel felt that this increase led to higher patient waiting time and personnel workload. Clinic managers decided to examine the possibility of adding resources to alleviate nurse workload. Patient trajectories and lead times, appointment scheduling and nurse workload are analyzed with a discrete-event simulation model. It is shown that patient waiting time is not too long. A nurse overload problem is observed with a nurse occupancy rate of 86.98% in the morning and 64.48% in the afternoon. New schedule appointments taking into account nurse capacity are proposed. These result in a decrease of the difference in nurse occupancy rates in the morning and in the afternoon.