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Covid-19, which first appeared in Wuhan, spread worldwide. In Europe, Italy and Spain were the first to be hit, before the entire continent was. This health crisis has affected the whole world and at all levels (hospital capacity, number of health workers, shortage of medicines, ...). With 5,318,216 deaths worldwide as of December 16, 2021, the disease has shown that the health-care system is not sufficiently prepared to cope with the coronavirus.
COVID 19, like any other disease, requires a follow-up of its evolution to reduce its harmful effects. In order to ensure the comfort to the patients by offering them a care path adapted to their situation, the exploitation of artificial intelligence within the hospital is necessary and this by approaching the human cognition in the analysis of complex medical data.
The objective of this study is to generate the patient's care pathway from his initial state at the first consultation with the physician.
To do this, we will have to optimize the hospital supply chain by modeling the patient's care pathway.
First, we will proceed by identifying all the entities contributing to the hospital logistics chain.
Then, the supply chain will be optimized thanks to the use of lean to deliver to the patient what he needs when he needs it to accomplish its care.
Finally, the Multi Agents method will be used to model all the parts concerning the course of the treatment (radiology, surgery, pharmacy, accounting, ...) and to show the interactions that can take place to make them as effective as possible.