Implementation strategies of a contract-based MRI examination reservation process for stroke patients

International audienceTimely imaging examinations are critical for stroke patients due to the potential life threat. We have proposed a contract-based Magnetic Resonance Imaging (MRI) reservation process [1] in order to reduce their waiting time for MRI examinations. Contracted time slots (CTS) are especially reserved for Neural Vascular Department (NVD) treating stroke patients. Patients either wait in a CTS queue for such time slots or are directed to Regular Time Slot (RTS) reservation. This strategy creates "unlucky" patients having to wait for lengthy RTS reservation. This paper proposes and analyzes other contract implementation strategies called RTS reservation strategies. These strategies reserve RTS for NVD but do not direct patients to regular reservations. Patients all wait in the same queue and are served by either CTS or RTS on a FIFO (First In First Out) basis. We prove that RTS reservation strategies are able to reduce the unused time slots and patient waiting time. Extensive numerical results are presented to show the benefits of RTS reservation and to compare various RTS reservation strategies

A Monte Carlo Optimization and Dynamic Programming Approach for Managing MRI Examinations of Stroke Patients

International audienceQuick diagnosis is critical to stroke patients, but it relies on expensive and heavily used imaging equipment. This results in long waiting times with potential threats to the patient's life. It is important for neurovascular departments treating stroke patients to reduce waiting times for diagnosis. This paper proposes a reservation process of magnetic resonance imaging (MRI) examinations for stroke patients. The neurovascular department reserves a certain number of appropriately distributed contracted time slots (CTS) to ensure quick diagnosis of stroke patients. Additional MRI time slots can also be reserved by regular reservations (RTS). The problem consists in determining the contract and the control policy to assign patients to either CTS or RTS in order to reach the best compromise between the waiting times and unused CTS. Structural properties of the optimal control policy are proved by an average-cost Markov decision process (MDP) approach. The contract is determined by combining a Monte Carlo approximation approach and local search. Extensive numerical experiments are performed to show the efficiency of the proposed approach and to investigate the impact of different parameters