Introducing Augmented Reality Technique to Enhance the Preparation Circuit of Injectable Chemotherapy Drugs.

Chemotherapy preparations are often complex and subject to a strict regulatory context. The existing control methods are often limited to Double Visual Control (DVC). In this paper, the preparation circuit of chemotherapy drugs is evaluated through data collection and statistical analysis in order to highlight the difficulties encountered. The results regarding preparation and control times and the number of task interruptions highlight the unreliability of the DVC and its impact on processing time. As a solution, we propose a decision support system "Smart Prep" based on Augmented Reality (AR), co-developed, and commercialized by the Faculty of Pharmacy of Lille, Ecole Centrale de Lille and the company Computer Engineering. This system allows the preparation of chemotherapy drugs according to a step-by-step mode, a traceability of the preparation steps and a reduction of tasks' interruptions.

Impact of the Automation of Inpatient Bed Management to Reduce the Emergency Service Waiting Time.

The patient waiting time to be transferred for hospitalization is the time that the patient waits between the decision to hospitalize and the actual admission to an inpatient hospital bed. One of the difficulties encountered in qualifying waiting time for inpatient bed is the inability of hospital information systems to measure it. Hospitals in France have a specialized bed allocation team. This team must manage the bed allocation problem between different hospital departments using phone communication to assign patients to the adapted service. This kind of communication represents a lengthy additional workload in which effectiveness is uncertain. This paper presents a new approach to automate bed management in downstream service. For that, we have implemented algorithms based on artificial intelligent integrated in an inpatient web platform using IoT-Beacons, which is implemented to improve and facilitate the exchange of availability information of downstream beds within the Lille university hospital center (LUHC).

A multivalued agent-based model for the study of noncommunicable diseases.

This paper aims to test and illustrate the utility and extensibility of an existing model, SimNCD (Simulation of NonCommunicable Diseases). It also proposes a way to include questionnaires - widely used in epidemiology - in the individual's reasoning mechanism in order to identify his/her attitude and personal choices. SimNCD is a formal agent-based model. It helps researchers and health practitioners study and simulate the complex dynamics of noncommunicable diseases. It models individuals that evolve within a social network, and behave while engaging in activities offered by their physical environment. The literature strongly supports the influence of the individual's behavioral choices on their health, particularly, the acquirement and maintainability of noncommunicable diseases. Therefore, we propose to extend SimNCD in order to acquire the agents with a reasoning process that allows them to choose the activities to practice. Thus, we model their attitude via preferences that are modeled based on the available literature and expressed with the linguistic 2-tuple method. Our solution also employs a multi-attribute decision-making method. We specify the proposed solution in the study of childhood obesity and use it to predict children's corpulence variations in different scenarios.

An Innovative Approach to Jointly Scheduling and Assigning a Consultation Time to Patients Arriving in the Emergency Department.

Emergency departments (ED) are facing problems related to the growing demand of care. Patients' management is carried out according to the type of patient and care required: already scheduled patients and non-scheduled urgent and non-urgent patients arriving in the ED. One of the main problems confronted in hospitals is the permanent interference between these different types of patients to be treated under the stochastic behaviors of consultation time and arrival flows, which prevents any prior planning. The present work proposes a dynamic scheduling method, considering the impact of new patients' arrivals on the treatment of patients already scheduled to minimize the mean waiting time of patients in the ED. The originality of this work is to assign, at the time of arrival, a scheduled time to each patient in order to reduce their stress. The performance of the proposed method is examined through a concrete application in the Pediatric Emergency Department of CHRU of Lille.

Agents endowed with uncertainty management behaviors to solve a multiskill healthcare task scheduling.

Health organizations are complex to manage due to their dynamic processes and distributed hospital organization. It is therefore necessary for healthcare institutions to focus on this issue to deal with patients' requirements. We aim in this paper to develop and implement a management decision support system (DSS) that can help physicians to better manage their organization and anticipate the feature of overcrowding. Our objective is to optimize the Pediatric Emergency Department (PED) functioning characterized by stochastic arrivals of patients leading to its services overload. Human resources allocation presents additional complexity related to their different levels of skills and uncertain availability dates. So, we propose a new approach for multi-healthcare task scheduling based on a dynamic multi-agent system. Decisions about assignment and scheduling are the result of a cooperation and negotiation between agents with different behaviors. We therefore define the actors involved in the agents' coalition to manage uncertainties related to the scheduling problem and we detail their behaviors. Agents have the same goal, which is to enhance care quality and minimize long waiting times while respecting degrees of emergency. Different visits to the PED services and regular meetings with the medical staff allowed us to model the PED architecture and identify the characteristics and different roles of the healthcare providers and the diverse aspects of the PED activities. Our approach is integrated in a DSS for the management of the Regional University Hospital Center (RUHC) of Lille (France). Our survey is included in the French National Research Agency (ANR) project HOST (Hôpital: Optimisation, Simulation et évitement des Tensions (ANR-11-TecSan-010: http://host.ec-lille.fr/wp-content/themes/twentyeleven/docsANR/R0/HOST-WP0.pdf)).

Multi-agent Architecture for the Multi-Skill Tasks Modeling at the Pediatric Emergency Department.

Patient journey in the Pediatric Emergency Department is a highly complex process. Current approaches for modeling are insufficient because they either focus only on the single ancillary units, or therefore do not consider the entire treatment process of the patients, or they do not account for the dynamics of the patient journey modeling. Therefore, we propose an agent based approach in which patients and emergency department human resources are represented as autonomous agents who are able to react flexible to changes and disturbances through pro-activeness and reactiveness. The main aim of this paper is to present the overall design of the proposed multi-agent system, emphasizing its architecture and the behavior of each agent of the model. Besides, we describe inter-agent communication based on the agent interaction protocol to ensure cooperation between agents when they perform the coordination of tasks for the users. This work is integrated into the ANR HOST project (ANR-11-TecSan-010).

Mapping patient path in the Pediatric Emergency Department: A workflow model driven approach.

The workflow models of the patient journey in a Pediatric Emergency Department (PED) seems to be an effective approach to develop an accurate and complete representation of the PED processes. This model can drive the collection of comprehensive quantitative and qualitative service delivery and patient treatment data as an evidence base for the PED service planning. Our objective in this study is to identify crowded situation indicators and bottlenecks that contribute to over-crowding. The greatest source of delay in patient flow is the waiting time from the health care request, and especially the bed request to exit from the PED for hospital admission. It represented 70% of the time that these patients occupied in the PED waiting rooms. The use of real data to construct the workflow model of the patient path is effective in identifying sources of delay in patient flow, and aspects of the PED activity that could be improved. The development of this model was based on accurate visits made in the PED of the Regional University Hospital Center (CHRU) of Lille (France). This modeling, which has to represent most faithfully possible the reality of the PED of CHRU of Lille, is necessary. It must be detailed enough to produce an analysis allowing to identify the dysfunctions of the PED and also to propose and to estimate prevention indicators of crowded situations. Our survey is integrated into the French National Research Agency (ANR) project, titled: "Hospital: Optimization, Simulation and avoidance of strain" (HOST).

A workflow model to analyse pediatric emergency overcrowding.

The greatest source of delay in patient flow is the waiting time from the health care request, and especially the bed request to exit from the Pediatric Emergency Department (PED) for hospital admission. It represents 70% of the time that these patients occupied in the PED waiting rooms. Our objective in this study is to identify tension indicators and bottlenecks that contribute to overcrowding. Patient flow mapping through the PED was carried out in a continuous 2 years period from January 2011 to December 2012. Our method is to use the collected real data, basing on accurate visits made in the PED of the Regional University Hospital Center (CHRU) of Lille (France), in order to construct an accurate and complete representation of the PED processes. The result of this representation is a Workflow model of the patient journey in the PED representing most faithfully possible the reality of the PED of CHRU of Lille. This model allowed us to identify sources of delay in patient flow and aspects of the PED activity that could be improved. It must be enough retailed to produce an analysis allowing to identify the dysfunctions of the PED and also to propose and to estimate prevention indicators of tensions. Our survey is integrated into the French National Research Agency project, titled: "Hospital: optimization, simulation and avoidance of strain" (ANR HOST).