Healthcare Systems. Группа авторов
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Healthcare institutions will evolve towards becoming more innovative institutions by pursuing defined paths that consider risk factors and the collective and individual context of patients. They will take advantage of information technologies, scientific methods and mass data to prevent, anticipate, monitor and follow developments in public health, in order to intervene at the right time with the right tools. They will focus on people, be it the patient, the citizen or the caregivers by providing a high-performance health environment that meets safety, quality and productivity requirements.
The theme of this book centers around the engineering and management of healthcare and healthcare institutions, with the aim of making them agile and integrated into their environments. The book thus deals with the “hospital” system and the path to good health: issues, prevention approaches, data/IT, organizational innovations and recent technological solutions. It also opens up new opportunities for improving hospital systems with advances in artificial intelligence, information systems and service robotics.
The current context of the Covid-19 pandemic that we have been experiencing since early 2020 has only confirmed this need for openness, modernization and innovation in our healthcare systems. This crisis has shown us that we are vulnerable, that everyone is affected by these public health issues and that these can only be resolved through a collective and global effort. So, one wonders, what is the role of the hospital? Does it wait for a request for care? It is clear that the hospital cannot take care of everything and yet it should pay attention to everything. Our motivation for this book is to present scientific work that will allow our hospitals to evolve into innovative hospitals, open to their environment and efficient where health is concerned, not only to deliver care but also allowing citizens to prevent diseases and put their health at the heart of their priorities.
This book is presented in three different parts, each composed of five chapters that have been written by health professionals, researchers in science and technology, as well as in the human and social sciences from different Frenchspeaking countries. The first part presents the various works that have been addressed optimization and simulation in healthcare systems. This research shows the potential and the opportunities offered by these techniques to support institutions in their management and organization of care methods. The second part focuses on digital and electronic technologies with an emphasis on artificial intelligence methods, allowing for the intelligent use of data or even robotization in the integration of technologies our healthcare offers, the working conditions of our caregivers or the assistance being afforded to fragile and vulnerable people. These first two parts highlight opportunities for innovative organizations and better management, as well as the threats related to changes in the daily life and practices of our institutions. The third part of the book therefore responds to the problems of change management and the impacts on our practices, our organizations and our management methods.
Sondès Chaabane
October 2021
Summary of Contributions – Part 1
Towards a Prototype for the Strategic Recomputing of Schedules in Home Care Services, by Cléa MARTINEZ, Maria DI MASCOLO, Marie-Laure ESPINOUSE and Jérôme RADUREAU.
Home care is an alternative to traditional hospitalization to cope with aging populations and the increase in the number of vulnerable people whilst ensuring a good quality of life for patients. Even though these structures are developing more and more, the planning of their activities remains manual and can be time-consuming and exceedingly complex on a large scale. It is therefore essential to have effective solutions for planning interventions with an update mechanism to compensate for unforeseen events. This contribution therefore offers a decision support tool to solve the problem of long-term re-scheduling in the home care sector. A weekly planning update prototype was developed to meet a need expressed by a home care company operating in Auvergne Rhône-Alpes: Adomni-Quemera.
Home Healthcare Scheduling Activities, by Rym BEN BACHOUCH JACQUIN and Jihene TOUNSI.
This chapter examines the problem of planning rounds in hospitalization at home (HaH) by taking into account uncertainties and integrating dynamic re-scheduling. The authors propose an approach based on a genetic algorithm which considers re-scheduling in real time to resolve any conflicts that may arise as a result of unforeseen disruptions which may occur. This approach takes place in two phases. The first phase is carried out “offline”, making it possible to establish the schedules of the nursing staff. The second phase is “online”, making it possible to manage unforeseen events in real time, such as the absence of staff and delays in care. In the disrupted context, a new schedule is generated in order to cope with the disruption. The results obtained show the efficiency and robustness of the proposed approach with rapid computation time.
Optimal Sizing of an Automated Dispensing Cabinet under Adjacency Constraints, by Khalid HACHEMI, Didier GOURC and François MARMIER.
This contribution focuses on the dispensing phase of the medication circuit. This phase corresponds to the validation of the prescription, preparation and delivery of the medication. The main objective of the study is to minimize the errors that occur during this phase and, more specifically, in the case of automated dispensation cabinets. Such errors can occur when the cabinet is filled with the wrong product in the wrong place resulting in the wrong medication being delivered to the patient. To resolve this problem, the authors propose an algebraic model for the calculation of boundary conditions necessary for the allocation of medications to different compartments of a cabinet. This method must ensure that certain products are not placed in neighboring compartments due to the risk of confusion, which may lead to distribution errors, for example, medicinal products having a similar appearance, nomenclature or dosage. A modeling of the maximum permissive target problem (MPTP) has been proposed, as well as its resolution through a real-world digital application.
Validation of an Automated and Targeted Pharmaceutical Analysis Tool at the CHU de Liège, by Sophie STREEL, Nathalie MAES, Véronique GONCETTE, Laurence SEIDEL, Denis MENAGER, Adelin ALBERT, Philippe KOLH and Didier MAESEN.
This next contribution also looks at the medication flow, which can be a major challenge for a hospital. This flow is a complex and multidisciplinary process, which includes the clinical pathways (prescription, distribution, administration) and logistics (supply, transport, storage). The computerization of the medication flow at the “CHU de Liège” is widely implemented. This study describes how an automated and targeted pharmaceutical analysis tool was built, implemented and evaluated at the “CHU de Liège”. The objective of this tool is to provide reliable and solid support to pharmacists for the verification of prescriptions so as to optimize and meet the hospital’s accreditation criteria. Various pharmaceutical validation algorithms were thus constructed, and the computer validation tool was developed and tested on these bases which generated very encouraging results.
Simulation of Countermeasures in the Face of Covid-19 Using a Linear Compartmental Model, by Alain GUINET.
Since the start of 2020, the whole world has been confronted by a pandemic, which led to the confinement of over half of the world’s inhabitants. We are disarmed in the face of the coronavirus (SARS-CoV-2), and containment seems to be the only countermeasure capable of containing the pandemic despite the consequential economic cost. This chapter presents a simulation of the epidemic based on the SIR (Susceptible–Infected–Recovered) model, which is known as a compartmental model in epidemiology. This simulation makes it possible to calculate,