Healthcare Systems

Sondes Chaabane is a researcher at the Laboratory of Automation, Mechanics and Industrial and Human Computer Science (LAMIH UMR CNRS 8201) at Université Polytechnique Hauts-de-France and a lecturer at INSA Hauts-de-France. Her research focuses on the control and resilience of complex systems that combine optimization, simulation and artificial intelligence techniques.Etienne Cousein is Head of the Pharmacy Department at the Valenciennes Hospital Center, France, and Vice President of the Commission Médicale d'Établissement. His main research interests include automated distribution solutions and medicine management within electronic patient records.Philippe Wieser is Honorary Professor at EPFL, Switzerland, and Professor at the École des Ponts ParisTech, France. His fields of research are predominantly related to project management, industrial supply chain management and hospital logistics.

• Foreword xiiiAlain GUINETPreface xviiSondès CHAABANEPart 1. Optimization and Simulation of Healthcare Systems 1Summary of Contributions – Part 1 3Chapter 1. Towards a Prototype for the Strategic Recomputing of Schedules in Home Care Services 7Cléa MARTINEZ, Maria DI MASCOLO, Marie-Laure ESPINOUSE and Jérôme RADUREAU1.1. Introduction 71.2. Literature review 81.3. Description of the problem 111.3.1. Constraints 111.3.2. Objective function 131.4. Resolution method 131.4.1. Route generation 131.4.2. Route selection 141.5. Presentation of the prototype 141.6. Tests and results 151.7. Conclusion and perspectives 171.8. References 17Chapter 2. Home Healthcare Scheduling Activities 21Rym BEN BACHOUCH JACQUIN and Jihene TOUNSI2.1. Introduction 212.2. State of the art 212.3. Description of the proposed approach 242.3.1. Home healthcare planning “offline phase” 242.3.2. Rescheduling in online mode 272.4. Experiments and results 282.5. Conclusions and perspectives 302.6. References 30Chapter 3. Optimal Sizing of an Automated Dispensing Cabinet Under Adjacency Constraints 35Khalid HACHEMI, Didier GOURC and François MARMIER3.1. Introduction 353.2. Problem statement 373.2.1. Description of the assignment problem 383.2.2. Notations and definitions 383.3. Mathematical formulation 403.3.1. Determination of boundary conditions 403.3.2. Problem solving approach 423.4. Application example 453.5. Conclusion 473.6. References 47Chapter 4. Validation of an Automated and Targeted Pharmaceutical Analysis Tool at the CHU de Liège 49Sophie STREEL, Nathalie MAES, Véronique GONCETTE, Laurence SEIDEL, Denis MENAGER, Adelin ALBERT, Philippe KOLH and Didier MAESEN4.1. Introduction 494.2. Methods 514.3. Results 534.3.1. Creation of algorithms 534.3.2. IT tool development 534.3.3. Tool validation 564.4. Discussion and conclusion 574.5. References 59Chapter 5. Simulation of Countermeasures in the Face of Covid-19 Using a Linear Compartmental Model 61Alain GUINET5.1. Introduction 615.2. The compartmental model 625.2.1. Model assumptions 625.2.2. Model parameters 635.3. A linear SIR model 645.3.1. Data 645.3.2. Variables 655.3.3. Objective function 655.3.4. Constraints 665.4. Results 685.5. Conclusion 695.6. References 70Part 2. Digital and New Technologies for Health Services 73Summary of Contributions – Part 2 75Chapter 6. Towards a New Classification of Medical Procedures in Belgium 79Pol LECLERCQ, Sarah BARDIAUX, Djohra AZZI, Julie VAN DEN BULCKE and Magali PIRSON6.1. Introduction 796.1.1. An essential but obsolete medical healthcare nomenclature 796.1.2. Decision to initiate a structural reform of the Belgian healthcare nomenclature 806.1.3. The NPS V0 nomenclature in a few figures 816.1.4. Purpose of the presentation 816.2. Methodology 826.2.1. Term analysis and standardization (NPS ATMC V1-1) 846.2.2. Medical pre-validation (NPS ATMC V1-2) 846.2.3. Matching the WHO International Classification of Health Interventions (NPS ATMC V1-3) 866.2.4. Provisional classification of new terms (NPS ATMC V1-3') 896.2.5. INAMI administrative work 916.2.6. Validation of proposals by expert groups (NPS ATMC V1-4) 916.3. Results 936.3.1. Planning 936.3.2. A summary of the modifications between NPS V0 and NSS V1-3 936.3.3. Validation of proposals by experts (NPS ATMC V1-5) 966.4. Discussion 966.4.1. From the standardization of medical procedures to a common descriptive classification 976.4.2. Evaluate the quality for the standardization of medical procedures 996.4.3. An estimate of the resources mobilized to arrive at a common descriptive classification 1006.4.4. Participation of medical experts 1006.4.5. The implementation of common descriptive classification (CC ATMC V1) 1016.5. Conclusion 1036.6. References 103Chapter 7. Digital Toolkit for the Ergonomic Evaluation of Workstations 105Valentin ROCHAT and Antoine HAYEK7.1. Introduction 1057.2. ProcSim and ergonomics 1067.2.1. Origin 1067.2.2. Our product 1067.2.3. Examples of applications in different sectors 1077.2.4. Benefits and value addition 1087.3. Ergonomic assessment process 1087.3.1. Data collection 1087.3.2. Data analysis 1097.3.3. Workstation modeling 1117.3.4. Virtual reality testing of possible activities 1117.3.5. Improvement proposals and recommendations 1117.4. Conclusion 1127.5. References 113Chapter 8. Simulation on an RFID Interactive Tabletop with Tangible Objects of Future Working Conditions: Prospects for Implementation in the Hospital Sector 115Yoann LEBRUN, Nicolas VISPI, Sophie LEPREUX, Sondès CHAABANE and Christophe KOLSKI8.1. Introduction 1158.2. State-of-the-art on the simulation of future working conditions 1168.3. Proposal for a simulator on an interactive tabletop 1178.4. Development of a first version of a simulator on an interactive tabletop 1198.5. Application opportunities in the healthcare industry 1238.6. Conclusion and perspectives in the healthcare industry 1248.7. Acknowledgments 1258.8. References 125Chapter 9. Robotic Geriatric Assistant: A Pilot Assessment in a Real-world Hospital 129Dimitri VOILMY, Karine LAN HING TING, Ana IGLESIAS, Rebeca MARFIL, Juan Pedro BANDERA, Fernando FERNANDEZ and Quitterie DE ROLL9.1. Introduction 1299.2. Geriatric assessment: from needs to the proposed solution 1309.2.1. Data management and the proposed robotic solution 1319.2.2. The Clara robotic geriatric assistant – research 1329.2.3. Hypotheses and research objectives 1349.3. Methodological approach: living lab approach 1349.3.1. Empowerment in and through interaction 1359.3.2. Contribution: new analytical framework 1369.3.3. Mixed methodological approach 1369.4. Pilot assessment 1379.4.1. Procedure and test protocol 1379.4.2. Results 1389.5. Conclusion 1409.6. Acknowledgments 1419.7. References 141Chapter 10. Perspectives on the Patient Experience (PX) of People with Disabilities in the Digital Age: From UX to PX 145Djilali IDOUGHI, Karim TOULOUM, Yohan GUERRIER and Christophe KOLSKI10.1. Introduction 14510.2. State-of-the-art on Patient eXperience (PX) 14610.3. Research methodology and proposal 14910.4. Illustrations relating to the “user research” phase of the methodological framework 15110.5. Case study: digital care journey of a patient with a disability 15310.6. Conclusion 15510.7. References 155Part 3. Change Management and Organizational Innovations 159Summary of Contributions – Part 3 161Chapter 11. Jointly Improving the Experience of All Stakeholders in Hospital 4.0: The ICSSURP Initiative 165Wilson GOUDALO, Christophe KOLSKI and Frédéric VANDERHAEGEN11.1. Introduction 16511.2. Digital transformation to Hospital 4.0 16611.3. Essential qualities of information systems of Hospital 4.0 16711.3.1. Security in information systems of Hospital 4.0 16811.3.2. Usability of information systems of Hospital 4.0 16911.3.3. Resilience of information systems of Hospital 4.0 17011.3.4. Performance of information systems of Hospital 4.0 17111.4. Towards a joint security, safety, usability, resilience and performance engineering initiative (ICSSURP) 17211.4.1. Advanced conceptual model of ICSSURP 17211.4.2. System of homogeneous metrics 17211.4.3. Summary of the ICSSURP initiative 17411.5. Conclusion and perspectives 17411.6. References 175Chapter 12. A Tool-based Approach to Analyze Operating Room Schedule Execution: Application to Online Management 179Leah RIFI, Franck FONTANILI and Michel JEANNEY12.1. Introduction 17912.2. Methodology used to generate our approach 18112.2.1. Preliminary phase: from observation to the approach outline 18112.2.2. Phase 1: design 18112.2.3. Phase 2: build 18212.2.4. Phase 3: test 18212.3. Current version of the proposed tool-based approach 18312.3.1. Presentation of the first tool: the dashboard conceptual model 18312.3.2. Presentation of the second tool: the Logbook 18512.3.3. Description of the current version of the approach 18512.4. Applied example of our tool-based approach at the Centre Hospitalier de Narbonne 18912.4.1. Step 1 – collect and process the data 18912.4.2. Step 2 – evaluate the feasibility and optimality of the initial schedule 19012.4.3. Steps 3 and 4 – study the indicators and their deviations for the operating suite and the operating rooms 19012.4.4. Step 5 – study the indicators and their deviations at the level of the interventions 19112.4.5. Step 6 – determine root causes, impact on the performed schedule and responsibility for deviations 19112.4.6. Step 7 – evaluate the quality of the actions implemented 19212.4.7. Summation 19212.5. Conclusion and perspectives 19212.6. References 193Chapter 13. Planning Patient Journeys in Outpatient Hospitals to Support the Ambulatory Shift 195Virginie FORTINEAU and Lucie ROUSSEL13.1. Introduction 19513.2. Background and state-of-the-art methods 19613.2.1. Planning patient journeys at the hospital 19613.2.2. 4.0 transforming the operational management of hospital flows 19713.2.3. Research problem 19813.3. State-of-the-art and field of application 19813.3.1. Field of application: patient flows in outpatient hospitals 19813.3.2. Little tactical planning for the state of the art 19913.3.3. Choosing a planning and workflow management method 20113.4. Contribution 20213.4.1. Macro-planning for groups of pathways: an S&Op for ambulatory medicine 20213.4.2. Feedback 20413.5. Discussion and perspectives 20513.5.1. Repeatability and accessibility of the macro-planning approach 20513.5.2. Beyond the macro-planning for groups of pathways: towards integrated planning 20513.6. Conclusion 20613.7. References 206Chapter 14. Treatment Protocols Generated by Machine Learning: Putting a Case Study of Hospitalization at Home into Perspective 209Alice MARTIN, Jean-Baptiste GUILLAUME, Alain GUINET and Julien FONDREVELLE14.1. Introduction 20914.2. Context and perspective 21014.2.1. France’s healthcare restructuring and the impact for HaH 21014.2.2. Hospitalization at home and target patients 21014.2.3. The positioning of hospitalization at home versus traditional medicine 21214.2.4. The problems facing hospitalization at home 21314.3. The contribution of protocolization 21414.3.1. A quality tool for the patient and the healthcare provider 21414.3.2. The interface protocol between healthcare facilities 21514.3.3. Protocol facing its limitations 21614.4. Study and proposed methodology 21614.4.1. Case study of the cost drivers of a hospitalization at home 21614.4.2. Patient trajectory forecasting and protocol generation 21914.5. Conclusion 22114.6. References 221Chapter 15. Resilience of Healthcare Teams: Case Study of Two Cardiology Intensive Care Units 223Racha LAMARI15.1. Introduction 22315.2. Theoretical framework 22515.2.1. Defining the concept of resilience within the framework of the study 22515.2.2. Nature of events and situations studied 22615.2.3. The conceptual framework of the study 22615.3. Research methodology 22715.3.1. The narrative of the event 22715.3.2. The data collection 22815.4. Research results 22915.4.1. Identification of stressors 22915.4.2. The resilience process 23115.5. Discussion 23815.6. Conclusion 24215.7. References 242Conclusion and Perspectives 249Sondès CHAABANEGlossary 253List of Authors 259Index 263