A Cooperative Hospital Network Digital Twin for the Management of Non-Elective Surgery Care Pathways
Project Lead: Oualid Jouini
Coordinating institution: CentraleSupélec
Care pathways, digital twins, health territory, artificial intelligence, hospital cooperation, health economics optimization, emergency surgical care, exceptional health situations, large-scale data
NETSURG addresses the increasing pressure on healthcare systems due to the scarcity of financial and human resources in hospitals, combined with a growing number of patients requiring emergency surgery. Emergency operating rooms are particularly costly, representing 20-40% of hospital expenses, and suffer from inefficiencies in resource management, leading to extended waiting times, increased intra-hospital mortality, longer patient stays, and higher costs. Given this context, NETSURG aims to optimize the management of emergency surgery care pathways by leveraging innovative technologies such as digital twins, data-driven optimization models, and hospital cooperation mechanisms. By improving the efficiency of emergency surgical care, the project seeks to enhance patient outcomes while reducing operational inefficiencies.
NETSURG is an interdisciplinary project with the primary goal of developing a multi-scale digital twin for managing emergency surgery care pathways across a hospital network. This starts from the patient arrival (to the emergency department, hospital wards, etc.) to their discharge from the hospital. Using data from the French National Health Data System (SNDS) and three large hospital health data warehouses in France, it aims to model and improve care pathways at three scales: patient, hospital, and network of hospitals at different national health territories. The project considers clinical, medico economic, social, patient and healthcare professional-centered criteria in data-driven optimization of care pathways. The interdisciplinary nature of NETSURG allows for a robust approach that combines data science, healthcare operations management, medicine, human and social sciences, and health economics, ensuring the proposed solutions are both innovative and applicable across different networks and territorial settings.
The scientific outcomes of NETSURG will advance state-of-the-art methodologies in healthcare operations management by developing data-driven models for predicting and optimizing emergency care pathways. The project will pioneer the use of medical key performance indicators in this domain and conduct cost-effectiveness analyses in association with hospital cooperation mechanisms. Furthermore, NETSURG’s development of a hospital network digital twin will enhance resource utilization, improve patient care (such as scheduling and recovery time management), and monitor facility saturation levels, particularly during crises. The societal impact is significant: the project will improve access to emergency care, leading to better patient outcomes, economic benefits for healthcare systems, and support for decision-making in the territorial planning of emergency care services. Additionally, the digital pre-software tool developed in our project, aimed at optimizing emergency care pathways, will be adaptable and applicable to most medical and surgical care pathways.
The project is challenging given the high dimension and the inherent stochastic and dynamic nature of the related problems, and our ambition to center on benefits and impacts for patients, medical staff, hospitals, and healthcare authorities. NETSURG builds on the successful collaboration of some of the partners under the ANR-funded DOSE project, which develops a local digital twin for La Pitié Salpêtrière hospital. NETSURG extends this work by applying it at a network level, as well as across different national health territories in France. NETSURG considers factors such as care quality, access times, cost of care, socio-economic impacts, and the potential for regional collaboration. These care parameters will be refined through insights from the SAFEPAW project, currently funded by the SantéNum program.
| Laboratory / department / team | Supervisory institution(s) |
| Industrial Engineering Laboratory (LGI) (coord.) | CentraleSupélec, Paris-Saclay University |
| LIMOS | Mines Saint-Étienne (EMSE) |
| iPLesp – UMR 1136 – “Pharmacoepidemiology and Care Evaluation” team | Inserm, Sorbonne University |
| Clinical Research Group in Anaesthesia, Intensive Care and Perioperative Medicine (GRC 29) | Sorbonne University, AP-HP La Pitié |
| Health Technology and Medical Practice Evaluation (METRICS), ULR 2694 | University of Lille |
| Nantes Atlantique Laboratory of Economics and Management (LEMNA) | Nantes University |

