Performance and Systemic optimization of Emergency medicine – POSAMU

1) Influence of the transmitted ECG obtained on-site by the SMUR team on the regulator’s therapeutic decision was evaluated.
2) The total process, from the call to center 15 until the SMUR team’s arrival at the patient, was subjected to digital modeling. The model used data collected over 14 consecutive months from the regulatory center’s database (number of calls per time slot for the different days of the week, their geographic origins, characteristics of the medical needs, classification of the emergency need for a SMUR intervention as primary or secondary for interhospital transfers), characteristics of the SMUR interventions (duration of the action, diagnosis of the disease); the geolocation software identifying every 10 seconds the GPS-tracked routes used by the intervention vehicles. The routes taken were reconstructed (as a function of the time slot and days of the week depending on traffic conditions) and a matrix of distances in French department 94 was built. Then, several scenarios varying human resources, the number of SMUR teams at different times, their initial base positions and dispatching strategies were run to evaluate outcomes on the time to the team’s arrival at the patient.
3) The total time between the call and the team’s real arrival at the patient (not the given address) was assessed to define the final on-foot pathway (“fine” accessibility) to reach the patient. The typology of the latter was studied with geomatics tools (mapping of the most relevant on-foot pathway and the development of an “obstacles” database for the SMUR teams).

1) For ~100 SMUR interventions with ECG transmissions to the regulator, no significant differences were found between their interpretation, diagnoses and the management decisions made.
2) The model was run on 314,326 calls to center 15 and 9386 SMUR interventions. The latter were classified as category 1 (1457 extreme emergencies, mostly primary) and category 2 (8325 less urgent situations, also predominantly primary). Time to arrivals at the patient were calculated based on a matrix of 527 IRIS islands (population density of ~2000 inhabitants/island) in the Val de Marne department. The route achieving the fastest arrival was chosen when several vehicle-choice options were available. Sixty-two scenarios were run to define the impact of the resource variations, SMUR-base repostitioning, assigned fixed geographic base sites, activity variations and, finally, analysis of specific days because of the unusual prolongations of transport times. The initial situation was very good (95.5% of emergency interventions in <30 min). The main findings were: decreasing the number of teams mostly affected performance between 8 am and midnight, and transiently repositioning a base (8 am to 8 pm) in the most distant zone (east department 94) maintained the performance level when traffic was congested.
3) For 15% of the interventions, 5 additional minutes on foot were needed to reach the patient. Fifty “vulnerable” zones were identified. The geographic database was unable to define on-foot paths or where to park the vehicle to achieve the shortest times. An “obstacle” database to map on-foot routes compatible with SMUR interventions needs to be created.

Geolocation, with real-time visualization on a screen, would enable the regulator to choose the vehicle that should reach the patient the fastest (displaying the time on the icon of each vehicle). A database must be created because traditional GPS tracking is not pertinent for rescue vehicles that can exceed speed limits, etc., all of which must be integrated into the regulatory software that will provide the SMUR team with a map with the ideal road and on-foot routes. A development phase is needed (equipment of vehicles with tracking devices for geolocation), followed by progressive implementation of the database including mapping of on-foot accessibility after field analysis, then using the data to determine the optimal positioning of the SMUR bases and indicators of the traffic conditions helping the regulator decide the transient repositioning of teams to maintain optimal arrival times.

1) Master 2 Recherche Informatique Systèmes Intelligents, Université Paris Dauphine, sept 2011: recalage de données GPS, analyse de distributions de vitesses et calcul d'itinéraires, M. Mestiri;
2) Master 2 Recherche Information Géographique, Ecole Nationale des Sciences Géographiques, sept 2012: Accessibilité fine aux patients du SAMU et bases de données d'adresses, A. Kiki;
3) Thèse en Génie Industriel, Ecole Centrale Paris, juin 2014: Evaluation et amélioration des performances des sytèmes d'Aide Médicale Urgente: application au SAMU du Département du Val de Marne, L. Aboueljinane;
4) Aboueljinane L, Sahin E, Jemai Z, Marty J. A simulation study to improve the performance of an emergency medical service: Application to the French Val-de-Marne department. Simulation Modelling Practice and Theory 47, 46-59, 2014.
5) Marty J, Vaux J, Baron I, Pineau P, Chollet-Xémard C. Quels indicateurs pour mesurer les délais des interventions SMUR primaires en milieu urbain? Urgences, Paris, 2011.

Given the significant development of the urban areas in the last decades, recent parliamentary reports pointed out the existence of important territorial disparities in the organization of care by underscoring “deficits and defects in the health system”. The “Hospital, Patients, Health, Territories” Law of the 21st July 2009 launches a reform aiming at ensuring an equal access to the health care system from any point of the territory and at ensuring a more effective care delivery.

The SAMU system (Emergency Medical Aid Service) created 30 years ago in order to organize the urgent medical aid at the level of each department, has to adapt itself to this reform. In France, the handling of calls arriving to the SAMU system involves a medical diagnosis. The medical decision, in the most serious cases, consists in sending a SMUR (Reanimation and Emergency Mobile Service) team on scene. However, since its creation, the SAMU-SMUR system does not have appropriate performance indicators, its performance being evaluated only at the volume of activities realised by the system. In urban areas, where the problems of accessibility are important, the analysis of the current system identified some deficiencies: the ratio of SMUR teams arriving on scene in less than 10 minutes after the reception of the call was lower than 21% (observation from SAMU 94 data). The SAMU system is therefore a perfect example of urban service illustrating the gap between the hospital and the sustainable city concepts. For this system, since urban constraints are very strong, it is difficult to guarantee an access to the care within the period of time recommended by the medical review of literature (direct relationship between mortality and time).
The objective of this project is to optimise the organisation of the service provided by the SAMU-SMUR system by using a systemic approach taking into account all the elements of this complex care delivery system in an urban context. We therefore aim at working on the whole organization and the medical strategy of the SAMU system by deploying a multi-disciplinary approach based on the most relevant and recent scientific methods and technologies in order to respect the target times for critical pathological situations.
The method will be developed by using data from pilot departments having maximum urban environmental constraints. It can then be deployed to the other French urban areas. The project consortium consists in: the SAMU 94 and 4 research laboratories (EA 4390 of UPEC,, LGI lab of ECP, COGIT Lab of IGN and LVMT of ENPC.).. The scientific program is structured over 7 tasks:
1 - definition of the objectives
2 - identification of urgent medical situations by new technologies
3 - quantitative performance evaluation of the global system
4 - definition of the system architecture and data flows
5 - simulation of various scenarios to optimize the static structure of the system
6 - simulation of dynamic scenarios in order to propose real time options to physicians
7 – development of organizational recommendations, a computer aided tool that enables to redefine the organization and a demonstrator for real-time operations
The 24 months duration project will provide 6 deliverables:
deliverable 1: methodological guidelines for the optimization of SAMU operations
deliverable 2: an optimization model enabling to improve SAMU operations in urban areas
deliverable 3: recommendations for a better identification of medical emergency situations
deliverable 4: specifications for a decision-making software to be used by the regulating SAMU physician
deliverable 5: design of a demonstrator illustrating the information flow, the interfaces between systems, their update and the tracing of data
deliverable 6: recommendations towards the town planning process in terms of accessibility needs for medical emergency services