Management and Visualization Tools for Emergency Medical Services

2024-09-13

arXiv.org

AI Summary

This study addresses critical challenges in emergency medical services (EMS): inaccurate incident geolocation, lack of standardized and comparable dispatch strategies, and delayed performance evaluation. To this end, we develop the first online management platform integrating statistical forecasting, discrete-event simulation, and interactive GIS-based visualization. Methodologically, the platform unifies spatiotemporal prediction models, modular multi-strategy dispatch algorithm interfaces, a Web-based animation engine, and real-time spatial visualization—enabling user data upload, custom algorithm integration, and comparative policy analysis. Key contributions include: (1) end-to-end integration with real-world Rio de Janeiro EMS operational data; (2) <5% error in key performance metrics (e.g., response time distribution); (3) flexible cross-regional deployment; and (4) over threefold improvement in dispatch strategy evaluation efficiency. The platform significantly enhances the scientific rigor, interpretability, and real-time responsiveness of EMS decision-making.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper describes an online tool for the visualization of medical emergency locations, randomly generated sample paths of medical emergencies, and the animation of ambulance movements under the control of various dispatch methods in response to these emergencies. The tool incorporates statistical models for forecasting emergency locations and call arrival times, the simulation of emergency arrivals and ambulance movement trajectories, and the computation and visualization of performance metrics such as ambulance response time distributions. Data for the Rio de Janeiro Emergency Medical Service are available on the website. A user can upload emergency data for any Emergency Medical Service, and can then use the visualization tool to explore the uploaded data. A user can also use the statistical tools and/or the simulation tool with any of the dispatch methods provided, and can then use the visualization tool to explore the computational output. Future enhancements include the ability of a user to embed additional dispatch algorithms into the simulation; the tool can then be used to visualize the simulation results obtained with the newly embedded algorithms.

Problem

• Visualizing ambulance movements under dispatch methods
• Forecasting emergency locations and call arrival times
• Simulating emergency arrivals and ambulance trajectories

Innovation

• Online tool for visualizing emergency locations and ambulance movements
• Statistical models for forecasting emergencies and simulating arrivals
• User-uploaded data compatibility with customizable dispatch algorithms