Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok

Acute ischemic stroke (AIS) requires rapid treatment to minimize neurological damage. Mobile Stroke Units (MSUs) provide timely interventions, and this study optimizes the rendezvous strategy (MSU-RS), where ambulances meet MSUs at predetermined points (rendezvous points). This research proposes a novel method to select optimal rendezvous points, reducing travel times, and enhancing MSU efficiency. Using a modified p-median problem and Geographic Information System (GIS) data, the research calculates precise travel times with the Open-Source Routing Machine (OSRM). A Genetic Algorithm (GA) is employed to solve this NP-hard problem. The research investigates the case study in central Bangkok incorporates telecommunication parameters critical for telemedicine. The result shows significant travel time reductions with the proposed GA configurations, especially the Mutation Dominant (MD) configuration. This research highlights the potential of GA in improving MSU rendezvous strategies, enhancing patient outcomes, and operational efficiency.

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Published
2024-12-15
DOI
https://doi.org/10.1109/ieem62345.2024.10857036
Primary Topic
Evacuation and Crowd Dynamics
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article
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article

Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok

R. Sirovetnukul, Yongchai Nilanont, K. Yongvongphaiboon
Evacuation and Crowd Dynamics
article

Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok

R. Sirovetnukul, Yongchai Nilanont, K. Yongvongphaiboon
article en

Abstract

Acute ischemic stroke (AIS) requires rapid treatment to minimize neurological damage. Mobile Stroke Units (MSUs) provide timely interventions, and this study optimizes the rendezvous strategy (MSU-RS), where ambulances meet MSUs at predetermined points (rendezvous points). This research proposes a novel method to select optimal rendezvous points, reducing travel times, and enhancing MSU efficiency. Using a modified p-median problem and Geographic Information System (GIS) data, the research calculates precise travel times with the Open-Source Routing Machine (OSRM). A Genetic Algorithm (GA) is employed to solve this NP-hard problem. The research investigates the case study in central Bangkok incorporates telecommunication parameters critical for telemedicine. The result shows significant travel time reductions with the proposed GA configurations, especially the Mutation Dominant (MD) configuration. This research highlights the potential of GA in improving MSU rendezvous strategies, enhancing patient outcomes, and operational efficiency.

Siriraj Hospital (TH), Mahidol University (TH)
Openalex Percentile: Top 65%
Evacuation and Crowd Dynamics
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Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok — R. Sirovetnukul, Yongchai Nilanont, et al. · (2024) | TGRS Research Map | TGRS