Associative analysis of inefficiencies and station activity levels in emergency response

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Article

Source Title

International Journal of Geo-Informaion

Volume

11

Issue

356

Publication Date

2022

Abstract

Emergency medical services (EMS) around the world face the challenging task of allocating resources to efficiently respond to medical emergencies within a geographical area. While several studies have been done to improve various aspects of EMS, such as ambulance dispatch planning and station placement optimization, few works have focused on the assessment of existing rich real-world emergency response data to systematically identify areas of improvement. In this paper, we propose DAPI (data-driven analysis of potential response inefficiencies), a general tool for analyzing inefficiencies in emergency response datasets. DAPI efficiently identifies potential response bottlenecks based on spatial distributions of ambulance responses and statistically assesses them with respect to inferred activity levels of relevant dispatch stations to aid causality analysis. DAPI is applied on a dataset containing all medical emergency responses in mainland Portugal, in which we find statistical evidence that inefficiencies are correlated with high levels of activity of stations closer to an emergency location. We present these findings, along with the associated patterns and geographical clusters, serving as a valuable decision support tool to aid EMS in improving their operations.

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Disciplines

Emergency and Disaster Management

Keywords

Emergency medical services

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