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<p>Emergency aeromedical interhospital transfers are critical for ensuring timely access to specialized care in underserved regions. While emergency ground transportation has been extensively studied, strategic decisions regarding aeromedical fleet composition remain underexplored, despite their significant impact on response times, patient outcomes, and operational efficiency. In this study, we develop a discrete-event simulation model to analyze how fleet size, patient-carrying capacity, aircraft speed, and fleet mix influence overall performance. The conceptual model and its outputs were validated using real-world data from Évacuations Aéromédicales du Québec (EVAQ) and integrated into EVAQ’s fleet renewal planning process, demonstrating its practical relevance for decision-making. By incorporating demand patterns, network constraints, and both strategic and operational considerations, the model provided quantitative insights into service performance, particularly patient transfer times. For example, doubling the fleet from one to two aircraft reduces average transfer times by nearly 30%, whereas adding more than two yields only marginal gains; likewise, increasing capacity from two to four stretchers lowers transfer times for non-urgent patients by up to 18% with little effect on urgent cases. The results offer valuable guidance for aeromedical managers seeking to improve fleet planning and enhance access to specialized healthcare in underserved areas.</p>

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Strategic analysis of heterogeneous fleet composition for aerial interhospital transport in underserved areas of Canada

  • 期刊论文

  • 发表日期：

    2026年2月28日

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  • Joelle Cormier,
  • Valérie Bélanger,
  • Marie-Éve Rancourt

摘要

Emergency aeromedical interhospital transfers are critical for ensuring timely access to specialized care in underserved regions. While emergency ground transportation has been extensively studied, strategic decisions regarding aeromedical fleet composition remain underexplored, despite their significant impact on response times, patient outcomes, and operational efficiency. In this study, we develop a discrete-event simulation model to analyze how fleet size, patient-carrying capacity, aircraft speed, and fleet mix influence overall performance. The conceptual model and its outputs were validated using real-world data from Évacuations Aéromédicales du Québec (EVAQ) and integrated into EVAQ’s fleet renewal planning process, demonstrating its practical relevance for decision-making. By incorporating demand patterns, network constraints, and both strategic and operational considerations, the model provided quantitative insights into service performance, particularly patient transfer times. For example, doubling the fleet from one to two aircraft reduces average transfer times by nearly 30%, whereas adding more than two yields only marginal gains; likewise, increasing capacity from two to four stretchers lowers transfer times for non-urgent patients by up to 18% with little effect on urgent cases. The results offer valuable guidance for aeromedical managers seeking to improve fleet planning and enhance access to specialized healthcare in underserved areas.