Artificial Intelligence Applications For Decision Support And Response Time Optimization In The Saudi Red Crescent Authority

Abstract

Artificial intelligence (AI) has become an essential component of modern emergency medical services (EMS), offering advanced capabilities that enhance decision-making, improve operational efficiency, and reduce overall response times. Recent global studies demonstrate that AI-supported applications—such as machine learning–based demand forecasting, natural language processing (NLP) for call triage, and dynamic routing algorithms—significantly improve dispatch accuracy, optimize ambulance distribution, and strengthen situational awareness in high-pressure environments. These technologies also support EMS teams by facilitating early recognition of critical conditions and improving resource allocation during peak demand.

Within Saudi Arabia, the Saudi Red Crescent Authority (SRCA) has undertaken substantial digital transformation initiatives aligned with Vision 2030, including the adoption of geospatial intelligence, unified emergency reporting platforms, and automated operational dashboards. Despite these advancements, there remains a scarcity of empirical research evaluating AI’s real-world impact on SRCA operations, particularly regarding dispatch performance, triage accuracy, and response time optimization. This integrative review synthesizes evidence from studies published between 2020 and 2025 to assess the role of AI in global EMS systems and explore its applicability within the Saudi context.

Findings from 48 eligible studies indicate that AI-driven tools can reduce dispatch and routing times by 10–40%, improve triage accuracy by up to 28%, and enhance demand prediction precision with error margins below 10%. However, challenges persist, including data interoperability, workforce readiness, ethical considerations, and the need for context-specific model adaptation. The review highlights the critical opportunity for SRCA to implement and evaluate AI-enabled solutions to strengthen decision support, optimize ambulance operations, and improve patient outcomes nationwide.

Overall, AI represents a transformative pathway for advancing prehospital emergency care. Strategic investment in localized AI development, pilot testing, and longitudinal evaluation is essential for enabling SRCA to achieve world-class EMS performance and support national health transformation objectives.