Changing the Paradigm of Disaster Medical Response through Data-Driven Decision-Making

The landscape of disaster response is rapidly evolving, driven by the increasing complexity, frequency, and scale of emergencies. To meet these challenges, there is a pressing need to transition from intuition-based or reactive responses toward data-driven, evidence-informed strategies that improve the effectiveness, efficiency, and equity of medical care in disaster contexts. Leveraging real-time data, predictive analytics, and performance monitoring enables more adaptive and accountable decision-making—ushering in a new era of precision disaster medicine.

This research topic seeks to explore the integration of data systems, analytical tools, and performance metrics into the practice of disaster medical response. It invites interdisciplinary contributions that demonstrate how data-driven approaches can enhance preparedness, coordination, field hospital operations, and clinical outcomes during crises. Emphasis is placed on practical applications, implementation science, and the critical feedback loops that allow health systems to learn and evolve in real time.

Key focal areas may include, but are not limited to:

Real-Time Operational Data Use: Development and application of tools and dashboards to monitor clinical, logistical, and operational metrics during field operations.

KPI-Based Evaluation of Field Hospitals: Research on frameworks that use key performance indicators to evaluate the quality, timeliness, and scalability of emergency medical interventions.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Data-Driven Response, Real-Time Evaluation, Health System Resilience, Performance Indicators

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.