A direct qualitative content analysis on the design, implementation, and evaluation of prehospital earthquake exercises aligned with the HSEEP framework
摘要
Disaster exercises are a vital strategy for enhancing Emergency Medical Services (EMS) operational preparedness. This study aimed to extract “Golden Keys” for Design, Implementation and Evaluation of earthquake exercises aligning these key components with the internationally recognized Homeland Security Exercise and Evaluation Program (HSEEP) Framework from the perspective of experienced Iranian prehospital technicians.
MethodA qualitative study was conducted using a directed content analysis. Data were systematically gathered through in-depth semi-structured interviews with 11 prehospital technician that purposefully selected based on their demonstrated expertise in prehospital exercise management. Data analysis was conducted in five steps following Granheim and Lundman’s approach and the study used Lincoln and Guba’s recommendations to assess data trustworthiness.
ResultAfter multiple rounds of data analysis and summarization 386 initial codes, 13 subcategories, and five main categories were identified. These main categories included “Exercise Foundation and Program Governance”, “Exercise Design, Coordination, and Control”, “Operational Implementation of the Exercise”, “Performance Evaluation and Capability Assessment” and “Learning, Workforce Empowerment”, and “System Improvement”.
ConclusionEarthquake preparedness exercises must be sustained as an ongoing effort to enhance prehospital system resilience. The indicators identified in this study provide an actionable, evidence-based framework for EMS managers and policymakers to design, implement, and evaluate exercises aligned with system priorities. Translating exercise outcomes into actionable evidence facilitates informed decision-making targeted resource allocation and evidence-based policy formulation. Future research should focus on contextualizing this framework within localized programs and conducting quantitative validation of the proposed indicators.