معرفی
Ehsan Rezaeidarzi is a Research Fellow at the School of Public Health and Preventive Medicine, Monash University, based at the Alfred Hospital. His work lies at the intersection of biostatistics, epidemiology, and health economics, with a strong focus on methodological rigor in public health research.
Research Interests:
His primary expertise includes biostatistical modeling, data analytics, injury surveillance, and the design and analysis of complex study designs such as stepped wedge cluster randomized trials. He applies advanced statistical techniques to real-world health data to improve public health outcomes, particularly in injury prevention and health services evaluation.
Publication Trends:
His recent publications (2023–2025) demonstrate a consistent focus on improving statistical methodologies for cluster-randomized trials and leveraging large-scale health datasets for injury research. Key themes include data quality assessment, injury severity scoring, gender disparities in fall-related injuries, and optimization of trial designs for efficiency and ethical considerations.
Scientific Contributions:
- Developed novel approaches to incomplete stepped wedge designs to reduce burden and cost.
- Evaluated emergency department data quality for injury surveillance systems.
- Compared methodologies for calculating Injury Severity Scores using ICD-coded data.
- Investigated gender differences in fall-related hospitalizations among older adults.
Academic Engagement:
He actively contributes to academic training by co-organizing workshops, including the 2023 event on the design and analysis of longitudinal cluster randomized trials. While no formal advisees are listed, his collaborative research involves mentoring through co-authorship and project involvement.
Research Environment:
He operates within a multidisciplinary research network at Monash University’s School of Public Health and Preventive Medicine, collaborating with leading experts in biostatistics and epidemiology. His work is supported by access to state-level health datasets and contributes to policy-relevant public health knowledge.
