Profile
Biography
Han-I is a research fellow in the York Trial Unit (YTU). She completed her Doctorate in health economics at the University of York in 2011 and worked in the Epidemiology Cancer Statistics Group (ECSG) (2011-2019) and the Mental Health and Addiction Research Group (MHARG) (2019-2023) before joining YTU in 2023.
Han-I specialises in economic evaluation, health outcomes research, and, more recently, climate change and sustainability. Her work often involves large, complex patient-level datasets and the application of advanced simulation techniques, including both cohort and individual-level models. In addition to her background in health economics, she is a trained data scientist and is actively incorporating machine learning and deep learning methods into health economic evaluation and outcomes research. She collaborates with academic teams and government organisations both within and beyond the University of York, working across the UK and internationally to support interdisciplinary research in this field
Qualifications
- MSc, Computer Science with artificial intelligence, University of York
- PhD, Health Economics, University of York
- MSc, Health Economics (with distinction) Taipei Medical University
Departmental roles
- Programme Lead- PGCert in Health Research and Statistics
Research
Overview
Han-I is engaged in health outcome research, economic evaluation, and the integration of deep learning techniques, with a strong emphasis on maximising health benefits and promoting equity. Her work spans a range of public health and clinical areas, including cancer, mental health, tobacco use, chronic diseases such as diabetes, and the health impacts of climate change.
Her specific research interests include:
- Economic evaluation and health outcome research using complex patient level data
- Decision modelling/simulation research using real-world data
- Assessing both the efficiency and equity impact of health interventions through distributional cost-effectiveness analysis
- Application of deep learning techniques for clinical outcome prediction, cancer risk stratification, and healthcare needs forecasting
- Palliative / End-of-life care and place of death research
Projects
- ACTIVE - A RCT assessing the effectiveness of internal plate fixation versus external fine wire fixation for the management of Type C, closed pilon fractures of the distal tibia
- ASPECT - Alleviating Specific Phobias Experienced by Children Trial
- ASSSIST-2 – Social Stories for children with autism
- BASIL/BASIL+ - An RCT of the BASIL programme, a psychological intervention, for mitigating depression and loneliness during the Covid-19 pandemic in older people with long-term health conditions
- BAY - An RCT investigating behavioural activation for moderately to severely depressed young people in CAMHS settings.
- HAMLET - A multicentre, two-arm, non-blinded, pragmatic, parallel group, randomised controlled superiority trial assessing the clinical and cost effectiveness of Through Knee Amputation (TKA) compared to Above Knee Amputation (AKA) in patients requiring major lower limb amputations (MMLA), but who are unsuitable for a Below Knee Amputation (BKA).
- I-SOCIALISE - Investigating Social Competence and Isolation in children with Autism taking part in LEGO-based therapy clubs In School Environments
- MCLASS II - Muslim Communities Learning About Second-hand Smoke in Bangladesh
- MODS - A programme aiming to develop and evaluate an intervention to improve physical and psychological functioning in older adults with long-term physical health conditions and low mood or depression
- STIMULATE-ICP - Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways
- Trial Forge Studies Within a Trial (SWAT) centre
Research group(s)
Supervision
Han-I would be interested in supervising or co-supervising MSc and PhD students in the following areas: economic evaluation, cost analysis, health outcome research, decision modelling, big data analysis, and machine learning.