🎥 DSxHE Data Diversity X Statistical Methods Tutorial - Distributional Cost-Effectiveness Analysis (DCEA) 🎥
Standard cost-effectiveness analysis tells you how much health an intervention buys, but says nothing about who gains and who loses.
On October 5th 2026, Dr Ahwaz Akhtar (The George Washington University) led a 90-minute interactive tutorial on Distributional Cost-Effectiveness Analysis (DCEA) - a framework for bringing equity directly into health economic evaluation.
Using a case study, the participants learned to model how health gains and costs are distributed across population subgroups, apply fairness adjustments, and evaluate competing interventions using inequality indices and social welfare tradeoffs, all through live-coded R examples. The session combined short presentations, guided coding walkthroughs, and breakout discussion, and is designed for early-career researchers and practitioners in health data science who are already comfortable with basic CEA/QALY concepts but new to distributional methods.
This session was a partnership between DSxHE's Statistical Methods and Data Diversity Themes, in collaboration with Cancer Research UK.
The recording is now available to watch on demand!
The coding notebook can be viewed here
The slides can also be downloaded here:
Who it's for: No prior experience with distributional or equity-weighted evaluation required - just basic familiarity with R/Python, standard CEA concepts and a lot of enthusiam for data diversity!
About the Data Diversity Theme
Health datasets often don’t reflect the diversity of the populations they aim to serve. This lack of representativeness can limit the generalisability of research, reduce the effectiveness of new tools, and risk widening health inequalities.
A partnership between Data Science for Health Equity and Cancer Research UK, the Data Diversity Theme brings together researchers, clinicians, funders, and patient advocates to co-create practical ways of embedding diversity across the research lifecycle. It is co-led by Dr Toral Gathani (University of Oxford) and Dr Brieuc Lehmann (UCL).
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