top of page


The Poverty You Can’t See: Scarcity, Stress, and the Health Data That Miss Them (Part 2)
Socioeconomic status (SES) is part of the default demographic toolkit in health research — right up there with age and sex. And much like those, it’s often included reflexively, adjusted for automatically, and measured using whatever data happen to be available. Part 1 lays out the limits of income-based SES measures and introduces alternative ways to capture deprivation, including household-level metrics and geographic proxies.
6 days ago


📄Data Diversity Theme survey: Challenges in embedding inclusion and diversity in data-driven health research
Share your views and help us shape the priorities of the Data Diversity theme for the next year! The Turing Way Community, & Scriberia. (2024). Illustrations from The Turing Way: Shared under CC-BY 4.0 for reuse. Zenodo. https://doi.org/10.5281/zenodo.13882307 Health datasets can fail to fully represent the populations they aim to serve. When certain groups are missing or measured inconsistently, research findings may not generalise, and data-driven tools can perform less we
Nov 6


The Poverty You Can’t See: Scarcity, Stress, and the Health Data That Miss Them (Part 1)
Socioeconomic status (SES) is part of the default demographic toolkit in health research — right up there with age and sex. And much like those, it’s often included reflexively, adjusted for automatically, and measured using whatever data happen to be available. Part 1 lays out the limits of income-based SES measures and introduces alternative ways to capture deprivation, including household-level metrics and geographic proxies.
Nov 3


Why Causality Matters for Health Equity: Understanding Path-Specific Fairness
By asking how inequity flows through the health system, we can build predictive models and interventions that align with the real-world drivers of injustice. Path-specific fairness helps us design systems that treat patients equitably, not just equally. In this blog post, we walk through a real example that shows how surface-level fairness can reinforce inequities. Then we introduce the idea of causal fairness.
Oct 2


How can statistical methods reduce inequalities in genomics?
by Brieuc Lehmann Inequality is part of our society, and the way we collect and analyse information about people can reinforce this...
Aug 20, 2024


Why Businesses Should Invest in the Community Diamond Innovation Network (CDIN)
by Katherine Liddell Engaging in the Community Diamond Innovation Network (CDIN) presents a unique opportunity for businesses to align...
Aug 1, 2024


Building a Preventative Health Network: Insights on Technology, Relationships, and Health
by Katherine Liddell Our aim to build a preventative health network has surfaced three critical insights: the importance of technology,...
Jul 26, 2024


A DSxHE Reflection on the Whitehead Review Recommendations
by Lizzie Remfry Whitehead Full Report: Equity in Medical Devices: An Independent Review The Whitehead review, released in March 2024,...
Jul 1, 2024
bottom of page