New ECHILD Publication: Phenotype Code List Repository improves identification of clinical phenotypes in administrative data

Dr Matt Jay, a member of the ECHILD team, has published a new article in the International Journal of Population Data Science (IJPDS).

The publication explores the challenges and opportunities of using administrative health data—such as Hospital Episode Statistics (HES)—to identify groups of individuals with particular clinical conditions, a process known as phenotyping. These clinical phenotypes play a crucial role in research, serving as exposures, covariates, or outcomes across studies using administrative data, especially when linked with datasets beyond health, like those in the ECHILD project.

To support researchers working with linked data, the ECHILD team, led by Matt, has developed the ECHILD Phenotype Code List Repository—an open, searchable website housing phenotype code lists suitable for use with ECHILD and other datasets. The Repository includes summaries, implementation scripts for R and Stata, and was designed using clear principles to ensure ease of use and standardisation.

This resource represents a significant step forward in improving the accessibility, findability, and usability of phenotyping resources in the ECHILD project and linked administrative data research more broadly.

🔗 Open science and phenotyping in UK administrative health, education and social care data: the ECHILD phenotype code list repository | International Journal of Population Data Science
🔗 https://code.echild.ac.uk/