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Can we identify vulnerable groups from users of the UK's largest mental health service provider?

Research Question: (RQ09):

Can we identify vulnerable groups from users of the UK’s largest mental health service provider?


Robert Stewart, Honghan Wu; South London and Maudsley; HDR UK Scotland, Edinburgh

Submission Date:


Research Question Narrative:

Use natural language processing to identify patients with vulnerable physical underline conditions on near real time SLaM EHR data.

Intended Research Outcomes:

An automated pipeline to identify most vulnerable people from EHRs.

SAGE Priority Area:

Direct Impact; Other conditions

Prioritisation Score:


Prioritisation Rounds:


Progress So Far:

33 phenotypes have been defined including various autoimmune disorders. A set of multi-morbidity NLP models have been adapted to run on the whole set of free-text SLaM EHRs.

PPIE Activities So Far:

hub for data sharing and interoperability

HDR UK community members with skill & will to contribute:

Original content: