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Akrivia Health
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Sample details

Akrivia Health is one of the world’s largest and most in-depth datasets, comprised of anonymised longitudinal psychiatric data derived from the electronic health records (EHRs) of over 6 million patients in secondary mental health and dementia care across England and Wales. The data is regularly refreshed and harmonised across 20 NHS Healthcare Organisations providers. Akrivia Health was initiated in 2019, with patient records dating back to before 1990, including participants with psychiatric health record entries, likely over representing individuals with severe mental illness compared to the general population. The dataset contains structured data, such as patient demographics and service pathways, while research-relevant information is also extracted from free-text clinical notes using natural language processing (NLP).

Study design
Cohort - open, Cohort - clinical, Registry

Number of participants at first data collection

> 6,331,592 (participants as of January 2025)

Recruitment is ongoing

Age at first data collection

Varied (participants)

Participant year of birth

Varied (participants)

Participant sex
All

Representative sample at baseline?
Broadly representative of the adult secondary care psychiatric service user population in England.

Sample features

People with psychiatric conditions
Population-based sample
Dataset details
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Countries

England, United Kingdom of Great Britain and Northern Ireland, Wales

Year of first data collection

2019 (Akrivia inception)

1990 (medical records)

Primary Institutions

Akrivia Health

Links

akriviahealth.com/data/

Funders

Innovate UK (UKRI)

Wellcome Trust

Ongoing?
Yes

Data types collected

mentalHealthData
dataLinkage
Quantitative data collection
  • Secondary data
  • Self-report questionnaire – unspecified
Qualitative data collection
  • None
Neuroimaging data collection
  • None
Linked or secondary data
  • Healthcare data
Features

Engagement

  • Patients, service users, lived experience involvement
  • Participant or community advisory groups
  • Keywords

    Electronic health records
    Health and wellbeing
    Healthcare access and use
    Mental health
    Neuroscience
    Population-based
    Service use
    Treatment experiences and outcomes
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