UCL Application for a Mental Health Data Pathfinder award
Lead Research Organisation:
University College London
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
Advancing methodology and linkages in electronic health records for mental health research.
UCL’s cross-disciplinary mental health research is world leading, with current mental health grant activity in excess of £100M. Our Mental Health Data Pathfinder proposal brings together research leaders from across our mental health and neuroscience Divisions and Institutes, and integrates our unparalleled infrastructure and expertise in Population Health Sciences and Health Informatics. The application builds on our track record in neurosciences, epidemiology and mental health database research. Our project is ambitious and deliverable, representing a range of research disciplines that will meet several pathfinder data challenges, and will deliver real impact on data quality and methods in mental health research.
The UCL mental health data pathfinder aims to enhance UCL’s Electronic Mental Health Record capacity through new linkage, new data discovery methods, involving large databases of adults and/or children in primary and secondary care. This will determine the effectiveness, precision and safety of mental health interventions.
UCL’s cross-disciplinary mental health research is world leading, with current mental health grant activity in excess of £100M. Our Mental Health Data Pathfinder proposal brings together research leaders from across our mental health and neuroscience Divisions and Institutes, and integrates our unparalleled infrastructure and expertise in Population Health Sciences and Health Informatics. The application builds on our track record in neurosciences, epidemiology and mental health database research. Our project is ambitious and deliverable, representing a range of research disciplines that will meet several pathfinder data challenges, and will deliver real impact on data quality and methods in mental health research.
The UCL mental health data pathfinder aims to enhance UCL’s Electronic Mental Health Record capacity through new linkage, new data discovery methods, involving large databases of adults and/or children in primary and secondary care. This will determine the effectiveness, precision and safety of mental health interventions.
Organisations
Publications
Adams EA
(2023)
Investigating social deprivation and comorbid mental health diagnosis as predictors of treatment access among patients with an opioid use disorder using substance use services: a prospective cohort study.
in Substance abuse treatment, prevention, and policy
Bauernfreund Y
(2023)
Incidence and associations of hospital delirium diagnoses in 85,979 people with severe mental illness: A data linkage study.
in Acta psychiatrica Scandinavica
Cripps R
(2020)
Characteristics and risk of repeat suicidal ideation and self-harm in patients who present to emergency departments with suicidal ideation or self-harm: A prospective cohort study
in Journal of Affective Disorders
Dalton-Locke C
(2020)
Using de-identified electronic health records to research mental health supported housing services: A feasibility study.
in PloS one
Hayes JF
(2022)
Association between quetiapine use and self-harm outcomes among people with recorded personality disorder in UK primary care: A self-controlled case series analysis.
in Journal of psychopharmacology (Oxford, England)
Jeffery A
(2024)
The association between antidepressant treatment and rates of insulin initiation in comorbid depression and type 2 diabetes: A UK electronic health record nested case-control study
in Diabetes Research and Clinical Practice
Jeffery A
(2023)
Association between polypharmacy and depression relapse in individuals with comorbid depression and type 2 diabetes: a UK electronic health record study.
in The British journal of psychiatry : the journal of mental science
Jeffery A
(2023)
Polypharmacy and antidepressant acceptability in comorbid depression and type 2 diabetes: a cohort study using UK primary care data
in British Journal of General Practice
Description | DataMInd |
Amount | £2,031,434 (GBP) |
Organisation | United Kingdom Research and Innovation |
Sector | Public |
Country | United Kingdom |
Start | 08/2021 |
End | 08/2024 |
Description | Increasing access to social prescribing for people living with severe mental illnesses at risk of cardiovascular disease |
Amount | £224,999 (GBP) |
Funding ID | MQF226 |
Organisation | MQ Mental Health Research |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2023 |
End | 10/2026 |
Title | C&I CRIS |
Description | ethics renewal for CRIS research database at Camden and Islington NHS Foundation Trust took place to facilitate data Pathfinder activity. approved researchers may apply to use the database |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | faciliates clinical research and also service evaluation for the local NHS Trust |
URL | https://www.candi.nhs.uk/health-professionals/research/ci-research-database |
Description | MQ Data Science Meeting |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | MQ data science meeting for using health data in mental health research |
Year(s) Of Engagement Activity | 2020 |