OHDSI UK Collaborators
Akrivia Health
πhttps://akriviahealth.com/
Akrivia Health provides a secure data environment for nationally federated psychiatric electronic health records (EHRs) and linked research data. Akrivia provides the NHS, academia, and industry with access to the UKβs largest repository of anonymised, OMOP-harmonised, NLP-enriched EHRs from 6.3 million patients across 20 secondary healthcare organisations in England and Wales, a growing repository of multi-omics data, and linked primary care data through a partnership with Optimum Patient Care.
Barts Health NHS Trust
π¬hiba.junaid@nhs.net; usama.rahman@nhs.net; j.lane10@nhs.net
πhttps://data.bartshealth.nhs.uk
Barts Health NHS Trust is the largest NHS hospital group in the UK. We are harnessing one of the NHSβs largest and most diverse datasets to revolutionise healthcare. It contributes a dataset of approximately 3 million patients from across its six hospitals in East London. The dataset spans from 2012, with comprehensive and consistent records available from 2015/2016 onwards
Centre of Health Informatics, University of Nottingham
π¬philip.quinlan@nottingham.ac.uk; esmond.urwin@nottingham.ac.uk; andy.rae@nottingham.ac.uk
πhttps://bunny.health; https://carrot.ac.uk; https://www.nottingham.ac.uk/health-informatics/index.aspx
The Centre for Health Informatics at the University of Nottingham have been pioneers in developing software that support the conversion and use of data to the OMOP Common Data model. Our software tools are used internationally. Carrot is our tool to help organisations to covert data to OMOP. Bunny is our software to help federated discovery of data.
These are developed across existing programmes of Health Data Research UK and NIHR Nottingham Biomedical Research Centre.
Clinical Architecture
π¬info@clinicalarchitecture.co.uk
πhttps://www.clinicalarchitecture.co.uk/
Clinical Architecture was established in 2007 with the goal of becoming the leading provider of solutions and services that focus on healthcare terminology and data quality management. Clinical Architectureβs core capabilities and experience revolve around semantic and syntactic health data translation. We support transformations into the OMOP common model along with semantic normalisation of terminology, a key activity that can directly impact the quality of the data transformations.
Clinical Practice Research Datalink (CPRD)
πwww.cprd.com
Clinical Practice Research Datalink (CPRD) is a real-world research service supporting retrospective and prospective public health and clinical studies. CPRD research data services are delivered by the Medicines and Healthcare products Regulatory Agency with support from the National Institute for Health and Care Research (NIHR), as part of the Department of Health and Social Care. CPRD collects anonymised patient data from a network of GP practices across the UK.
DataLoch, University of Edinburgh
π¬Maheva.Vallet@ed.ac.uk; Nicola.Symmers@ed.ac.uk; dataloch@ed.ac.uk
πhttps://dataloch.org; https://cancer-data.ecrc.ed.ac.uk
DataLoch is a Trusted Research Environment integrating routinely collected health data from primary and secondary care in the Lothian region covering a population of 900k people. In partnership with Edinburgh Cancer Informatics, it offers OMOP CDMs for the general population, with records for ~1.76M unique patients going back to 1984, and a cancer-specific CDM containing ~38.7k patients diagnosed with breast cancer since 1960. We plan to include additional tumour types in future.
Evidentli
π¬guyt@evidentli.com; Tsafnat@ohdsi.org
πEvidentli.com
Evidentli is the leader in the transformation of data from any source to OMOP 50X faster and 6X more accurately than subject matter experts. We specialise in federated learning, AI enablement, eSource, site & patient recruitment and clinical trial monitoring for life sciences, and clinical quality improvement and compliance and federation in healthcare including the NHS.
Great Ormond Street Hospital NHS Foundation Trust
πhttps://www.gosh.nhs.uk/; https://www.goshdrive.com/
GOSH is a specialist tertiary care paediatrics hospital in the UK receiving children with complex and/or rare conditions. A large proportion of the children that GOSH see typically require long-term care and follow up at GOSH. This results in data collected during routine healthcare that are very rich in number of variables and detail and includes all the Electronic Patient Data since 2019 covered over 200,000 patients
HIC
π¬HIC-Ops@dundee.ac.uk; k.milburn@dundee.ac.uk
πhttps://www.dundee.ac.uk/hic
Established over 20 years ago, we are a Safe Haven Network Node for the Scottish Government, ISO27001 certified, delivering secure, research managed βaccess toβ data. Our experience from the CO-CONNECT project and the Alleviate Pain Data Hub developing open-source tools/expertise to support making datasets FAIR using the OMOP Common Data Model. We have worked with many data partners to map their data to OMOP and can support your mapping needs for research collaborations or as a service.
Health Data Sciences, University of Oxford
π¬daniel.prietoalhambra@ndorms.ox.ac.uk
πhttps://www.ndorms.ox.ac.uk/research/research-groups/Musculoskeletal-Pharmacoepidemiology; https://oxford-pharmacoepi.github.io/Oxinfer/
Our research is focused on the understanding of the safety and effectiveness of new and long-licensed medications and devices. We are particularly interested in studying both the benefits and the potential risks of the use of such therapies in special subgroups of the population that were under-represented in previous clinical trials. The group also develops and maintains several R packages widely used on the OHDSI community.
Lancashire Teaching Hospitals NHS Foundation Trust
πhttps://lscsde.org/; https://www.lancsteachinghospitals.nhs.uk/
LTHβs OMOP database is one of a few (or only one) globally that refreshes daily and is used for research, operational/direct care intelligence as well as to support clinical trials with cohort discovery. We were awarded 2024 HDRUK Team of Year for our approach.
It covers most aspects of secondary care for 1.5 million patients with increasing data coverage in recent years. We are building a single OMOP instance to integrate all regional primary and secondary care data.
Leeds Teaching Hospitals NHS Trust
π¬leedsth-tr.researchdata@nhs.net; stelios.theophanous@nhs.net
πhttps://www.leedsth.nhs.uk/about/; https://www.leedsth.nhs.uk/research/our-research/research-data-strategy/
Leeds Teaching Hospitals NHS Trust is one of the largest acute hospital trusts in the country, a regional and national centre for specialist treatment, and the local hospital for the Leeds community - treating 1.5 million patients annually, including over 200,000 emergency cases. The LTHT OMOP database includes research-ready demographic, clinical and a wealth of cancer-specific data derived from electronic health records of patients diagnosed and treated at LTHT since 2003.
National Institute for Health and Care Excellence
π¬shaun.rowark@nice.org.uk; dataanalytics@nice.org.uk
πnice.org.uk
NICE helps practitioners and commissioners get the best care to people, fast, while ensuring value for the taxpayer. We do this by: -producing useful and usable guidance for health and care practitioners -providing rigorous, independent assessment of complex evidence for new health technologies -developing recommendations that focus on what matters most and drive innovation into the hands of health and care practitioners -encouraging the uptake of best practice to improve outcomes for everyone.
Optimum Patient Care Research Database (OPCRD)
π¬info@opcrd.co.uk
πhttps://opcrd.optimumpatientcare.org/
The Optimum Patient Care Research Database (OPCRD) is established and maintained by Optimum Patient Care (OPC), a UK based social enterprise.
OPC supports more than 1,000 GP practices across the United Kingdom and is one of the biggest primary care data and research networks in the world.
The anonymous electronic medical records and patient questionnaires collected within OPCRD provide an essential source of real world data to promote evidence-based research and quality improvement.
Queen Mary University of London / Notts and Nottinghamshire NHS
My research interests r.e. OHDSI are text-to-sql generation in the OMOP CDM and methodological research
University College London Hospitals
π¬uclh.safehr@nhs.net; andrew.south2@nhs.net
University College London Hospitals is an inner city teaching hospital treating >1m outpatients and >100k inpatients per year. The patient population includes national referrals for tertiary and quaternary services (cancer, neurology etc.). A new initiative, SAFEHR (Secure and Anonymised Framework for Electronic Health Records), supports health researchers at UCL and UCLH to work with hospital data. A re-useable OMOP-Extraction System (OMOP-ES) is used to provide researchers with OMOP data.
Become a collaborator
Join our mail list and become a collaborator telling about us: Fill out this form.