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Leeds Teaching Hospitals OMOP Database
Population Size
1,500,000
People
Years
2003 - 2025
Associated BioSamples
None/not available
Geographic coverage
E08000035
Lead time
2-6 months
Summary
Documentation
The Leeds Teaching Hospitals NHS Trust (LTHT) OMOP database is a robust, longitudinal dataset constructed using data from the electronic health records (EHR) of patients treated and diagnosed at Leeds Teaching Hospitals NHS Trust since 2003. This comprehensive resource is mapped to the OMOP CDM, ensuring interoperability with other OMOP databases, and enabling privacy-preserving, large-scale, multi-centre studies.
Encompassing a wide array of clinical data, the database includes information on demographics, diagnoses, procedures, medications and laboratory results. A particular strength lies in its detailed cancer-specific data, which supports in-depth analyses of treatment outcomes, survival rates, and disease progression. This makes it an invaluable resource for researchers focusing on oncology, as well as those interested in broader secondary care settings.
Researchers can draw insights from the LTHT OMOP database through federated analytics approaches as well as through the use of standardised OHDSI tools, which enable secure, privacy-preserving analyses across multiple institutions, eliminating the need to access individual-level patient data.
Notably, the LTHT OMOP database has been instrumental in several high-profile studies:
• HERON Network: LTHT is a member of the HERON network, funded by HDR UK, which focuses on enhancing the quality and impact of cancer research through federated analytics. LTHT participated in a study examining the use of antibiotics which are in the WHO watchlist for high risk of antimicrobial resistance. • DigiONE Pilot Studies: These studies analyse harmonised routine care data from OMOP databases in 6 digitally mature European hospitals. Three studies have been conducted to date, focusing on the impact of the COVID-19 pandemic on cancer care, on metastatic non-small cell lung cancer, and on HER2-/HR+ metastatic breast cancer. • FALCON-Lung Study: This study focused on the uptake of immune checkpoint inhibitors for metastatic non-small cell lung cancer across the world, and implemented a clinically validated line of therapy algorithm using systemic anti-cancer therapy data in the OMOP databases of 17 international institutions.
In summary, the LTHT OMOP database stands as a robust resource for secondary care research, particularly in oncology. Its comprehensive, high-quality data, combined with a commitment to national and international collaboration, positions it as a cornerstone for advancing healthcare research and improving patient outcomes.
The LTHT OMOP database consists of the following tables and data:
• Visit occurrence: includes inpatient and outpatient admissions for all patients that are or have been part of the cancer pathway, as well as all in-patient admissions for all other patients. The visit_detail table has not been populated. • Condition occurrence: populated with all diagnoses in the Trust since 2003. • Drug exposure: populated. Includes all anti-cancer drugs (chemotherapy and immunotherapy), and selected antibiotics medication (all antibiotics that are in the WHO watchlist for antimicrobial resistance, as well as access antibiotics). Plans to extend this to all medication prescribed. • Procedure occurrence: populated. Includes surgical and radiotherapy procedures delivered to patients with cancer, as well as all surgical procedures delivered to all other patients. • Measurement: populated with weight, height, TNM staging, performance status, and metastasis location data. • Observation: populated with ethnicity, IMD quintile, clinical trial participation (cancer only) and cancer histology data. • Device exposure: not populated. • Death: populated from ONS.
Dataset type
Dataset sub-type
Dataset population size
Keywords
Observations
Observed Node | Disambiguating Description | Measured Value | Measured Property | Observation Date |
---|---|---|---|---|
Persons | Given total of distinct PERSON_ID in the OMOP PERSON table | 1500000 | Count | 07 May 2025 |
Events | Total count of diagnosis | 8000000 | Count | 06 May 2025 |
Events | Number of visits (in-patient/out-patient) | 13000000 | Count | 06 May 2025 |
Provenance
Purpose of dataset collection
Source of data extraction
Collection source setting
Patient pathway description
disease progression and treatment efficacy.
In addition to cancer care
Image contrast
Biological sample availability
Structural Metadata
Details
Publishing frequency
Version
Modified
15/05/2025
Distribution release date
07/05/2025
Citation Requirements
Coverage
Start date
01/01/2003
End date
07/05/2025
Time lag
Geographic coverage
Maximum age range
Follow-up
Accessibility
Language
Alignment with standardised data models
Controlled vocabulary
Format
Data Access Request
Dataset pipeline status
Time to dataset access
Access request cost
Access method category
Access service description
Access to the LTHT OMOP database is governed by strict data governance protocols to ensure patient privacy and compliance with ethical standards. Individual-level patient data is not accessible to external researchers; instead, analyses are conducted through federated platforms, such as Vantage6, and/or using standardised OHDSI tools, which allow for secure, privacy-preserving research. Researchers interested in drawing insights from the LTHT OMOP database without accessing individual-level patient data can initiate the process by contacting the LTHT research data and informatics team (R-DIT) to discuss their project goals and requirements.
Jurisdiction
Data use limitation
Data use requirements
Data Controller
Data Processor
Dataset Types: Health and disease, Treatments/Interventions, Measurements/Tests, Socioeconomic
Dataset Sub-types: Cancer, Cardiovascular, Rare diseases, Metabolic and endocrine, Respiratory, Musculoskeletal, Renal and urogenital, Pathology, Ethnicity, Deprivation, Births and deaths
Collection Sources: Clinic, Primary care - Clinic, Secondary care - Accident and Emergency, Secondary care - Outpatients, Secondary care - In-patients
Publications about this dataset
OHDSI Europe symposium
Published - 2023