An analytical framework for increasing the efficiency and validity of research using primary care databases

Date of Approval
Application Number
Technical Summary

Routinely collected electronic medical record (EMR) databases are rich sources of data for health research. Although lacking the rigour of Randomised Controlled Trials (RCTs) and potentially affected by bias from uncontrolled factors, these databases allow the investigation of research questions which may not be feasible to address by other means. The UK leads the world in Primary Care Databases (PCDs), which collate data from the electronic records of patients registered with large numbers of general practices, benefitting from the almost complete computerisation of UK primary care. Publications using PCDs and the Clinical Practice Research Datalink (CPRD) in particular attract global research interest and applications are becoming more sophisticated, and the demands made on the data greater, as the field develops. This work focuses on three problematic or under-developed aspects of PCD-based research studies: a) reducing duplication of effort; b) increasing validity and reproducibility; c) improving analysis methodologies. To address these issues we will develop and maintain an online repository and also develop methods and software to perform power calculations, extract data and impute missing data. Our aim to increase the efficiency and transparency with which PCD-based research is conducted and the validity of the findings resulting from that research.

Health Outcomes to be Measured

Asthma, atrial fibrillation, cancer, coronary heart disease, chronic kidney disease, chronic obstructive pulmonary disease, dementia, depression, diabetes mellitus, epilepsy, heart failure, hypertension, hypothyroidism, learning disability, osteoarthritis, osteoporosis, severe mental illness, stroke, and Body Mass Index


Evangelos Kontopantelis - Chief Investigator - University of Manchester
Evangelos Kontopantelis - Corresponding Applicant - University of Manchester
Darren Ashcroft - Collaborator - University of Manchester
David Reeves - Collaborator - University of Manchester