B4437 - Synthetic Health Data for Research Support - an exemplar from a birth cohort - 31/10/2023

B number: 
B4437
Principal applicant name: 
Mark Mumme | University of Bristol
Co-applicants: 
Dr Eleanor Walsh, Dr Daniel Major-Smith, Prof Kate Northstone
Title of project: 
Synthetic Health Data for Research Support - an exemplar from a birth cohort
Proposal summary: 

Electronic health records (EHRs) are a valuable resource in research, with the potential to increase sample size, reduce biases and improve representativeness, by being collected on national scale at the point of care by health care providers. Due to the personal and sensitive nature of EHRs, the confidentiality of these data is protected by strict regulatory frameworks. Accessing EHRs can take months or even years; this remains a major barrier for researchers gaining timely access to real world data. We propose to use the ALSPAC setting as an exemplar project synthesising EHRs in a cohort context. We will develop a roadmap of the key requirements for synthesising EHRs within a cohort setting.

Impact of research: 
This project will provide a roadmap of key requirements for syntheising EHRs applied in a cohort setting, as well as an evaluation of current approaches.
Date proposal received: 
Monday, 16 October, 2023
Date proposal approved: 
Monday, 30 October, 2023
Keywords: 
Statistics/methodology, Statistical methods, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc.