Title: OpenSAFELY: how we addressed privacy and efficiency challenges to provision whole population GP data for researchers.

Biography: Ben is a doctor, academic, writer, and broadcaster. He trained in medicine at Oxford and UCL, in psychiatry at the Maudsley, and in epidemiology at LSHTM. His academic and policy work is in informatics, epidemiology and evidence based medicine, where he works on various problems including variation in care, better uses of routinely collected electronic health data, evidence-based social policy, access to clinical trial data, efficient trial design, and retracted papers.

He runs the Bennett Institute for Applied Data Science. This is a multidisciplinary team of academics, clinicians and software developers, all pooling skills and knowledge to turn large datasets into tools and services as well as pure academic research papers.

OpenSAFELY is a fully open source and highly secure analytics platform for NHS data created during the COVID-19 pandemic. It is currently executing code across an unprecedented scale of data: 58 million patients full raw GP records - 70 billion rows of information - linked onto various other sources including SGSS, SUS/HES, ECDS, ISARIC, ICNARC, ONS death, and more. All code for the platform, and for data management and analysis of each output, is shared under open licenses for review and re-use. OpenSAFELY has delivered a range of outputs in journals such as Nature, Lancet and the BMJ from a large national academic collaboration. 

All welcome

In OS6 Oakfield House or zoom