OpenSAFELY: secure access to data to deepen our understanding of COVID-19
The health and care system will look increasingly to trusted research environments (TREs), which are secure spaces where researchers can access sensitive data without breaching privacy. In-depth analysis can be undertaken on rich datasets without identifiable information ever being seen by researchers and analysts.
OpenSAFELY is a new secure analytics platform for research using patient health records. The platform uses a new model for enhanced security and timely access to data: data stays in the secure environment in which it is stored for individual care.
OpenSAFELY was established at the beginning of the emergency to enable major breakthroughs in COVID-19 research. So far it has identified key factors related to COVID-19 death including being male, older age, having uncontrolled diabetes and severe asthma.
Working on behalf of NHS England and NHSX, OpenSAFELY is a collaboration between the DataLab at the University of Oxford, the EHR group at London School of Hygiene and Tropical Medicine, TPP, Emis and other electronic health record software companies, who already manage NHS patient records.
Dr Alex Walker, lead researcher for the OpenSAFELY initiative
“Personally for me the pandemic highlighted a stark need to gather as much information about COVID-19 as possible. We needed to know what groups of people were most vulnerable, how the virus affected them, which drugs might help or hinder when treating patients and what happened to patients who recovered from infection. To answer these questions quickly, we needed an unprecedented amount of clinical patient data. At the DataLab in Oxford, our goal is to build data-driven tools and services for all to use and benefit from.
"This is when we developed OpenSAFELY. Knowing how sensitive patient data is, we needed to develop safe and effective ways of handling and processing it. The solution we came up with was to make sure that data analysis only happens within a secure and trusted NHS research environment. We also wanted to make sure that all code used for analysis in OpenSAFELY is publicly available, making the research more transparent and reusable.
"42 days after our first meeting to discuss developing such a system, OpenSAFELY came into being. Based on the medical records of 17.4 million adults, we produced a broad overview of the factors associated with COVID-19 deaths. Since our first paper, the outputs of the OpenSAFELY collaborative have been numerous. OpenSafely has been used for informing policy on shielding and vaccine prioritisation; we have added substantially to the evidence base for how several drugs, like hydroxychloroquine and inhaled corticosteroids are associated with COVID-19; and work on vaccine uptake has highlighted the large discrepancies in coverage between different ethnicities and socioeconomic groups. This impact will continue throughout the pandemic, for example with work on vaccine efficacy and long COVID follow-up.
"OpenSAFELY gives us the power to quickly respond to emerging clinical population health and policy challenges with precise data and open methods. Looking beyond the pandemic, we hope that the learnings from this project will change how we approach access to and analysis of data so that researchers can continue to provide immediate answers to extremely urgent questions in any future health emergency, while maintaining public confidence in the security of their data."