Better research, improved patient confidentialityWhy OpenSAFELY?
OpenSAFELY is a highly secure, transparent, open-source software platform for analysis of electronic health records data. All platform activity is publicly logged. All software for data management and analysis is shared, automatically and openly, for scientific review and efficient re-use.
We never let researchers download patient data, and OpenSAFELY tools let users to write code to analyse patient data without even needing to view the raw records.
Auditable by the public
It is a privilege to use patient data for the public good. OpenSAFELY respects patients by carefully considering this in every part of its design.
Better, open science
OpenSAFELY requires publication of all analytic code, and our tools drive all users to produce prespecified, reusable, testable, shareable and modular software for research.
Enabling high volumes of research
Over 22 published research outputs to date, with many more in progress.
OpenSAFELY is revolutionising the way we work with health data. The initiative has already delivered major contributions to public health during the COVID-19 pandemic. But OpenSAFELY also leads the way in terms of transparency, open working methods, and a uniquely secure data access model.
Open for research
We are currently working with NHS England to cautiously on-board a small number of external pilot users to develop their analyses on OpenSAFELY. This first wave of pilot users will be collaborators, working closely alongside us to co-develop the platform.Read about our pilot onboarding process
Python, R and Stata
Choose any of these languages to write your analytic code
Primary care data
Our deployment for NHS England uses primary care data to research questions related to the Covid-19 emergency
A commitment to open ways of working
We believe transparency and open working methods are key to earning public trust and improving research quality
Latest from the blog
Why did we create a new query language?
The OpenSAFELY Collaborative has won a prestigious CogX Award for the Best Innovation in Open Source Technology
In this blog, we describe the development of a set of key measures used to monitor the ongoing impact of the COVID-19 pandemic on primary care as part of the OpenSAFELY Service Restoration Observatory (SRO). The results from this work have now been published in eLife.
Here we introduce the Bennett Institute’s Information Governance team, explaining who they are, and what they do.
Our new paper describes some of the biases that exist when estimating COVID-19 vaccine effectiveness using routinely-collected health data, and discusses the use of target trial emulation to avoid or mitigate these biases.
An introduction to what clinical codes are, why they are used and the terminology systems used within OpenSAFELY work.