This is the code and configuration for our paper, "Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform".
- The paper has been submitted to medRxiv, and will appear here soon.
- Raw model outputs, including charts, crosstabs, etc, are in released_output
- If you are interested in how we defined our variables, take a look at the study definitions in analysis; this is written in
python, but non-programmers should be able to understand what is going on there - If you are interested in how we defined our code lists, look in the codelists folder.
The OpenSAFELY framework is a new secure analytics platform for electronic health records research in the NHS.
Instead of requesting access for slices of patient data and transporting them elsewhere for analysis, the framework supports developing analytics against dummy data, and then running against the real data within the same infrastructure that the data is stored. Read more at OpenSAFELY.org.
The framework is under fast, active development to support rapid analytics relating to COVID19; we're currently seeking funding to make it easier for outside collaborators to work with our system. You can read our current roadmap here.