This is the code and configuration for our paper, OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients
- The paper is here
- Raw model outputs, including charts, crosstabs, etc, are in
released_analysis_results/ - If you are interested in how we defined our covariates, take a look at the study definition; 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 codelists, look in the codelists folder. A new tool called OpenCodelists was developed to allow codelists to be versioned and hosted online at www.opencodelists.org. The tool allows agreed codelists to be pulled into a repository by running a Python command. More information available in the README of the codelist folder
- Developers and epidemiologists interested in the code should review DEVELOPERS.md.
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.