Allowing developers to generate random data based on their study expectations. They can then use this as input data when developing analytic models.
Supporting downloading of codelist CSVs from the OpenSAFELY codelists repository, for incorporation into the study definition
What is OpenSAFELY
Working on behalf of NHS England we have now built a full, open source, highly secure analytics platform running across the full pseudonymised primary care records of 24 million people, rising soon to 55 million, 95% of the population of England. We have pursued a new model: for privacy, security, low cost, and near-real-time data access, we have built the analytics platform inside the EHR data centre of the major EHR providers, where the data already resides; in addition we have built software that uses tiered increasingly non-disclosive tables to prevent researchers ever needing direct access to the disclosive underlying data to run analyses; code is developed against simulated data using open platforms before moving to the live data environment. Everything has run smoothly. We are fully live inside TPP; we are signed off with full data access and end-stage tech development for the computational platform with EMIS.
This is the repository for the OpenSAFELY job runner. A job runner is a service that encapsulates: the task of checking out an OpenSAFELY study repo; executing actions defined in its project.yaml configuration file when requested via a jobs queue; and storing its results in a particular locations.
The documentation is aimed at developers looking for an overview of how the system works. It also has some parts relevant for end users, particularly the project.yaml documentation.
This is the code for the OpenSAFELY job server designed for mediating jobs that can be run in an OpenSAFELY secure environment. The Django app provides a simple REST API which provides a channel for communicating between low-security environments (which can request that jobs be run) and high-security environments (where jobs are run).
OpenPrescribing and DataLab Papers
It has been a busy month for paper publication at The DataLab. We have written a brief description of the most recent papers below. Please sharewith colleagues and [get in touch(mailto:[email protected])if you have any relevant observations! Remember you can read all our academic papers related to OpenPrescribing on our research page.
Methotrexate Prescribing Safety – New paper in BJGP
This week the British Journal of General Practice published our latest paper on unsafe prescribing of methotrexate. We found that the prevalence of unsafe methotrexate prescribing (10mg tablets) has reduced but remains common, with substantial variation between practices and CCGs. In the paper we also discuss recommendations for better strategies around implementation.
OpenSAFELY is a new secure analytics platform for electronic health records in the NHS, created to deliver urgent results during the global COVID-19 emergency. OpenSAFELY is a collaboration between the DataLab, the EHR group at London School of Hygiene and Tropical Medicine and TPP who produce SystmOne. OpenSAFELY is now successfully delivering analyses across more than 24 million patients’ full pseudonymised primary care NHS records. The first analysis from OpenSAFELY is Factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients with more answers to important questions expected shortly.
OpenPrescribing.net has been updated this week with the latest release of prescribing data covering March 2020. In-depth analysis will be needed over the coming months, but this release gives us the first glimpse into the impact that COVID-19 has had on prescribing. At the DataLab we have been quite busy with the new secure analytics platform OpenSAFELY but the following blog is a rapid analysis of the March prescribing data which others may find helpful to focus their own investigations. As always, all our analytical code is openly available on our GitHub for inspection and reuse by anyone.