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Project #111:
OpenSAFELY Interactive PILOT

OpenSAFELY is a powerful platform for analysing patient records in English primary care and other linked healthcare datasets. After rapid development at the start of the COVID-19 pandemic (March 2020), we launched a pilot programme to allow external research/informatics groups to use the platform for COVID-19-related questions. This has been highly successful; however, such project applications require a certain technical skillset, and there is a relatively long lead-time to start performing analyses; although feedback from users is that the onboarding time is relatively short compared with many platforms (typically 5-10 weeks), it is not possible to conduct any rapid analysis. While we are creating dashboards that show activity in selected clinical areas, we would like to permit some simple counts to be accessible more flexibly and widely, for example, for policy experts and other individuals involved in NHS service planning, commissioning, monitoring and best practice guideline development.

For the pilot phase, access will be provided to a defined group of NHS England policy makers. Once approved, individuals will be able to submit simple analyses, by selecting a clinical codelist (a list of clinical codes used to capture all the ways an activity or condition may have been recorded, e.g. a blood test or asthma) from the OpenCodelists tool. For the pilot phase, only codelists which have been used for existing OpenSAFELY COVID-19 related projects on will be incorporated into the tool. Users also select a time period and a small range of other options.

For the pilot phase, we propose the following category of analyses, returned to the requester within a simple PDF/html. The number of occurrences of the chosen codelist are counted over the selected time period and figures may include: a table of the most common codes within the codelist, variation in code use between practices per week/month, rates broken down by sex/age group/ethnicity/region. Patient counts will be rounded and small numbers suppressed to protect patient privacy. We will apply automated statistical disclosure controls where appropriate, and where necessary results will be reviewed prior to release by trained output-checkers. Practices will not be identified; except in cases where an appropriate governance approval has been granted, such as a practice requesting to identify only its own data within a graph of other practices.

Using this tool users will be able to: preview codelists; see which codes in a particular codelist are most often used; assess the change over time in a particular clinical activity; get an indication of the level of coding of conditions/activities of interest; or ensure an activity/outcome of interest is recorded in sufficient numbers to permit further analysis prior to submitting a full project application.

In the pilot phase, results are not publishable - but used to inform development of OpenSAFELY-Interactive.

  • Study lead: Helen Curtis
  • Organisation: NHS England and University of Oxford Medicine
  • Project type: Service evaluation
  • Topic area: Other/indirect impacts of COVID on health/healthcare