Important: Disclaimer

This is not the official site but a store of technical documents and ongoing work. Opinions expressed in posts are not representative of the views of NHS England and any content here should not be regarded as official output in any form. For more information about NHS England please visit our official website

NHSX is now part of the NHS Transformation Directorate - Learn more at https://www.nhsx.nhs.uk

Welcome

The NHS England Transformation Directorate Analytics Unit (formerly NHSX Analytics Unit) sees open ways of working as pivotal to increasing innovation and efficiency in the NHS. This site has been created so we can share some focussed technical thoughts and examples.

Within the unit we have analysts, data engineers, data scientists, developers, economists, and evaluation specialists. Here we will advertise public projects from all these disciplines as well as publishing thoughts on how healthcare analysts can interact with the open tools and data.

Innovation Research Areas

There are many areas of innovation that have huge potential for healthcare data. We are focussed on increasing the value we get from our data and what innovations could be put in place to support this. There are two ways to do this:

  • Create examples of applying novel techniques to data to demonstrate the art of the possible
  • Focus on creating accessible data and tooling which would allow others to do the first point.

Thus, whilst we are interested in conducting work focussed on a specific question, we see the value in spending just as much, if not more energy on creating useful data assests. To this end our research areas of interest are:

  • the best approach to synthetic data generation and evaulation to enable easier sharing of data for innovation
  • how to collate and Curate NHS-related text data sources into a training corpus which represents how NHS clinicains and patients talk about their health
  • demonstration of system and patient simulation methods such as disrecete event simulation and agent based modelling
  • how to define and deal with privacy concerns in text data and remote analysis using privacy enhancing technologies
  • methods for extracting insight from large scale event logs and multi-modal data using graph-based approaches
  • establishing open ways of working and supporting reproducible analytical pipelines across NHS analysts
  • applied forecasting with explainability

Within the AU, the innovation branch attempts to push forwards these research interests through our PhD Data Science Internship Scheme as well as internal projects to connect academia with NHS operations.