Digital Health Hub for AMR delivers training to NHS clinicians
The Digital Health Hub for AMR, in collaboration with the UK Health Security Agency (UKHSA) and UCL’s Centre for Advanced Research Computing (ARC), successfully delivered a new 5-day workshop focused on equipping clinicians with core skills in reproducible data science.
Designed and delivered by specialist research technology professionals from ARC, the training brought together participants from UCLH NHS. While centred around AMR, the course was intentionally structured to support surveillance and analytical workflows across a wide range of public health and research domains.
Building foundations in R for reproducible analysis
The first three days introduced participants to the R programming language, RStudio, and Quarto. Sessions focused on building strong foundational coding skills and promoting best practices for reproducible analysis - such as modular workflows, automation and encapsulating tasks clearly.
Participants worked with synthetic AMR datasets to explore real-world examples without the pressure of using sensitive or operational data. Many attendees reported that the pace, clarity of explanation, and hands-on structure made R feel more accessible, even for complete beginners.
“The course built my confidence in using R from scratch.”
“Really helpful introduction - everything flowed logically.”
Applying version control and database concepts
The second part of the workshop introduced Git, GitHub and core principles of collaborative version control. Attendees learned how to track changes, publish code and work with remote repositories directly through RStudio.
The course concluded with an introduction to SQL and working with databases. Participants practised interacting with an SQLite database from within R, enabling them to apply structured query language to extract and manipulate surveillance data more efficiently.
Feedback from participants was highly positive across all areas of the course. Attendees highlighted:
· Clear explanations and highly supportive instructors
· Useful hands-on exercises
· A good balance between beginner-friendly material and challenging concepts
· Immediate applicability to their work in surveillance and epidemiology
Many emphasised how learning R, Git and SQL would improve the reproducibility, efficiency, and transparency of their analyses.
Akish Luintel, Consultant in Infectious Diseases and General Medicine at UCLH said: "The practical introduction to R, Git, and SQL has given us tools that will immediately strengthen the way we analyse and interpret microbiology and AMR data. The training was clear, supportive, and directly relevant to our day-to-day work, and I’m confident it will help us produce more reproducible, transparent and impactful analyses going forward.”
The Digital Health Hub for AMR is committed to strengthening capability across the AMR research and policy landscape. This workshop represents a key step in supporting clinicians to adopt modern, robust and reproducible workflows.
Given the strong demand and positive feedback, the Hub plans to explore opportunities to run this training again and develop further capacity-building programmes in digital health, analytics and computational skills.
