Health Economics in R Data Hack

On January 21st – 22nd 2020 at Queen’s University Belfast, we hosted the second health economics in R event – a workshop/hackathon/data dive mash-up. (Read about the first one here).

Generally, day one was aimed more at people new to health economics and R. Day two was aim more at those more familiar with health economic evaluation who were interested in creating new R tools to tackle problems in health economics large and small.

There was a lot of interest in the event beforehand and it was oversubscribed. Attendees came from academia, government, consultancies and industry, including UCL, University of Bristol, Glasgow and NICE amongst others. In particular, we had a lot of attendees from Ireland and outside of London which was one of our intentions. The Belfast hackathon website has more details about the structure of the two days and the aims.

Day 1

The day was structured as a series of introduction to health economics and healthcare evaluation lectures. This was lead by Dr Felicity Lamrock, and covered cost-effectiveness modelling, uncertainty and Markov modelling. The day ended with a demonstration of all of these things in R using the package heemod. The slides can be found on GitHub here.

It was also great to socialise with everyone at the evening meal at the end of the first day, following a hard days work, at the lovely Riddle Hall.

Day 2

The hackthon started with brief project pitches by several attendees. Following this, the participants split into groups to work on these or other projects proposed within groups.

The hackers were supported by our expert research software engineers Rob Ashton, Igor Siveroni and Giovanni Charles from Imperial College London.

Projects included:

• pdf2data – To take a pdf table of input data (from an HTA report) and wrangle it into a form for use in a cost-effectiveness model in R.
• Formatting-data-for-network-meta-analysis – Converting systematic literature review data for network meta-analysis.
• Creating shiny application for existing models.

We also had focused, advanced R skills sessions to up-skill current R users on Git and GitHub, Shiny, and package building in RStudio.

These meetings have been made possible by generous support from the Medical Research Council, Centre for Global Infectious Disease Analysis (Grant Reference MR/R015600/1), NIHR Health Protection Research Unit in Modelling Methodology and Imperial College London.