Health Technology Assessment using R

Background

Health technology assessment (HTA) informs decisions about which health technologies to adopt and fund, but it depends on rigorous, reproducible decision-analytic and economic modelling that few clinicians and policy-makers are formally trained to perform. R offers a free, transparent, and fully reproducible environment for building these models end to end. This Workshop on Health Technology Assessment (HTA) using R was designed to give participants practical, code-based skills in health-economic modelling, lowering the barrier to conducting credible HTA.

Approach

The workshop was delivered as a 2-day hands-on programme at the Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), Thiruvananthapuram. Sessions paired concept introductions with guided coding in R, working through the core HTA modelling toolkit: building decision trees, constructing Markov models, running probabilistic sensitivity analysis (PSA), conducting and visualising cost-effectiveness analysis, and assembling interactive HTA reports. The programme was aimed at public-health professionals, health economists, policy-makers, and postgraduate students.

What we found

Participant learning outcomes include the ability to:

• Structure and build decision-tree models for HTA in R.
• Construct and run Markov (state-transition) models.
• Implement probabilistic sensitivity analysis (PSA) to quantify uncertainty.
• Conduct cost-effectiveness analysis and visualise results.
• Produce reproducible, interactive HTA reports.

Outputs & impact

The workshop produced a full set of session materials, hands-on exercise scripts, and worked modelling examples spanning decision trees, Markov models, PSA, and cost-effectiveness analysis. It was delivered over two days at SCTIMST, Thiruvananthapuram, on 9–10 September 2025, equipping public-health professionals, health economists, policy-makers, and postgraduate students with reproducible HTA modelling skills in R.