Further Resources

Curated links for continuing your R for HTA journey

Books and Online Textbooks

R for Health Technology Assessment by Gianluca Baio, Andrea Berardi, and Anna Heath is the definitive textbook on using R for HTA. It covers survival analysis, decision modelling, network meta-analysis, population adjustment, discrete event simulation, and Shiny applications. An online version is freely available.

Decision Modelling for Health Economic Evaluation by Andrew Briggs, Karl Claxton, and Mark Sculpher (Oxford University Press, 2006) remains the foundational reference for the modelling concepts used throughout this workshop — decision trees, Markov models, PSA, and value of information analysis.

Organisations and Consortia

DARTH — Decision Analysis in R for Technologies in Health is a multi-institutional collaborative that develops transparent, open-source solutions for decision-analytic modelling in R. Their coding framework paper (Alarid-Escudero et al., 2019) provides a structured approach to building reproducible HTA models.

R-HTA Consortium is an academic consortium that promotes the use of R for cost-effectiveness analysis. They host annual workshops, webinars, and maintain a growing library of tutorials and recorded talks.

R-HTA in LMICs is the low- and middle-income country chapter of R-HTA, particularly relevant for analysts in the Indian and South Asian context. Their workshops and tutorials are tailored for settings with limited prior R exposure.

R Consortium HTA Working Group brings together stakeholders from industry, HTA bodies, and academia to develop best practices for using R in HTA analytics for both clinical assessment and economic evaluation.

R Packages for HTA

The following packages form the core ecosystem for health economic evaluation in R. All are available on CRAN.

Package Purpose Links
heemod Markov cohort models with PSA, heterogeneity analysis, and time dependency CRAN
dampack Analysing and visualising health economic model outputs — CEA, EVPI, EVPPI, CEAC CRAN / GitHub
BCEA Bayesian cost-effectiveness analysis — CE plane, CEAC, EVPI, expected loss CRAN / GitHub
hesim High-performance simulation (cohort, partitioned survival, individual-level) with built-in PSA CRAN / Documentation
flexsurv Flexible parametric survival models (Weibull, Gompertz, generalised gamma, splines) CRAN
survHE Survival analysis wrapper integrating frequentist (flexsurv) and Bayesian (Stan/INLA) approaches CRAN / Paper (JSS, 2020)
darthpack DARTH coding framework template for structured, reproducible CEA projects GitHub / Documentation

Indian HTA Resources

ParCC — Parameter Converter and Calculator for Cost-effectiveness is an R-based tool developed at RRC-HTA, AIIMS Bhopal. It helps HTA analysts convert and calculate parameters commonly needed in cost-effectiveness analysis — for example, converting between rate and probability, estimating transition probabilities from hazard ratios, deriving distribution parameters (Beta, Gamma, Log-Normal) from mean and confidence intervals, and computing discounting. ParCC is available both as an interactive Shiny web app and as an installable R package.

Health Technology Assessment in India (HTAIn) under the Department of Health Research coordinates HTA activities across Regional Resource Centres in India.

Tutorials and Short Courses

Key Published Papers

These papers provide the methodological foundations for the techniques covered in this workshop:

  • Alarid-Escudero, F. et al. (2019). A need for change! A coding framework for improving transparency in decision modeling. PharmacoEconomics, 37(11), 1329–1339. PMC
  • Baio, G. & Dawid, A. P. (2015). Probabilistic sensitivity analysis in health economics. Statistical Methods in Medical Research, 24(6), 615–634.
  • Briggs, A., Claxton, K. & Sculpher, M. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press.
  • Fenwick, E., O’Brien, B. J. & Briggs, A. (2001). Cost-effectiveness acceptability curves — facts, fallacies and frequently asked questions. Health Economics, 10(7), 605–615.
  • Husereau, D. et al. (2022). Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022. Value in Health, 25(1), 10–31.
  • Incerti, D. & Jansen, J. P. (2021). hesim: Health economic simulation modeling and decision analysis. arXiv:2102.09437.

Getting Help

When you get stuck (and you will — everyone does), these are good places to ask questions: