An Introduction to Open-Source Modelling and Version Control for Decision Modelling

Ready to bring Clarity in the Chaos in Uncertain Times?

28 June 2026, 1:30 PM – 4:55 PM | 13:30 – 16:55 (local time)

Faculty

  • Eline Krijkamp, PhD – Assistant Professor, Health Technology Assessment, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Netherlands
  • Wael Mohammed, PhD – Assistant Professor (Health Economics); Dark Peak Analytics & University of Sheffield, United Kingdom
  • Ron Handels, PhD – Health Economist and Epidemiologist, Maastricht University, Netherlands
  • Robert Smith, PhD – Director, Dark Peak Analytics, United Kingdom
  • Xavier Pouwels, PhD – Assistant Professor, Health Technology & Services Research, University of Twente, Netherlands

Course Overview

Decision models are routinely used to inform health policy decisions. However, the source code of these models is often not publicly available, which limits transparency and may negatively affect public and patient trust in model outcomes. In addition, the lack of accessible models prevents reuse for future decision making and leads to duplication of effort across the field.

Open-source modelling practices provide a more transparent and efficient approach to model development by promoting freely available, reproducible, and well-documented code. These practices are gaining traction in health economics and decision science.

Although decision scientists frequently take methodological courses, many are self-trained in coding workflows. The increasing use of programming languages such as R and Python, combined with the desire to share models openly, has led many to use platforms such as GitHub. However, evidence suggests that many shared models lack proper documentation, structure, or licensing.

This course introduces participants to open-source modelling practices and emphasizes version control as a core component of model development. Participants will learn how version control supports tracking changes, enhancing collaboration, and standardizing modelling workflows to improve transparency and accessibility in health economic models.

Learning Objectives

Participants will learn how to:

  • Use version control systems to support the development and use of decision models
  • Explain the differences between version control approaches when working individually versus collaboratively
  • Apply good practice principles in Git and GitHub for version control
  • Describe differences between software licenses and select appropriate licenses for their own models

Course Format

This half-day course includes lectures, demonstrations, and applied exercises.

Participants will be introduced to open-source modelling concepts, followed by practical sessions focused on:

  • Version control for individual projects (“gitting” alone)
  • Collaborative workflows (“gitting” together)
  • Publishing and licensing models (e.g., CRAN, Zenodo)

The course will include code review, demonstrations, and opportunities to apply concepts through exercises.

Participant Requirements

Participants should have:

  • A basic understanding of programming languages (e.g., R or Python)
  • Familiarity with decision modelling methods (e.g., decision trees, state-transition models, infectious disease models, or discrete-event simulation)

Prior experience developing models or access to personal modelling code is helpful but not required.

Participants are encouraged to bring a laptop with the latest versions of R and RStudio installed, although it will also be possible to follow along without coding directly. personal modelling code may be helpful but is not required. Participants are encouraged to bring a laptop with test versions of R and RStudio installed, though it will also be possible to follow along with demonstrations without coding directly during the session.