Creating treatment episodes of medications using PRE2DUP method – arranged by NORPEN

Date: 2 June 2026 

Time: 13:00–17:00 

Location: MH2 U.10.306, Floor 10, MH2 building, UiT- The Arctic University of Norway

Getting to the university from the conference hotel.

Mazemap QR code for the workshop room:

Session Responsibles: 

Leader(s) – Speaker(s): Heidi Taipale and Pia Vattulainen

Coordinator(s): Nhung Trinh and Jacqueline Cohen 

Assistant with R practical: Jinmei Chen

Short Description:PRE2DUP is an advanced method for generating drug use periods from drug purchases and PRE2DUP‑R is the new open-source R-implementation of it. PRE2DUP-R estimates drug use periods from drug purchases, based on dispensed amount and sliding average of daily dose. It utilizes package-level parameters, hospital care periods and personal purchase regularity over time. PRE2DUP-R can be applied to all medications, any drug form and different dispensing regulations. A key requirement for using PRE2DUP‑R is the construction of package‑level parameters—often the main challenge when applying the method. The course includes short presentations introducing the PRE2DUP‑R and package-level parameters, followed by hands‑on exercises. Participants will work in small groups (5–10 people) to design package‑level parameters, run the PRE2DUP‑R program in R, troubleshoot common errors, and explore advanced features. Exercises will use simulated Nordic register‑based data. Each group will present their solutions to the full group. 

Learning Outcome(s): By the end of the session, participants will learn:

1. The fundamentals of parameter design;
2. How to apply these parameters in practice; and
3. How to approach special cases and troubleshooting scenarios.

Requirement(s): Participants should have a basic understanding of pharmacoepidemiology and/or Nordic prescribed drug register data. A laptop with R and RStudio installed is required. Participants should also install the R packages:

• devtools from CRAN
• PRE2DUP-R from GitHub

Installing instructions: https://piavat.github.io/PRE2DUP-R/articles/introduction.html. 

Throughout the course, participants will have an excellent opportunity to receive guidance directly from the developers of PRE2DUP and PRE2DUP‑R. 

Pre‑reading: Introduction to PRE2DUP-Rhttps://pubmed.ncbi.nlm.nih.gov/41689954https://piavat.github.io/PRE2DUP-R/index.html

Program