End of SummeR Meetup: R meets Health

This evening, we look at R and healthcare from three angles: how SWICA, a major health insurer, uses data to shift towards value-based care, how the Swiss Health Observatory uses R to plan and allocate resources across cantons, and how Swisstransplant uses statistical modelling to understand and predict organ transplants.

Join us for an exciting evening on analytics in healthcare, and for the apéro!
The meetup will be hosted by SWICA at the Hotel Banana City, Winterthur

****
Schedule:

• 18:15 opening doors, registration
• 18:45 Introduction (R User Group)
• 18:50 R for an efficient and qualitative health care system (Eva Blozik, SWICA)
• 19:00 R for health policy planning - from Copy Paste to Pipelines (Jonathan Zufferey and Reto Jörg, OBSAN)
• 19:40 R for predicting kidney transplant success (Simon Schwab, Swisstransplant)
• 20:10 apero
• 21:30 closing

****

! Please note that the number of participants is hard capped at 60 including organizers and speakers. Please use the meetup registration and waitlist if necessary to help us plan and withdraw if you cannot make the event.

**** Talks ****

Prof. Dr. Eva Blozik, Head of Healthcare Management at SWICA

R for an efficient and qualitative health care system

Eva will introduce how data analysis drives value-based care from an insurer's perspective.

****

Dr. Jonathan Zufferey, Scientific Project Leader at OBSAN
Reto Jörg, Scientific Project Leader at OBSAN

R for health policy planning - from Copy-Paste to Pipelines

Cantonal health reports
Every five years, the Swiss Health Observatory (OBSAN) produces analyses based on the Swiss Health Survey (SHS), providing each canton with detailed insights into the population's health, behaviours, and care utilisation.
In the past, these analyses were published in reports that were created by exporting SAS analyses into Excel and then manually inserting them into Word — a tedious process that had to be replicated for every canton. In 2024, the team transitioned to a fully integrated and automated workflow using R and Excel. This shift enabled them to simultaneously generate both a web-based output and a pdf report.

Primary Care Monitoring System
This project examines regional disparities in access to primary care services in Switzerland using a Floating Catchment Area (FCA) approach developed by the Obsan. Healthcare provider capacity is estimated from health insurance claims data, while healthcare demand is modelled using population characteristics and commuter flows. Accessibility is assessed using travel times derived from road network data, with DuckDB used to process it efficiently.

****

Dr. Simon Schwab, Statistician at Swisstransplant

R for predicting kidney transplant success

In Switzerland, 292 deceased-donor kidney transplants were performed in 2025, while over 880 patients remained on the national waiting list at the end of the year. Although kidney transplantation has excellent outcomes, graft loss remains a major concern for patients and clinicians.
This talk presents the KIDMO project (Kidney Prediction Model), a statistical model to predict graft loss. Simon will explain the model development and validation pipeline, and demonstrate how these clinical prediction models can be translated into practical tools, including an R package and an online risk calculator built with Shiny, Quarto, and Posit Connect Cloud.