useR! 2026

From Administrative Data to Interactive Healthcare Benchmarking: An End-to-End R Workflow

7 Jul 2026, 16:15

5m

Lightning Talk (5 minutes) Lightning Talks

Speaker

Janez Bijec (University of Ljubljana / Statistical office of Slovenia)

Description

Routine administrative data collected by healthcare payers hold significant potential for monitoring care quality, yet translating them into actionable insights requires careful statistical modeling and thoughtful communication. This talk presents a complete R-based pipeline — from raw reimbursement data to an interactive Shiny dashboard — developed to benchmark hospital performance for coronary artery disease care in Slovenia.
We walk through four stages of the workflow, each presenting distinct R-specific challenges. First, data quality assessment using tidyverse tooling to evaluate conformance, completeness, and plausibility of administrative records not originally intended for research. Second, dimensionality reduction via exploratory factor analysis to construct municipality-level contextual variables. Third, risk-adjusted benchmarking using generalized linear mixed effects models fitted with glmmTMB — including multilevel logistic, negative binomial, and Gamma regression — followed by indirect standardization to produce fair provider comparisons across 14 hospitals. Finally, dashboard development in Shiny, where we discuss design decisions for presenting statistically complex outputs to non-technical healthcare stakeholders in a transparent and interpretable way.
The resulting dashboard compares 13 key performance indicators across five care domains for 14 hospitals and 212 municipalities, with interactive filtering, confidence interval visualization, and regional mapping. We share practical lessons on structuring a Shiny app around mixed model outputs, communicating uncertainty to domain experts, and the broader challenge of secondary use of administrative data in R.
Attendees will leave with transferable patterns for building reproducible, model-driven dashboards in R for real-world institutional use.

Additional Material or Paper

Yes – a version focused primarily on statistical methodology and healthcare implications (without detailed emphasis on the R/Shiny implementation) was presented at the Applied Statistics conference under the title “Developing a Dashboard of Key Performance Indicators for Coronary Artery Disease Care Using Administrative Data in Slovenia.”

If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.

Generative AI (Claude Sonnet 4.6 by Anthropic) was used solely to assist with English phrasing, structure, and formatting of the abstract. All research, statistical analysis, Shiny development, methodology, results, and scientific content originate entirely from the author's master's thesis. The author has reviewed every sentence and takes full responsibility for the final text.The AI assistance was specifically employed to create a new version that differentiates from the author's previous presentation … with stronger emphasis on the R and Shiny technical implementation details for the useR! audience."