Using Data-Driven Decision Algorithms and Real-World Data for Updating Clinical Practice Guidelines.

Abstract

Clinical practice guidelines often struggle to stay updated, especially as cancer care becomes more personalized. We transformed guidelines into data-driven Clinical Decision Algorithms (CDAs) and compared Dutch and US CDAs, enriching the Dutch version with real-world data from the Netherlands Cancer Registry. An interactive dashboard was developed to automate guideline comparisons, adherence analysis, and alternative treatment evaluations, enabling timely updates and more responsive, evidence-based care.