Traditional research often relies on administrative claims or single-source registries, which lack the clinical depth and longitudinal perspective needed to fully understand disease progression and treatment impact.
Research challenge
Researchers needed a platform that could:
- Follow COPD patients across all healthcare settings
- Capture rich clinical measurements alongside medication use and outcomes
- Enable robust longitudinal and epidemiological analyses
Our approach
Our approach combined rigorous epidemiological design with advanced statistical modeling to explore the temporal relationship between COPD exacerbations and subsequent cardiovascular (CV) events in a large, incident patient population. Using the Dutch PHARMO Data Network—a comprehensive real-world database linking general practitioner, hospital, and pharmacy records—we constructed a retrospective cohort of individuals aged ≥40 years with newly diagnosed COPD, carefully confirmed through medical coding, spirometry, hospitalization records, or GOLD classification to ensure diagnostic accuracy. Comorbidity clustering used unsupervised machine learning on multidomain data.
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