DATA FEASIBILITY ASSESSMENT

 

I perform rigorous data feasibility assessments using a structured and customizable evaluation framework designed to support study-ready decision-making. This approach allows for consistent, transparent, and reproducible assessment of data sources, vendors, and datasets against study-specific requirements.

 

My feasibility process evaluates multiple dimensions, including patient population coverage, longitudinal data continuity, endpoint and variable availability, coding consistency, data latency, and regulatory acceptability. I also assess operational factors such as data refresh frequency, linkage capabilities, and geographical representativeness.

 

The use of standardized yet adaptable tools enables side-by-side comparison of multiple data sources, supporting objective selection of the most appropriate datasets. These tools can be tailored to specific therapeutic areas, study designs, or regulatory expectations, ensuring flexibility without compromising rigor.

 

This structured approach reduces uncertainty early in the study lifecycle, minimizes downstream operational risk, and ensures alignment between protocol requirements and real-world data (RWD) capabilities. It ultimately enables faster, evidence-based go/no-go decisions and more robust study planning.