Top Pitfalls Observed When Using Real World Data

Description

Real world data is increasingly being drawn upon by the Life Science industry to inform a broad range of business functions throughout the product life cycle, including clinical trial support, market insight, comparative effectiveness, understanding existing care standards and much more. And despite the richness of insight available through E.H.R and claims-based data assets, we sometimes encounter concerns from end users about the data quality, and its ability to support the analytic goals of an organization. Oftentimes, such complaints are the result of misconceptions around what RWD reflects vs. their desired analytic purpose.

This discussion will provide a useful snapshot into some common pitfalls we encounter when it comes to data interpretation, use and expectations – along with recommendations as to how they can be managed/avoided.