Optimizing Integrated Registries

Real-world evidence (RWE) and real-world data (RWD) have become buzzwords in the biopharmaceutical industry, comprising any number of definitions and considered key to numerous applications. When properly understood and managed, a real-world evidence strategy can be invaluable to life science researchers, particularly in the area of rare diseases — in this case, to create singular, integrated disease and product registries by combining independent registries and supplementing their data with information from secondary sources.
RWD typically relates to a patient's health status or delivery of healthcare, while RWE is clinical evidence about the usage and potential benefits or risks of medical products, derived from RWD. More digital healthcare data than ever before is available from an increasing number of sources. These huge volumes — combined with advances in medtech, IT infrastructure, and artificial intelligence (AI) — have encouraged greater democratization of healthcare data. However, many organizations lack the in-house expertise and resources to organize, analyze, or meaningfully draw conclusions from data.
Rare disease research — in part because of the small patient populations and patient variability within those groups — benefits greatly from data integration. In terms of patient population, rare disease research must glean as much information as it can from a limited sample size. Consider that rare disease in the U.S. is defined as a cumulative number (afflicting 200,000 or fewer people; the U.S. population is ~330M people), while the European Union (EU) defines a rare disease as one that affects ≤ 5 per 10,000 people.