Closing the Evidence Gap in Interstitial Lung Disease. The Promise of Real‐World Data

Abstract

The complexity of modern medicine generates an enormous number of clinical questions, resulting in an expanding evidence gap that cannot be addressed by traditional clinical trials alone. Simultaneously, today s health systems generate an unprecedented amount of routine health information, known as real world data . Advances in computing power and analytical capabilities have recently made it possible to transform real world data into evidence. In turn, real world evidence can inform medical decision making, improve individual and population health, and transform the relationship between clinical medicine and research. The potential to leverage real world data to generate knowledge is well illustrated in the study of interstitial lung disease, a group of rare lung diseases that are challenging and expensive to evaluate in the context of traditional trials. Harnessing the power of large, heterogenous, real world data cohorts enables investigators to improve our understanding of disease and disease management by addressing questions related to longitudinal outcomes, treatment risks and effectiveness. In this Perspective we review 1) sources of real world data and the process for converting data into evidence for use in clinical research; 2) prior and current applications of real world data to advance clinical research, using the field of interstitial lung disease as an example and 3) the challenges and opportunities for future, widespread use of real world data in clinical research - specifically technical, operational and cultural issues.