The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.
Keywords: Biotechnology; Evidence-Based Medicine; Information Technology; Medicine/Clinical Issues; Research And Technology.