Clinical and Research Informatics Data Strategy for Precision Oncology

Abstract

Overview Oncology informatics in the era of precision oncology is challenging because no unified comprehensive system exists linking Health Information Technology (HIT) deployed in clinical settings to the translational needs of researchers. Many advanced informatics solutions have been developed for clinical trials, biobanking, cancer imaging, and high‐throughput‐omic technologies. These are fundamentally transforming the treatment and management of cancer patients. However, the lack of fully developed interoperable cancer research informatics and HIT technologies to move between the bench and the bedside remains a significant challenge. Oncologists and translational cancer investigators require knowledge of informatics, data science, and advanced machine learning (artificial intelligence) as these are the major change agents influencing the development of new therapies, especially in the era of Precision Medicine and Learning Health Systems for oncology. In addition, cancer care delivery is very dependent on new developments in clinical practice and requires a thorough, systematic reevaluation of the electronic health records (EHRs) in use today. The ability (through mobile computing) to have information “on demand” during daily oncology practice is reshaping our thinking of how we record, document, and share data toward the common purpose of improving cancer outcomes for the patients we serve. This article looks at HIT and clinical, translational, and research informatics for oncologists and cancer researchers and begins to paint a picture of what an “ideal” environment for cancer care delivery would look like to support Precision Oncology and Learning Health Systems.