Kathryn A. Phillips, Ph.D. is Professor of Health Economics at UCSF and Founding Director of the UCSF Center for Translational and Policy Research on Personalized Medicine (TRANSPERS). Her expertise is on the implementation of new technologies to improve healthcare. She conducts research that spans multiple disciplines including basic, clinical and social sciences, and brings together leading experts in academia, industry, healthcare, payers, and government. Kathryn is considered one of the world’s leading experts on the economic and coverage issues relevant to the translation of personalized/precision medicine into clinical care and health policy. She has published ~150 articles in major journals, including JAMA, the New England Journal of Medicine, and Health Affairs, and has led NIH grants for over 25 years including the first NIH Program Project Grant funded by NCI in this area. Most recently, Kathryn was awarded a unique NIH Fellowship to become one of the first researchers to focus on the economic implications of "Big Data" – the aggregation and analysis of data across diverse sources using artificial intelligence and other approaches – and the trend towards "Precision Health".
Precision Health offers an opportunity to achieve "high value care" through innovative approaches. However, in order to fulfill this objective, we must demonstrate its economic value, someone must be willing to pay the costs, and there has to be data available to provide the needed evidence. In this talk, I will draw on my research over the past decade examining (1) how to measure the value of complex technologies such as Precision Health, (2) what payers cover and how they decide to provide coverage, and (3) how Big Data can be leveraged. I will also describe "lessons learned" about successful adoption from working with dozens of start-ups, VCs, and biotech companies. The talk will illustrate these issues using the case study of "liquid biopsy" – a potentially transformative technology that illustrates both the opportunities and challenges for Precision Health.