Learning healthcare systems for cost-effective precision oncology.
Dr. Dean Regier (BC Cancer, University of British Columbia) and Deirdre Weymann (BC Cancer)
Thursday, 27 February 2020, 12pm to 1pm
Big Data Institute (BDI) LG 0 Seminar Room, University of Oxford Old Road Campus, Oxford, OX3 7LF
Hosted by HERC
Precision oncology aims to improve patient health through biomarker discovery and individualized patient care. In pursuit of individualization, precision oncology has amplified evidentiary uncertainty. In Canada, go/no-go decisions based on reference case economic evaluations and health technology assessment (HTA) are failing to stem intense clinician and patient demand for low-value precision oncology. Life-cycle health technology assessment (LC-HTA), which enables conditional patient access alongside continuous evidence development, is one approach to balancing demand and uncertainty with healthcare systems' sustainability objectives. LC-HTA is characterized by repeated, standardized, real-world data collection and analyses to guide appraisal, re-appraisal, and de-adoption. This seminar will describe a Canadian initiative for learning healthcare and precision oncology that is: developing an LC-HTA framework for managed access of early stage technologies; leveraging real-world data for continuous evidence generation; and applying machine learning to support health economic evaluation.
Dr. Dean Regier is a Scientist within Cancer Control Research, BC Cancer and the Canadian Centre for Applied Research in Cancer Control (ARCC), and an Associate Professor, School of Population and Public Health, University of British Columbia. Dr. Regier’s research focuses on understanding access to healthcare and improving methods to estimate the benefit of health care, with applications to genomic technologies and the ‘value of genomic knowledge’ i.e. how genes play a role in our personal lives and how publics value and trade between benefits and risks when making decisions to undergo testing. He incorporates this person-centred evidence into economic models that answer questions of equity and value for money.
Deirdre Weymann is a Senior Health Economist within Cancer Control Research, BC Cancer and ARCC. She holds a Master’s degree in Economics from the University of Victoria and a Bachelor of Science degree in Economics, Mathematics and Statistics from the University of British Columbia. Deirdre’s research focuses on preference elicitation and economic evaluation in the context of precision medicine. Her recent work uses quasi-experimental study design to evaluate genomic technologies outside of randomized controlled trials and considers the potential for machine learning to facilitate real-world data analysis.