Decision Making in Health and Medical Care
Modeling and Optimization
May 17-21, 2021
Andrew Lo (Sloan School, MIT) and Thaleia Zariphopoulou (Mathematics and Business School, University of Texas at Austin)
One of the most challenging set of decisions facing individuals and institutions today involves personal health and medical care. Breakthroughs in biomedical science and engineering have delivered life-saving therapies that were impossible just a few years ago, but at a cost of a million dollars per dose in some cases, making these therapeutics unaffordable to a number of patients and smaller self-insured employers. The decision-making processes for balancing medical needs with economic incentives and the complexity of the healthcare system are fraught with social, ethical, and political dimensions that most stakeholders are not equipped to address.
The purpose of this workshop is to bring together key representatives from all those stakeholder communities to develop a better understanding of these decision-making challenges and propose new approaches to address them. Topics will include i) measuring and incorporating patient preferences in the drug approval process, ii) applying data science and device discovery and development, biopharma investments, and healthcare delivery, iii) disruptive technologies for facilitating telemedicine and crowdsourced diagnoses, iv) innovative financial engineering solutions to funding biomedical innovation, and v) new approaches to pricing, access, and universal healthcare coverage.
The workshop will serve as a platform for mathematicians, statisticians, computer scientists, economists and medical doctors to discuss and debate about the modeling challenges, and the development of new techniques and quantitative areas to study such complex interacting systems.
Registration will open soon.