Digital Health, Robotics & AI for Personalized Medicine: Economic Analysis
Arrival Date in Beijing, China: Saturday, August 24, 2024 (course begins August 26, 2024)
Departure Date from Beijing, China: Saturday, September 14, 2024 (course ends by evening September 13, 2024)
Location: Stanford Center at Peking University, Beijing, China
Instructor: Professor Karen Eggleston, Director of the Asia Health Policy Program, FSI Shorenstein Asia-Pacific Research Center, Fellow at the Center for Innovation in Global Health at Stanford University School of Medicine, and Faculty Research Fellow of the National Bureau of Economic Research
Eligibility: Undergraduate, Co-term, or Master's level Stanford students from any major or discipline who are interested in health policy, biotechnology, public health, applied microeconomics, “computer science for social good” or “stats for social good"; or PhD level Stanford students in the first couple years of a doctoral program interested in exploring the nexus between their discipline and health tech adoption (for example: CompSci and SoM global health and AI-assisted care, SoE applied bioengineering, GSE health ed tech, GSB social tech entrepreneurship, development economics, SLS biotech law).
Fees/Cost: Airfare, accommodations, and food are covered by the Stanford Center at Peking University. See details under "Program Cost."
Overview
Globally, health systems struggle to provide affordable access to high-quality care for all their citizens. As potential solutions, digital health, robotics and AI for precision health and personalized medicine hold both promise and peril. Digital health tools can provide affordable access for remote and vulnerable populations, and some applications of AI can enhance precision health strategies to address social determinants of health and promote cost-effective screening (e.g. for diabetic retinopathy) for healthy aging. Yet algorithms can be biased, tech can complicate life for busy health professionals, and personalized medicine can be very expensive, exacerbating rather than mitigating disparities. This seminar gives students a glimpse of health economics concepts and research about the trade-offs involved in integrating health technology and AI health applications into healthcare system workflows. This seminar combines field trips across China with lectures and guest speakers at the Stanford Center at Peking University to help students think through the following questions: 1. What is the evidence about how digital health initiatives and applications of deep learning to health services work in practice, in high- and in low-resource settings? 2. How do government agencies and health tech assessment bodies determine a new digital health or AI-enabled technology can be marketed and if it can be covered by insurance? How have health systems attempted to address concerns about data privacy and security? 3. What are incentive structures and provider skillsets needed to harness these technologies to improve health equity, health service quality, and health system resilience at an affordable cost?
During the seminar, students will be assigned to teams with their Stanford classmates and students from Tsinghua and Peking University. These student teams of US and Chinese students will choose a case study of health tech in practice in a high-income setting and a low-income setting. Each team will analyze evidence about the social value of their chosen technology and propose adapting it to a different setting in East, Southeast, or South Asia.
Application Process
The 2024 Summer Quarter application will open soon. Please look out for updates on our website.
For More Information
Please contact our Program Coordinator, Owen Raymond (oraymond@stanford.edu), with "SCPKU Seminar" as your email subject.