From prevention to treatment: Designing personalised healthcare operations through analytics

From prevention to treatment: Designing personalised healthcare operations through analytics

EVENT DATE
27 January 2026
TIME
9:00 am 10:00 am
LOCATION
SUTD Data Analytics Lab (Building 1, Level 6, Room 1.610)

Healthcare extends beyond the clinical setting; it is a complex system where patients navigate interconnected stages of prevention, diagnosis, and treatment. In this talk, I provide an overview of my research, which examines healthcare systems through the lens of the patient journey. My works are grounded in collaborations with hospitals and public health agencies in Singapore and leverage real-world data alongside a blend of empirical and analytical methods.

I specifically highlight a project in preventive care: a large-scale randomised controlled trial investigating how information sharing improves cancer screening uptake. Most notably, we find that sharing screening process information significantly boosts intentions, whereas clinical information has no significant impact. This result along with others inform the design of personalised preventive care.

Papers/Articles
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4858824

Speaker’s profile

Wang Xiaodong (Frank) is a Research Fellow at the Lee Kong Chian School of Business, Singapore Management University, where he also earned his PhD. His research specialises in healthcare operations management, focusing on the intersection of system design and patient behaviour. Through close partnerships with healthcare practitioners, his work addresses high-impact operational challenges, including cancer screening promotion, outpatient no-show management, surgeon assignment, and care delivery in intensive care units. Methodologically, Frank employs a multi-disciplinary approach that includes empirical methods (randomised controlled trials and causal inference), sequential decision-making models (partially observable Markov decision processes and multi-armed bandits), and machine learning. His research aims to bridge the gap between analytical modelling and practical, data-driven solutions for modern healthcare systems.

For more information about the ESD Seminar, please email esd_invite@sutd.edu.sg
 

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