Rohit Vashisht, PhD
Professional Researcher in Medicine, Bakar Computational Health Sciences Institute, UCSF
Emulating target trials offers a principled path to generate meaningful real-world evidence that can inform clinical practice and policy, yet the path from observational data to actionable insight is far from straightforward, fraught with challenges related to data quality, selection bias, and computational scalability. In this talk, we discuss our efforts to establish a framework for target trial emulation across UC Health, focusing on the comparative effectiveness and safety of second-line treatments for type 2 diabetes in a complex clinical data ecosystem of over 9 million patients. One step at a time, we aspire to help realize the promise of causal inference in medicine — for better evidence, and better patient care.