AI and the healthcare data logistics problem by Vera Mucaj

Title: AI and the healthcare data logistics problem
Abstract:
Healthcare decisions depend heavily on comprehensive, accessible data. Without these, patient outcomes may suffer. However, healthcare data is often fragmented across multiple silos, limiting its true utility. In this lecture, we will discuss healthcare data fragmentation, and how overcoming it can lead to better datasets that can be used to train and fine-tune AI models. We will explore the concept of "Real World Data" (RWD) - information gathered from routine healthcare activities and daily life, and the use case applications of RWD.
We will also address how AI tools and healthcare intersect in two important ways. First, AI can improve healthcare data through standardization, curation, and more. On the flip side, healthcare data can improve and fine-tune AI models. We will discuss the importance of using complete and representative data to train AI models to avoid bias, and ensuring compliance with privacy regulations like HIPAA and GDPR.
The session will conclude with some interesting predictions on the intersection of healthcare and AI. I encourage the class to think of your own predictions as well.
Bio:
Vera Mucaj, Ph.D.,
Chief Scientific Officer, Datavant
Vera is the Chief Scientific Officer at Datavant, where she leads cross-functional teams dedicated to advancing technology that powers health data logistics. As a Product leader, Vera has successfully guided the development and widespread adoption of technology supporting healthcare data connectivity through Privacy Preserving Record Linkages. Her subject-matter expertise includes the technical and use case considerations for linking clinical trial data to real-world data, and the creation of large-scale real-world data research databases in both the public and private sectors.
Vera is a research scientist by training, and holds a BA in Biochemistry from Harvard College, and a PhD in Cell and Molecular Biology from the University of Pennsylvania Perelman School of Medicine. She has authored multiple peer-reviewed scientific papers in cancer research. Prior to joining Datavant, Vera worked at McKinsey & Company, where she supported pharmaceutical clients on growth strategy, business development, and M&A.

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