Seminars

Abstract: AI has the opportunity to transform medicine and healthcare by supporting medical education, clinical research, healthcare operations, among other use cases. However, in these scenarios, it is imperative to optimize its utility while minimizing its risks. In this talk, we will discuss the unique needs and challenges of AI in health, define principles of data and AI governance, and review the Penn Medicine Data & AI Governance Committee framework that draws upon existing governance structures. We will present summary data from Data & AI governance submissions to date, highlighting trends in use cases, common risks, and institutional learnings. This presentation aims to offer a practical roadmap for others building or refining local governance structures in the age of healthcare AI.​

Bio: Dr. Danielle Mowery is a collaborative investigator that leverages artificial intelligence (AI) and computational methods to integrate and analyze information from unstructured and structured health data to help clinical investigators better understand disease burden, treatment efficacy, and clinical outcomes. Her work aims to uncover scientific discoveries, identify actionable healthcare knowledge, and optimize translation of research into patient care. As the inaugural Chief Research Information Officer for Penn Medicine, she directs the Clinical Research Informatics Core at the Institute for Biomedical Informatics – a key position designed to bridge the gaps between clinical data, research expertise, and actionable healthcare knowledge. Dr. Mowery represents Penn Medicine in local, regional, national, and international clinical research informatics communities, i.e., formerly, serving as co-chair of the Association of American Medical Colleges (AAMC) Group on Information Resources (GIR) and as co-chair of the Penn Medicine Data & AI Governance Committee and member of the Epic Cosmos Governing Council. 

Bio: Dr. Michael Horst leverages biostatistics, informatics, and data science to support health system outcomes research with particular expertise in big data, predictive and spatial modeling. He leads the Penn Data and Analytics (PennDnA) biostatistics core serving as a biostatistician for numerous investigator-initiated projects. In addition to his role as AVP of Data Science and Research for the University of Pennsylvania Health System, he serves as a research administrator and as vice-chair of the Institutional Review Board at Penn Medicine/Lancaster General Hospital as well as co-chair of the Penn Medicine Data & AI Governance Committee. He brings more than 25 years of experience in various administrative and technical roles within a hospital/health system.