BIDS-BCHSI Research Xchange Forum — Algorithmic Stewardship
Date: Monday, December 7, 2020
Time: 12:30-1:30 PM Pacific Time
Location: Virtual Participation
Register to receive the virtual access link.
Speaker: Steph Eaneff, MSP, Data Science Health Innovation Fellow
Abstract: The use of AI/ML algorithms in clinical practice holds promise for improving the diagnosis, treatment, and management of disease. However, when used inappropriately, algorithms also have the potential to perpetuate existing biases and reinforce underlying patterns of structural inequality. To mitigate this risk, researchers, clinicians, and hospital administrators require clear processes for auditing algorithms prior to deployment and for monitoring their continued use. In this talk, Steph will discuss preliminary and ongoing work to conduct a series of algorithm audits at UCSF, including audits of widely used mortality prediction tools. She will review lessons learned from these initial audits, and will highlight the ways in which observational data from electronic health records can be used to help ensure that clinical algorithms are used safely, effectively, and fairly.
The BIDS-BCHSI Research Xchange Forum is an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science. Participants are invited to engage in a variety of activities, including presentations of work-in-progress, discussions and critiques of recent papers and AI methods in healthcare, introductions to new tools and methods, and opportunities to foster new collaborations. Invited speakers include leading voices in AI and Healthcare, and active conversations invite participants to share fresh perspectives. Clinicians and physicians with an interest in data science methods and tools, as well as data science faculty and researchers with applications or interests in the healthcare and health sciences, are welcome and encouraged to participate. Regular participants will also include the I4H Fellows, as well as post-docs, staff, and faculty from UC Berkeley, UCSF, and Johnson & Johnson. The immediate goals of this Forum are to share our current research projects with a wider audience, and to increase engagement and improve communication among the three host organizations. Meetings are held virtually on the first Monday of each month at 12:30-1:30 PM Pacific Time, and interested members of the UC Berkeley, UCSF, and Johnson & Johnson communities are invited to use this registration form to receive the schedule and access links. Please contact InnovateForHealth@berkeley.edu for more information.
Stephanie Eaneff is a data scientist with expertise at the intersection of public health and and public policy. She joined BIDS and BCHSI/UCSF in Fall 2019 as part of the first cohort of Data Science Health Innovation Fellows in the Innovate For Health program, having previously worked on a variety of interdisciplinary research teams including PatientsLikeMe, the New York Times machine learning team, Gryphon Scientific, and Talus Analytics. Steph holds a master’s degree in statistical practice from Carnegie Mellon University and a bachelor’s degree in biochemistry from UCLA.