AI Algorithms Used in Healthcare Can Perpetuate Bias
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Speaker: Dr. Michelle L. Rogers, Ph.D.
Data, Innovation, and Community Engagement Distinguished Lecture Series
Introduction
In this lecture, Dr. Michelle L. Rogers explored how data captured in electronic medical records (EMRs) can improve birthing outcomes for Black women and advance equitable maternity care. Her presentation highlighted how midwives can leverage both big and small data, alongside clinical expertise, to promote better health outcomes and address systemic disparities in maternal care.
Key Insights
- Leveraging Patient Data: Leveraging patient data from EMRs, clinical expertise and the latest evidence, midwives can make informed care decisions that promote the best possible outcomes for mothers and babies throughout the maternity care journey.
- Understanding Data Impact: Understanding the impact of health care data (big and small) on work practices will be crucial to understand as the increase in use of AI in healthcare.
- Tracking and Managing Conditions: As healthcare services diversify, the ability to track and manage conditions in between clinical encounters, it will be key for managing multiple chronic conditions.
“Innovation is crucial in strategies that we use for leveraging patient data from EMRs, clinical expertise and the latest evidence, in order for midwives to make informed care decisions that promote the best possible outcomes for mothers and babies throughout the maternity care journey.”
Why It Matters
Dr. Rogers’s research underscores the importance of using data-driven insights to transform healthcare practices and reduce maternal mortality disparities. Her work emphasizes that integrating EMR data and AI responsibly can empower midwives and health systems to improve patient care, equity, and long-term maternal outcomes.
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