Report Released from the CRA-I Workshop on Healthcare Data Sharing
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Barriers to Sharing Healthcare Data Panel with Ronald Emeni (CRISP DC), Margarita Gonzalez (GTRI), and Peter Margolis (Cincinnati Children’s).
The Computing Research Association – Industry (CRA-I) recently hosted a Sharing Healthcare Data Workshop on October 17-18, 2024, in Washington, D.C., bringing together 35 experts from industry, academia, and government to tackle pressing challenges and opportunities in healthcare data sharing. Please see the just released workshop report here.
The event featured keynotes from Deborah Estrin (Cornell Tech) and Tom Kalil (Renaissance Philanthropy), panel discussions, and breakout sessions focused on the intersection of AI, healthcare regulations, and ethical considerations in data sharing. A major theme that emerged was the growing role of AI in healthcare and how misalignments between stakeholders—including researchers, healthcare providers, and policymakers—continue to create barriers to effective data sharing.
Key Topics Discussed
- Barriers to Sharing Healthcare Data – Challenges such as trust, data ownership, standardization, and regulatory constraints that impact effective collaboration.
- Connecting Health Models with AI – The potential of AI to enhance healthcare outcomes, but also the need for ethical and human-centered design in AI-driven systems.
- Navigating the Regulatory Landscape – Understanding the evolving AI compliance landscape and the role of government agencies in shaping healthcare data policies.
- Ethical Considerations – Addressing privacy, patient control, and the implications of emerging AI technologies in healthcare decision-making.
Next Steps & Key Takeaways
Workshop participants emphasized the urgent need for continued collaboration between healthcare providers, computing researchers, and policymakers to build trust, improve data access and standardization, and create responsible AI governance frameworks. The report outlines recommendations for fostering cross-sector partnerships, ensuring equitable access to data, and advancing innovative approaches to healthcare AI.
Please see the full report here.