Healthcare Sandboxes Test AI and Data Sharing Before Full Rollout

Healthcare organizations are increasingly adopting sandbox environments to evaluate emerging technologies such as artificial intelligence. Utah’s sandbox permits companies to seek regulatory exemptions, allowing them to pilot select AI tools under state supervision. A case in point is Nola Health, which leverages AI to aid acne diagnosis and treatment over a 28-day cycle. The pilot includes escalation pathways to local dermatologists and initially requires two physicians to review AI actions, with oversight expected to decrease as safety benchmarks are met.

California’s sandbox, backed by Connecting for Better Health, centers on enhancing interoperability and data exchange between healthcare providers, insurers, and social service agencies. Leslie described a use case involving people experiencing homelessness. The sandbox revealed that health plans and county housing systems often lacked access to one another’s information, complicating efforts to connect individuals with housing and healthcare services. The work helped bring counties and health plans together to explore privacy-preserving ways to identify matching records and coordinate services.

Building trust requires more than technical testing. Regulators, healthcare systems, tech firms, and citizens must grasp the scope of testing, evaluation methods, and protective measures. Boyd stated his initiative earned trust by releasing data, inviting external experts, and refining pilot rules based on input. He also emphasized the importance of informing patients when they engage with AI systems and outlining how to report issues.

Independent reviews and ongoing monitoring after deployment are key components. Boyd noted that AI tools may function effectively in controlled tests but yield varied outcomes in real-world scenarios, necessitating sustained evaluation. Utah is developing governance guidance and evidentiary standards while exploring ways to coordinate oversight across states. California’s approach offers opportunities to reuse tested data-sharing practices across counties and healthcare organizations. The broader lesson, participants said, is that healthcare policies and technologies should be tested before large-scale deployment whenever possible. By creating space for controlled experimentation, transparent evaluation, and collaboration, sandboxes can help healthcare leaders reduce risk, improve interoperability, and move promising innovations toward safer, more effective use.