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Artificial Intelligence Is Accelerating the Learning Health System – Can our Methods Keep Up?
ABSTRACT
Artificial intelligence is accelerating healthcare intervention development and implementation, compressing learning cycles. Without corresponding advances in learning methods, health systems risk missing opportunities for improvement or deploying interventions without sufficient inquiry to ensure appropriateness and safety. We propose a new operating model for health system learning that tailors the timing and intensity of inquiry to intervention risks and opportunities for safe learning while embedding rigorous, continuous evaluation within care delivery.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.