aceArtificial Intelligence-Driven Clinical Decision Support for Postoperative Delirium Prevention: A Pragmatic Randomized Controlled Trial
Background Postoperative delirium affects up to 50% of older adults with cognitive impairment, yet preoperative identification of at-risk patients remains limited. Artificial intelligence methods, such as natural language processing, can extract cognitive impairment signals from electronic health records and enable targeted clinical decision support interventions to promote adherence to perioperative best practices and reduce postoperative delirium. We aimed to evaluate the effectiveness of an artificial intelli…
An AI-triggered, non-interruptive alert in the health record for surgical patients with cognitive impairment showed no significant effect on delirium incidence or on anesthesia teams' adherence to best practices.
Fewer than 20% of patients had documented delirium assessments because routine screening varied, so the authors say the trial cannot conclude the AI support was ineffective at preventing delirium.
Evidence
- Peer-reviewedAnesthesia & Analgesia2026-10-09
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Truvace Impact Record TRV-2026-1664, v1: “Artificial Intelligence-Driven Clinical Decision Support for Postoperative Delirium Prevention: A Pragmatic Randomized Controlled Trial.” Truvace, 2026-10-17. /record/TRV-2026-1664 (accessed at citation time). sha256 3f82e624c36c2d5a…
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