This article presents a practical one-page AI decision record designed for five-person behavioral-health practices, covering scope, data boundaries, human review ownership, exception logging, and stop conditions.
This article explains how a small behavioral-health practice redesigned human review of AI outputs so that it functions as more than a checkbox, including concrete design principles and a dual-review sequence.
This article presents a lightweight exception log for AI pilots in small behavioral-health practices, covering formal exceptions, near-misses, "we got lucky" moments, and the weekly review that makes the log useful.
This article provides a practical structure for explaining an AI workflow to a clinician who did not participate in its approval, emphasizing boundaries, the decision record, and professional responsibility.