Artificial intelligence (AI) tools are rapidly expanding into clinical medicine, integrating clinical data to provide decision support. Phenotypes and case-finding algorithms are routinely used by health systems and insurers to incentivize cost-effective care. But what does deep integration into clinical information systems promise? Will this liberate the physician's attention to the relational work of clinical psychiatry and improve outcomes for patients and communities? Or might it streamline structural injustices in health care while alienating clinicians from their patients? As AI tools are now capable to intersect at scale with accuracy in attention to psychological and behavioral data, psychiatrists must be leaders in deciding wisely whether and how to implement and govern them. This review will illustrate the technology, example applications, and implementation trials, while discussing quality improvement and governance principles for AI in phenotyping and case-finding for psychiatric conditions in emergency, inpatient, and outpatient care across medical and psychiatric settings.
Taylor Black (Wed,) studied this question.