Comprehensive Summary
This study explored the clinical uses of an AI-enabled clinical decision support system (CDSS) for personalizing major depressive order (MDD) treatment. The CDSS included three components: access to patients data, a clinical algorithm module that provides the clinician with personalized treatment options for each patient, and an AI component that predicts outcomes based on the suggested treatments. The clinicians were split into the active group which had full access to all CDSS tools and the active-control group which had limited access to the tools. Although both groups began with the same baseline depression severity, remission rates were significantly higher in the active group (28.6%) compared to the active-control group (0%). It is important to note that the study was terminated early due to lack of funding.
Outcomes and Implications
Unlike previous studies that used AI in a binary classification of treatments, CDSS is a platform that supports treatment selection and management in accordance with guidelines, thereby more useful in clinical settings. These results suggest that AI-enabled CDSS platforms can improve the effectiveness of treatment and rate of remission in MDD cases.