Optimizing Behavioral Healthcare Delivery Through Technology

The need for scalable delivery of mental health care services that are efficient and effective is now a major public health priority. Artificial intelligence (AI) tools have the potential to improve behavioral healthcare services by helping clinicians collect objective data on patients' progress, streamline their workflow, and automate administrative tasks. The goal of this study is to determine the feasibility, acceptability, and preliminary efficacy of an AI platform for behavioral health in facilitating better clinical outcomes for patients receiving outpatient therapy. This open randomized clinical trial will compare an AI platform provided by Eleos Health to treatment-as-usual (TAU) during the first 2 months of therapy. The study will be conducted at a community-based clinic in the U.S. Participants will be adults referred for outpatient, individual cognitive behavioral therapy for a main diagnosis of a depressive or anxiety disorder. Patients will be randomized to receive either therapy provided with the support of an AI platform developed by Eleos Health or TAU at the same clinic. Data analysis will be carried out based on intention-to-treat principle. The primary outcomes include the feasibility and acceptability of the AI platform. Secondary outcomes include changes in depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) scores as well as treatment attendance and satisfaction. Findings of this study will inform the optimization of future trials and services offered to individuals seeking mental health support in the U.S.