Depression and Anxiety Outcomes in a Technology-Enabled Psychotherapy Practice: Retrospective Cohort Study.

Area of Science:

• Mental Health
• Health Informatics
• Clinical Psychology

Background:

• Mental health conditions impose significant societal costs and distress.
• Access to high-quality mental health treatment in primary care is often limited, leading to suboptimal outcomes.
• Measurement-based care (MBC) and digital tools offer potential solutions to improve care quality and efficiency.

Purpose of the Study:

• To evaluate patient retention and outcomes for depression and anxiety within a technology-enabled psychotherapy practice.
• To assess the impact of innovations like MBC platforms and clinical decision support tools on mental healthcare delivery.

Main Methods:

• A retrospective cohort study analyzed 2984 adults treated at a hybrid technology-enabled behavioral health provider.
• Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7) were used to assess depression and anxiety symptoms.
• Key metrics included retention rates, survey completion, reliable change, recovery, remission, and symptom trajectory.

Main Results:

• High patient retention (89.1%) and MBC survey completion (96.3%) rates were observed.
• Significant improvements in depression and anxiety symptoms were noted by the 12th session, with high rates of reliable improvement (65.8%) and recovery (53.2%).
• Overall, 79.2% of patients achieved improvement or recovery by the end of treatment, with large effect sizes (Cohen d>0.9).

Conclusions:

• Technology-enabled measurement-based care (MBC) and clinical decision support systems (CDSSs) show promise in supporting high-quality mental health outcomes.
• These integrated technological approaches can enhance patient retention and symptom improvement in mental healthcare.
• The findings suggest a viable model for improving the effectiveness and accessibility of mental health services.