JMIR Publications

ABSTRACT

Background:

Mental health conditions account for significant distress, burden, and societal costs. Despite efforts to implement evidence-based practices, access to high quality mental health treatment in general practice remains limited, and clinical outcomes sub-optimal. Measurement-based care (MBC) is a transtheoretical and transdiagnostic strategy that has the potential, when implemented effectively, to improve the quality of care. Digital tools can also support clinicians by alleviating administrative tasks and providing in-the-moment performance data and clinical decision support. In this study, we examine the clinical outcomes of a technology-enabled psychotherapy practice, where clinicians are supported by a suite of innovations including an MBC platform, clinical decision support tools, and tools designed to alleviate administrative burden.

Objective:

The current study examines client retention and depression and anxiety outcomes within a technology enabled psychotherapy practice.

Methods:

This retrospective cohort study examines 2,984 adults who initiated mental health treatment with Two Chairs, a hybrid technology enabled behavioral health provider, between January 1 to June 30, 2024. Rates of reliable change, recovery, remission, and magnitude and trajectory of symptom change in depression and anxiety symptoms were assessed using the PHQ-9 and GAD-7.

Results:

The population demonstrated high rates of retention in care (89.9%), as well as high rates of MBC survey completion (96.3%). From baseline to the 12th session, patients showed significant symptom improvements in depression and anxiety, achieving high rates of reliable improvement (65.8%) and recovery (53.2%). Aggregate clinical outcomes continued to improve up to the point of termination. Pre to post-treatment effect sizes were large (all Cohen’s d’s > 0.9).

Conclusions:

This study demonstrates how technology-enabled measurement-based care and clinical decision support systems may drive high quality patient outcomes in mental health. Implications for healthcare costs and value-based payment models are discussed.