Leveraging a Learning Health System to Implement the DSM-5-TR Level 1 Cross-Cutting Measure in Real-World Mental Health Practices
The DSM-5-TR Level 1 Cross-Cutting Measure (DSM-XC) offers a comprehensive approach to assessing 13 domains of psychopathology through 23 questions, but its adoption in clinical settings has been limited. Through a collaboration between Osmind and the American Psychiatric Association (APA), we implemented the DSM-XC within Osmind's electronic health record (EHR) to evaluate its adoption in independent mental health practices over a 5-month period.
The study leveraged Osmind's Learning Health System, which continuously improves patient care by combining EHR capabilities, patient engagement tools, and systematic data collection. Implementation included educational content, social media campaigns, and in-product announcements to drive adoption, followed by usage tracking and feedback collection. Results showed rapid adoption across 115 practices, with 77% using the measure multiple times.
Usage increased significantly from 143 implementations in month one to 2,124 by month five, achieved through broad educational efforts and EHR integration alone. Average uses per practice reached 18.6 (SD=32.77). Among surveyed clinicians, 63% used it for initial visits, 30% for follow-ups, and 7% reported irregular use, with an overall usefulness rating of 6.6/10 (95% CI [4.72, 8.54]).
Clinician feedback highlighted key benefits including comprehensive screening capabilities during initial assessments, ease of use, patient acceptance, and ability to track progress like a psychiatric Review of Systems. Critical feedback identified needs for standardized score interpretation, built-in Level 2 measure administration following initial screening, and inclusion of ADHD domains in the adult version.
This implementation demonstrates how technology platforms can effectively support measurement-based care adoption in psychiatric practices. The success of this initiative suggests potential applications for validating composite endpoints in clinical trials focusing on symptoms rather than syndromes, with implementation techniques applicable to other measures of interest in mental health research and practice.