Meet the Founder: Milo LeGendre, LMHC

Milo LeGendre, LMHC is a thought leader and trailblazer in behavioral healthcare, pioneering the integration of artificial intelligence and visual analytics to transform clinical practice. As a Licensed Mental Health Counselor and current PhD student at National University studying Psychology, Social Policy, and Behavioral Health Administration, Milo combines hands-on clinical expertise with cutting-edge research to address one of healthcare's most pressing challenges: making data actionable for practicing clinicians.

The Research Foundation

During his doctoral studies, Milo immersed himself in the growing body of evidence highlighting critical gaps in behavioral health practice. His research revealed a troubling disconnect: while systematic reviews by Lloyd et al. (2019) demonstrated that routine outcome monitoring and feedback on client progress are associated with positive treatment outcomes, many therapists struggle to engage meaningfully with client data in ways that inform treatment decisions.

The problem wasn't lack of data — it was accessibility and interpretation. Milo understands that therapists are often overwhelmed by well-intentioned data sets that are essentially numbers on a computer screen, siloed in different compartments of vast electronic medical records. Research by Azizian Kia et al. (2024) confirmed that therapists are more likely to engage with data presented in clinically meaningful, visually intuitive formats conducive to self-reflection.

This convergence of evidence pointed to a clear solution need: data visualization that leverages human visual processing capabilities to decrease cognitive load and speed up decision making (Parikh et al., 2021). Inspired by how the scholarly literature was clicking for him, Milo wanted to find a way to combine his clinical expertise, technology, and data science to solve problems he experienced in the field.

The Clinical Innovation Journey

Drawing from his on-the-job clinical experience, Milo began experimenting with technology to bridge this research-practice gap. As he piloted visualization tools using de-identified client data from his caseload, he experienced what he describes as "a transformative form of routine outcome monitoring." Visualizing patterns in client PHQ-9 scores and attendance data allowed him to identify when interventions coincided with symptom improvements — and critically, when they did not.

The "Internal Call to Action"

This process created what Milo calls an "internal call to action" — visualized data sparked deeper clinical inquiry about treatment adjustments, therapeutic alliance factors, and evidence-based practice fidelity. Rather than data collection being a procedural task, interacting with visualizations fostered deliberate clinical reflection and adaptation, directly addressing the implementation barriers identified in his research. Milo believes that data-visualization in behavioral health creates a "motivating experience" within clinicians.

Innovation Through Research

Chartara Labs represents a novel approach to clinical decision support that synthesizes Milo's research findings into practical solutions. The platform addresses the core challenge identified by Lloyd et al. (2019): transforming routine outcome monitoring from overwhelming data dumps into accessible clinical insights.

Mission: Democratizing Data-Driven Therapy

Recognizing the transformative impact these tools had on his own practice, Milo founded Chartara Labs to disseminate these innovations to clinicians nationwide. Chartara Labs emerged from Milo's recognition that the future of mental health care lies in minimizing friction and maximizing insight — turning raw data into centralized, easily interpreted visuals that empower therapists and clinical supervisors to make truly data-driven decisions.

References:
Azizian Kia, S., Wittkampf, L., van Lankeren, J., & Janse, P. (2024). Motives of therapists for using routine outcome monitoring (ROM) and how it is used by them in clinical practice: Two qualitative studies. Administration and Policy in Mental Health and Mental Health Services Research, 52(2), 159–170.

Lloyd, C. E. M., Duncan, C., & Cooper, M. (2019). Goal measures for psychotherapy: A systematic review of self‐report, idiographic instruments. Clinical Psychology: Science and Practice, 26(3), Article e12281.

Parikh, N., Daughton, A., Rosenberger, W., Aberle, D., Chitanvis, M., Altherr, F., Velappan, N., Fairchild, G., & Deshpande, A. (2021). Improving detection of disease re-emergence using a web-based tool (RED Alert): Design and case analysis study. JMIR Public Health and Surveillance, 7(1), e24132.