Digital Measurement-based Peer Supervision Platform

An ongoing project (2024-Present).

A novel digital platform for measurement-based peer supervision of non-specialist providers conducting brief psychological interventions.


The Aim of the Study:

This study addresses the critical shortage of mental health providers by digitally supporting the deployment of non-specialist providers (NSPs) - such as community health workers, nurses, teachers, and peers in recovery - to deliver evidence-based brief psychosocial interventions. A key barrier to sustainable task-sharing is the availability of scalable, high-quality supervision. To address this, the team has developed a digitally-enabled version of the measurement-based peer supervision (MBPS) method, originally delivered in paper format, to support provider performance and quality assurance of care delivery. This project assesses the efficacy of that digital solution.


The Background:

Mental health disorders represent one of the most pressing and costly public health challenges of our time. Globally, depression and related conditions are a leading cause of disability, accounting for over $2.5 trillion in annual health spending - a figure projected to reach $6 trillion by 2030. In the United States, more than two in five adults report struggling with a mental illness, yet nearly 60% receive no care at all, and over 20% report inadequate treatment.

The primary driver of the treatment gap is a shortage of providers trained to deliver evidence-based psychological treatments. This is particularly acute in rural and low-resource communities. Critically, there is compelling evidence that NSPs can effectively deliver these treatments across diverse settings - including in primary and community care in the U.S. - yet a lack of scalable, quantifiable supervision methods remains a major barrier to sustaining care quality. This project directly targets both gaps: expanding the NSP workforce through digital tools, and ensuring their ongoing performance through measurement-based peer supervision.


The Project Plan:

  • Phase I (completed): In Phase I of this SBIR project, the team developed and usability-tested a prototype digital MBPS solution in Texas, informed by prior work with frontline health workers in India. End-user feedback was collected directly from NSPs working in underserved Texas communities who had recently been trained in Behavioral Activation (BA) treatment. Phase I demonstrated the acceptability and potential feasibility of digitally-enabled MBPS to support provider performance and quality of care.
  • Phase II (Ongoing)
    The overarching goal of Phase II is to enhance and assess the efficacy of digitally-enabled MBPS with NSPs already trained in and delivering BA in community settings. This will be accomplished through three specific aims:
    • Aim 1 - Enhanced App Development: Building an improved version of the MBPS app based on Phase I feedback, including a redesigned user interface, cross-platform support, automated flagging of high- and low-performing areas in peer review, improved data visualization, and preparation for integration with existing NSP systems. The team will also explore AI-powered session summaries to improve review efficiency.
    • Aim 2 - Mixed Methods Evaluation: Onboarding community health workers (N=50) trained in BA through the Baylor Scott and White Health System to use the MBPS app for peer review and supervision over 12 weeks. Primary outcomes include expert-assessed CHW competency in BA delivery and CHW self-efficacy; secondary outcomes include training satisfaction, peer engagement, and system usage.
    • Aim 3 - Cost Analysis: Conducting a cost analysis under varying implementation assumptions to build a cost calculator informing sustainability models and commercialization planning.


Supporters and Project Duration:

This study is funded by the National Institute of Mental Health through a Small Business Innovation Research grant (2R44MH130305-02). The study is led by Dimagi Inc. (PIs Neal Leash and Xian Ho) (2024-2026).


Findings:

An enhanced version of the MBPS app has been built and is now being tested within the Baylor Scott and White Health System in Dallas, Texas.


Next Steps:

The Harvard Medical School team is conducting a cost analysis for the system under different implementation rollout and volume assumptions.