#  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.

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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.

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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.

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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.

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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).

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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.

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Next Steps:

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