Use case 8: Documentation assistant

Description:

An AI-powered documentation assistant transcribes client sessions in real time. It generates structured summaries that highlight regularly occurring themes from the client and flags any missed therapeutic components from the care provider (for example, if they missed any questions they should have asked based on the structured intervention protocol).

Example scenario:

During a session, a care provider listens as a client describes ongoing struggles with motivation and daily routines. As the conversation progresses, the documentation assistant transcribes the discussion in real-time and highlights recurring themes such as “low mood,” “lack of engagement in activities,” and “avoidance.”

At the end of the session, the documentation assistant cross-checks the notes against the intervention manual and identifies that the care provider missed a goal-setting discussion, which is an important component of behavioral activation in CBT. The AI tool then generates structured session notes for the care provider that summarize critical client statements, outline intervention steps, highlight any omitted therapeutic components (in this case, the goal-setting discussion), and provide follow-up actions suggested for the next session.

After reviewing the notes, the care provider notices that there has been an increased sense of hopelessness in the client’s statements. To ensure timely support, they flag the session to be reviewed by a supervisor immediately and then save the session notes.

Opportunities unlocked:

The documentation assistant could address several challenges in mental health task sharing programs, including the following:

• Protocol drift. Care providers may unintentionally skip or alter processes during an intervention, especially in high-stress or high-volume settings. The AI tool could cross-reference session notes with evidence-based protocols to ensure that all essential components are covered and prompt follow-up actions are taken if needed.
• Limited, irregular session records or sparse documentation. Traditional paper-based or minimal documentation can hinder continuity and limit real-time feedback opportunities. Additionally, session notes can vary substantially between care providers, leading to inconsistent documentation and gaps in client history. The AI tool could transcribe sessions, organize structured data, and standardize notetaking formats to ensure accurate, detailed, and consistent documentation. This feature could reduce variability in notes, enhance continuity of care, lower the risk of provider burnout from administrative demands, and help supervisors to provide timely and targeted feedback based on comprehensive session records.

How could the end user(s) benefit from this solution?

The primary end users who would directly benefit from this solution are:

• Care provider. Care providers could benefit from automated notetaking, structured data organization, and protocol adherence checks. As a result, they could focus more on ensuring clients are engaged and maintaining high documentation standards.
• Supervisor. Accurate and consistent session records could help supervisors provide timely and targeted feedback to care providers. The AI tool’s structured data could allow supervisors to track progress and provide tailored coaching for the areas where providers need additional support.