How did you feel about the communication during your treatment?
Patient Experience Interview
Interviewer agent · 1.7K uses
Better care starts with hearing the whole patient story. A satisfaction score can't tell you what made care feel good or frustrating. This template runs an empathetic, one-on-one conversation with each patient — probing expectations, barriers, and the why behind their experience — so you can improve care. It gathers general experience feedback and steers away from protected health information.
Start from this conversation and adapt it to your team — change any question, add your own logic, and connect the tools you already use.
The core fields every response captures.
What was the best and most difficult part of your experience?
What would have made your care easier or clearer?
Follow-ups that change based on what people say.
If they mention a frustration, probe what would have made it better
If they start to share PHI, gently redirect to their general experience
Different paths for different answers.
Route recurring barriers to the patient-experience team
Direct positive feedback into what to protect and scale
Actions that fire the moment a response comes in.
Send recurring experience themes to the care team in Slack
Log each session's themes to a patient-experience doc in Notion
Post de-identified transcripts to your analysis pipeline via webhook
Define the experience or service you want feedback on. The empathetic AI moderator welcomes each patient, explores their experience and expectations, and probes what helped, what frustrated them, unmet needs, and barriers to care — adapting follow-ups to each answer. If a patient starts to share protected health information, it gently redirects to general experience. Themes are synthesized across everyone.
Define the experience, service, or change you want feedback on
Set an empathetic, supportive framing
Share the link with patients or a care population
Review synthesized themes, barriers, and improvement areas
A patient focus group gathers feedback from patients or care recipients about a healthcare experience, service, program, or proposed change. It explores their expectations, what helped or frustrated them and why, unmet needs, barriers to care, and reactions to a specific service. Traditional patient focus groups are hard to schedule and limited to a small room of voices. This template runs an empathetic, one-on-one conversation with each patient, adapting follow-ups to every answer, so you capture the full experience at scale and get synthesized themes in hours. It gathers general experience feedback and is designed to steer away from collecting protected health information.
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Go deeper on running AI focus groups to hear patients at scale.

The complete guide to running AI focus groups — why they work, when to use them, and how to get started.
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Concrete use cases for AI focus groups across teams — adaptable to patient experience research.
Read articleReplace drop-off, poor qualification, and missing context with AI conversations that capture structured data and real understanding. Set up in minutes.
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