Smart Foundations: Enhancing Patient-Centered Qualitative Research Through Responsible Innovation

Recruitment for this study required careful coordinationdue to the conditions burden and the population’s geographic dispersion. The client needed a way to ground their qualitative approach in meaningful patient context before conducting interviews, without adding burden or extending timelines.

KJT used AI-supported analysis to review a broad set of existing qualitative inputs, including, anonomymized transcripts, open-ends, secondary research, and caregiver narratives. This allowed our researchers to:

• Identify early themes related to emotional, functional, and logistical burden
• Highlight areas patients frequently struggled to express
• Uncover contextual factors (e.g., lifestyle limitations, decision barriers) that would shape interview design
• Map variation across patient and caregiver experiences

Every finding was reviewed, validated, and interpreted by experienced qualitative researchers with therapeutic expertise, ensuring outputs remained accurate and human-centered.

These early insights helped strengthen the qualitative research by:

• Refining the discussion guide to probe more effectively into emotional and contextual areas
• Prioritizing themes that patients identified as most impactful
• Increasing moderator preparedness for sensitive topics
• Enabling deeper, more empathetic conversations during live interviews

The result was a richer, more grounded understanding of the patient experience, allowing the client to make better informed decisions earlier in the research process.

AI-supported analysis doesn’t replace qualitative research, it elevates it. By giving researchers a clearer view of the emotional and practical realities patients face, it ensures that live conversations are more meaningful, efficient, and aligned with the needs of those living with the condition.