Patient Social Listening within Rare Disease with Shruthi Menon and Akansha Kumar

Rare disease patients typically wait years for an accurate diagnosis, often cycling through multiple specialists before anyone names what they have. That gap between symptom onset and diagnosis is exactly where Acceleration Point's Social Listening and Analytics team went looking when they built their ISPOR poster on Cushing's Syndrome.

Scott Thompson speaks with Shruthi Menon and Akansha Kumar (Acceleration Point) about that research. Social listening, the structured collection and analysis of patient-authored content shared publicly online, let their team trace the sequence of symptoms, misdiagnoses, and care-seeking behavior that patients described in their own words. Rare disease patients across Europe wait an average of 4.7 years for an accurate diagnosis, according to a Rare Barometer survey published via the National Institutes of Health (PMC), and Menon and Kumar's work looks at what patient-generated social content can add to understanding that gap. Menon and Kumar walk through their methodology, where the approach falls short as evidence, and where it could extend to other rare and orphan conditions. If your team is weighing whether social listening belongs in a patient-insights toolkit, this is a grounded starting point.

Key Takeaways:

• Social listening surfaces signals structured research misses. Patient-authored social content can reveal details about the rare disease patient journey that surveys and claims data do not capture.
• The ISPOR poster grounds the method in a real case. Menon and Kumar applied their methodology to Cushing's Syndrome, using patient posts to map the path from first symptoms to diagnosis.
• Methodology is the foundation, not an afterthought. The team built a structured process for collecting and categorizing patient-generated content rather than treating social listening as an informal scan of public posts.
• Limitations deserve the same attention as the findings. The conversation addresses where patient-authored social content falls short as evidence, including sample bias and the lack of clinical verification.
• The approach points beyond a single condition. Menon and Kumar discuss how the Cushing's Syndrome case study suggests broader applications for Medical Affairs teams studying other rare and orphan diseases.

Resources Mentioned

ISPOR Poster: Cushing's Syndrome Patient Journey Mapping: The poster presentation Menon and Kumar discuss throughout the episode, applying social listening methodology to map the rare disease patient journey. View the poster.

About Our Guests

Shruthi Menon is a member of Acceleration Point's Social Listening and Analytics team, where she works on applying social listening methods to uncover patient insights in rare disease.

Connect with Shruthi on LinkedIn: https://www.linkedin.com/in/shruthi-menon-288b3b97

Akansha Kumar is a member of Acceleration Point's Social Listening and Analytics team, where she works on applying social listening methods to uncover patient insights in rare disease.

Connect with Akansha on LinkedIn: https://www.linkedin.com/in/akansha-kumar-pharmd-msba-b1417911a

FAQ

What is social listening in a Medical Affairs context?
Social listening is the structured collection and analysis of patient-authored content shared publicly online, used to understand experiences and behaviors that traditional research methods may not capture.

Why is social listening useful for rare disease research specifically?
Rare disease patients often wait years for a diagnosis and see multiple specialists along the way. Patient-authored social content can capture that journey, including misdiagnoses and symptom progression, in the patient's own words.

What did the ISPOR poster on Cushing's Syndrome examine?
It applied social listening methodology to map the patient journey for Cushing's Syndrome, from symptom onset through diagnosis, using publicly shared patient content.

What are the limitations of social listening as a research method?
The episode discusses sample bias (not all patients share their experiences online) and the absence of clinical verification for what patients report, both of which limit how findings should be interpreted.

Curious how this applies to your organization? Let's talk.

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