AI with a heart: combining technology with empathy to better understand rare diseases
Soumya Roy, Founding Partner, Integro
Mike Page, CEO, Phebi
In the evolving landscape of healthcare, artificial intelligence (AI) is making significant strides – not just in diagnostics and treatment but also in understanding patient experiences. Together with voice and emotion analysis AI company, Phebi, we have pioneered a new approach that combines AI with primary research to uncover deeper insights into patient experiences of rare diseases.
The barriers to advancing rare disease research
Rare disease research faces several persistent challenges that limit progress. Patients are hard to reach via traditional research methods, particularly when quantitative information is needed. The small and dispersed nature of these patient populations make it difficult and costly to gather sufficient data, leading to gaps in understanding and delays in diagnosis. Traditional research methods also often rely on structured surveys and self-reported data, which may not fully capture the lived experiences of patients as they often navigate a complex and emotionally charged healthcare journey.
The best of both worlds
We leveraged what we call a 3D Approach – Discover, Define, Deep Dive. This provides a structured framework for gaining richer insights into rare disease experiences.
The Discover phase involves leveraging AI-driven social media scraping and sentiment analysis to explore the vast wealth of online information and identify emerging themes and patient sentiment.
The Define stage finalizes research needs, target audience, and generates key hypotheses.
Then we Deep Dive into these AI findings through empathetic primary research for broad (quantitative) insights and deep (rich qualitative) understanding. It allows us to identify pain points and opportunities to add value.
By combining AI generated insights with the depth and empathy of primary research, we transformed the understanding of rare disease patients and their experiences – extracting meaningful narratives that reveal patterns of struggle, resilience, and the profound impact of rare diseases on daily life.
The Role of AI in Capturing Emotional Insights
Traditional research methods rely on structured surveys, which can sometimes miss the nuanced emotions behind patient experiences. Phebi's AI-driven voice analysis and sentiment detection tools bridge this gap, capturing not just what patients say, but how they say it. By analyzing vocal tones, pauses, and inflections, AI can detect levels of stress, hesitation, and other emotional indicators that provide a deeper understanding of patient concerns.
For example, a patient describing their struggle with Covid-related breathing issues may sound resilient in their words but reveal exhaustion and frustration through their tone. AI helps researchers recognize these subtleties, leading to more personalized and compassionate care strategies.
The proven benefits of a mixed method approach
AI does not have to be purely clinical or impersonal. When matched with empathy, AI can amplify patient voices, making them heard in ways that were previously impossible. By combining technology with human skills and primary research, we can better understand, support, and ultimately improve the lives of those living with rare diseases.
This mixed method approach is still cost-effective and scalable. It allows for a more comprehensive view of rare disease patients: bringing their stories to life, providing a deeper understanding of rare diseases, and addressing patients’ unmet needs and challenges.
The future of AI in healthcare is not just about automation and efficiency – it’s about connection, understanding, and making healthcare more human. By leveraging a mixed method approach, we can build a system that truly listens to patients, ensuring that their needs and emotions are at the forefront of medical advancements.