We Are Expanding What Counts as Data
Artificial intelligence is transforming healthcare in remarkable ways. Today, AI is trained on information such as clinical trials, imaging and diagnostic data, treatment protocols, clinical workflows and population-level outcomes
These datasets are essential. They power advances in diagnosis, treatment, and clinical decision-making. But as AI becomes more integrated into the patient experience, a new question is emerging: Are the tools we are using aware of the full picture of what it means to be a patient?
Because alongside clinical data, there is another form of intelligence—one that is rich, consistent, and deeply human. It’s patient lived experience, and I’ll venture it is one of the most underutilized assets in healthcare today.
What Patient Lived Experience Adds to Clinical Insight
Clinical data tells us what a disease is, how it progresses and how it is treated
Patient lived experience tells us how a diagnosis is received, how patients and theri caregivers interpret risk and uncertainty, how individual and family decisions are actually made, what support is needed in real time and what living with a diagnosis or chronic illness is really like.
Both clinical data and patient lived experience datasets are critical. But only one has been systematically integrated into AI systems to date.
When I was diagnosed with breast cancer, the clinical information I received was accurate and necessary. But it didn’t fully address the questions I was carrying. I found myself asking:
“Am I going to be okay?”
“Am I going to die?”
“How do I tell my children?
“How do I navigate the emotions of others around me?”
“What happens to my life now?”
That gap is not a failure of medicine. I had terrific medical care. Rather, it is a reflection on how complex the human experience of illness really is. The answers to those patient lived experience questions came from conversations with others who had been through breast cancer.
The Interpretation Layer in Healthcare
The World Health Organization has long identified health literacy as a key driver of outcomes. But literacy is not just about access to information—it’s about understanding, context, and confidence. That is informed by patient lived experience.
You can explore their work on health literacy here: https://www.who.int/health-topics/health-literacy
Similarly, the Canadian Medical Association has highlighted that patients are increasingly turning to digital tools, including AI, to help interpret health information:
https://www.cma.ca/about-us/what-we-do/press-room/doctors-warn-canadians-are-turning-ai-health-information-and-it-hurting-them
Research reviews reinforce that limited health literacy is linked to poorer health outcomes and lower engagement: https://pmc.ncbi.nlm.nih.gov/articles/PMC1492599/
And a study published in JAMA Network highlights how patient comprehension directly impacts adherence and outcomes: https://jamanetwork.com/journals/jama/article-abstract/2826616
Even broader system reviews, such as those from Agency for Healthcare Research and Quality, emphasize that improving understanding is central to improving care quality:
https://www.ahrq.gov/health-literacy/about/index.html
Together, this research points to an important evolution: The next frontier in healthcare is not access to information. It is interpretation, and interpretation is shaped by context, accessibility, relationships, and empowerment. In other words, a deeper understanding of patient lived experience data.
Patient Lived Experience Is Structured, Valuable Data
In healthcare, patient lived experience is often described as “anecdotal.” But when viewed at scale and as a large, unstructured dataset, it is a potential goldmine of knowledge.
Lived experience is pattern-rich across patient populations, consistent in how people respond to diagnosis and uncertainty, predictive of engagement, adherence, and decision-making
It reveals when patients feel overwhelmed. Why they delay or avoid decisions. Why they engage (or don’t) in care. How trust is built—or lost. And what information is most useful and usable. Lived experience is not a replacement for clinical data. But it can be a powerful complement to it.
What This Means for AI in Healthcare
As AI moves closer to the patient—through conversational tools, digital companions, and navigation platforms—its role is expanding. AI is no longer just informing, analyzing and recommending. It is increasingly supporting, guiding and translating information for patients and caregivers.
To do this effectively, AI must account for both clinical accuracy and the true human experience of a diagnosis.
When these two datasets are combined, something important happens. Information becomes more relevant, understandable and actionable by the patient and their caregivers. Furthermore, patients and caregivers feel more confident and supported, and have the agency to be more engaged in their care journey.
The CARE Model™: Context as the Starting Point
CARE Model™ is a framework for human-centered AI in healthcare, and the first pillar is Context. Before we can deliver the right information to an individual in care, we need to understand where that patient is emotionally, what other challenges they are navigating, and what this moment means in their life. Clinical data tells you what is happening. Context tells you what it means to that person.
Read the full framework here:
The CARE Model™: Why AI in Healthcare Must Be Built on Lived Experience, Not Just Data
https://askellyn.ai/the-care-model-ai-based-on-lived-experience/
The AskEllyn Approach: Lived Experience for Conversational Care
AskEllyn was designed to fill the lived experience gap. By offering patients and caregivers with lived experience insights and empathetic understanding, delivered through conversational delivery, AskEllyn meets patients and caregivers where they are, translates information in meaningful ways, supports information understanding, not just access. She is also private, available 24/7, in every language offering a place of psychological safety for users. Through knowledge enhancement, AskEllyn can also serve as a digital concierge, guiding users to the exact information or resource they need, at exactly the right time.
To explore how emotional and cognitive responses shape patient experience, you may also find these helpful:
This is not about replacing clinical expertise; this is about extending support for patients and caregivers beyond the four walls of the clinic—into the moments between appointments, or at 2 AM, where patients are making sense of their experience.
A More Complete View of Care
The Alice L. Walton School of Medicine, founded in 2024, takes a fresh approach to medicine. It was established to reshape medical education with a focus on whole health and meaningful community change.
In a similar vein, as we look ahead, the opportunity with the CARE Model and the bringing of patient lived experience into view is not to change the approach to clinical data. It is to expand the system’s definition of data to include human experience, emotional patterns and real-world decision behavior.
Final Thoughts
AI is rapidly reshaping the future of healthcare and the patient experience. The question is not just whether it is or will be accurate. We should also ask what matters to the person who receives that information,
Continue the Conversation
This article is part of a broader framework on human-centered AI.
Read the full CARE Model™ here:
https://askellyn.ai/the-care-model-ai-based-on-lived-experience/
Citable Insights
- Lived experience is a critical but underutilized dataset in healthcare
- Clinical data and lived experience are complementary—not competing
- The next frontier in healthcare is interpretation, not access
- Context determines whether information is usable
- AI must integrate both clinical accuracy and human experience
