The Intellus Summit had a great turnout this year, which made it especially nice to connect with new people and reconnect with old colleagues. In a time where so much of our work happens over Zoom, it was nice to finally meet people I’ve collaborated with for years in person.
This year’s theme, From Instinct to Insight, feels especially relevant right now. We are all being pushed to move faster, adopt new tools, and still preserve the depth that actually makes insights meaningful, often with fewer team members to do it.
A few sessions have stayed with me.
The Medicare session from Astellas was one of the most grounding. It was an education on Medicare, the options available, and the decisions people have to make. Medicare is often talked about in technical or policy-heavy terms, but this made it real. It highlighted the complexity that people, often older patients, are navigating every day.
In the work we do, many patients are supported by government-funded healthcare, which adds another layer of complexity to the patient experience. There are so many factors shaping access and treatment decisions that go beyond the clinical itself, and those are not always fully understood.
This session reinforced how complex the system actually is. It is not just “I have Medicare.” There are multiple decisions people have to navigate, and each one carries real implications for their care.
Staniel Saraos from Jazz Pharmaceuticals also left an impression. She spoke about integrating patient-centered insights, but what resonated more was the intentionality behind it. Insights do not create value sitting in a report. They have to be connected across functions and brought to life in a way that helps them stay with people inside an organization.
What came up in discussion at the table is how difficult that has become in practice. With teams increasingly remote and communication defaulting to virtual, it is harder to create the kind of shared experiences that make insights stick. Add in the pace most teams are operating at, and even carving out a couple of focused hours is a challenge.
When that space is not created, the work often defaults back to slide presentations. That may be efficient, but it often falls short of creating real alignment.
As moderators, we are personally gathering these stories. We are sitting with patients and healthcare professionals as they share their experiences, often in a very real and vulnerable way. They are giving us their time and their trust, and that comes with a responsibility to make sure their stories are understood and remembered by the people who need to act on them.
One of the more thought-provoking sessions was Ideology as Identity in Healthcare from Reservoir Communications Group. It touched on how identity shapes perceptions of healthcare and pharma, including political ideology as one of many factors.
What struck me is how much this has evolved. In the past, we would not have looked at something like political ideology as a meaningful lens in understanding healthcare decision-making. Now it is part of the conversation, but it is only one piece of a much bigger shift.
People are forming perspectives in very different ways than they used to. Experiences over the past few years, especially during Covid, have influenced how people think about healthcare, trust information, and make decisions, but those views are not static.
At the same time, people are operating in increasingly narrow information environments. You can effectively optimize your algorithm to reinforce a specific point of view, which shapes what you see, what you trust, and how you interpret and decide on healthcare.
What feels most important is understanding what is shaping how people perceive healthcare and make decisions, and recognizing how quickly that is evolving.
And then there was AI.
It is already embedded across the ecosystem, whether we are talking about patients, physicians, or the work happening inside organizations. What is more interesting is not that it is being used, but how quickly it is becoming part of how people access information, interpret it, and make decisions.
That shift is starting to show up in a very real way inside pharmaceutical and research organizations.
AI is often framed as a way to drive efficiency, which can quickly become a conversation about reducing headcounts. But the value of this work still depends on people. People to interpret, to connect, and to bring insights to life in a way that others can understand and carry forward.
If AI is used well, it should free up time. Time that could be reinvested into more thoughtful, experiential work. The kind of work that creates shared understanding and stays with teams beyond a presentation. But that requires a different mindset at an organizational level. It is not about using AI to replace people. It is about using AI to enable people to do more meaningful work.
In the end, the thread across all of this is that both the tools and how people make healthcare decisions are changing. We need to adapt thoughtfully. Looking forward to carrying some of these ideas forward in the qualitative work we do.