In today’s healthcare landscape, understanding the patient journey is no longer a luxury—it’s a necessity. But as data sources multiply and patient experiences become more complex, the path to insight is anything but straightforward.

That’s why, in our latest episode of the Health Data Passport Webinar Series, we brought together a panel of global experts to explore one central question:
How can we better understand and act on the patient journey—no matter where in the world it begins?

What followed was a rich, cross-continental conversation that revealed not only the shared challenges we face, but also the innovative, AI-powered solutions that are helping us overcome them.

Challenge 1: Fragmented Patient Journeys

Patients today don’t follow a straight line from diagnosis to treatment. Their paths are winding, often crossing between public and private healthcare systems, leaving behind fragmented data trails that make it difficult to see the full picture.

In Brazil, Cristhiane Neves Gennaro (Principal, Real World Insights – Remit Latin America) described the challenge vividly: “We have the disease journey, the treatment journey, and the physician journey. But in countries with hybrid healthcare systems, patients move between providers. Having patient longitudinality in one place is one of our biggest challenges.”

In France, Ludovic Prevost (Principal, Consulting – Remit EMEA) added, “We now have access to such granular, longitudinal information that discovering the little signal that makes the difference is becoming more and more challenging.”

And in the UK, James Philpott (Director, Business Development – Remit EMEA) brought the patient’s voice into the conversation. “I’m wearing a Fitbit right now,” he said. “It’s recording my heartbeat, my sleep. As we work with Apple Watch and other vendors, we’re starting to access data that patients themselves are collecting. That can help optimise treatment and flag when a patient’s condition is worsening.”

These perspectives underscore the need for a solution that can unify these disparate data sources into a coherent, actionable view. That’s where IQVIA’s AI-Driven Patient Journey platform comes in. It integrates EMRs, claims, labs, wearables, and more into a single longitudinal view—giving teams the ability to follow patients across care settings and time. With real-time access to over 300 million patient journeys, the platform helps identify 3–5x more of the right patients, faster and with greater precision.

Challenge 2: Developing Patient Insights from Complex Data

As data grows in volume and complexity, so does the challenge of extracting meaningful insights.

In Brazil, Cristhiane Neves Gennaro noted the rise of AI adoption across hospitals, clinics, and payers. “We’re seeing health techs creating algorithms and supporting providers to put together their data and extract insights—especially using NLP tailored to local languages.”

In the USA, Anindya Banerjee (Managing Principal, Global Brand Insights Consulting) –emphasized the importance of understanding both the patient and physician journeys. “What does the physician need to make a decision? Literature? Peer insights? All of that impacts the patient journey.” Also Brian Hannah (Senior Principal, Global Patient Analytics and AI) pointed to platform-based solutions and generative AI as game changers. “IQVIA’s Patient Journey platform lets you dial down into very small groups of patients in any market. We’re overlaying Gen AI to compare and contrast groups and pull out the most relevant details.”

Challenge 3: Accelerating Insights into Patient Characteristics and Outcomes

Speed matters. But when data is fragmented, outdated, or locked in rigid reporting tools, insight generation slows to a crawl.

In the UK, Ed Banfield (Associate Director, Product & Strategy – IT Design & Development) explained: “We’re dealing with multiple sources—EMRs, labs, imaging, billing. Pulling them together, ensuring quality, and making them analyzable is a huge task.”

Over in the USA, Brian Hannah added, “Most reporting tools are static. You get a market share report, but you can’t double-click into the data to understand what’s really going on.”

IQVIA's Analytics Research Accelerator addresses this head-on. It provides a flexible, cloud-based environment where users can explore patient data, build dashboards, and generate insights on demand—without IT bottlenecks. With access to over 3,700 global data assets, it saves teams up to 80% of the time typically spent on data discovery.

Challenge 4: Enhancing Cohort Analysis

Understanding patient cohorts is essential for targeting, segmentation, and strategy—but it’s rarely straightforward.

In the UK, Martin described how IQVIA’s AI powered patient profiling solution combines deep EMR data with broader LRX datasets. “We can see test scores, diagnoses, demographics, and treatment histories. Then we project those insights onto a broader panel to understand where those patient populations are distributed.”

Mercury Williams from the USA added, “It’s not just about identifying cohorts—it’s about interpreting the insights. When we combine clinical expertise with data infrastructure, we help clients develop winning go-to-market strategies.”

IQVIA's Analytics Research Accelerator supports this by enabling users to define, compare, and validate patient cohorts using over 250 variables. With built-in Gen AI, it surfaces key differences and similarities—helping teams focus on what matters most.

Challenge 5: Identifying and Profiling Patients for Treatment

Finding the right patients at the right time is one of the most critical—and complex—tasks in healthcare.

In Brazil, Cristhiane Neves Gennaro described the challenge of integrating over 20 public data sources that don’t talk to each other. “Even within one provider, lab data might not connect with EMRs or pathology Once you integrate, you can start to mimic or find the best pathways to similar patients.”

Back in the USA, Mercury Williams explained how IQVIA uses predictive analytics and machine learning to dig into patients’ clinical backgrounds. “We develop models and deploy them across our data assets to find patients who are potentially ready for treatment.”

In Japan, Shujiro Takeno (Engagement Manager) emphasized the power of real-world data in forecasting disease progression “We know the past situation and current situation so that, for example, if rheumatoid arthritis patients are likely to develop severe disease, we can predict that they will move from steroids to biologics in the next two or three years. By identifying where these patients are—Tokyo, Osaka—we help clients allocate sales reps more precisely and size the future patient market.”

IQVIA’s AI-Driven HCP and Patient Profiling solution links patients to their treating physicians, enabling smarter outreach and accelerating product adoption.

Challenge 6: Identifying Patients at Risk for Medical Events

Anticipating medical events before they happen is a powerful goal—but one that’s often hindered by privacy constraints and data variability. Privacy, data clarity, and variability in patient journeys make it difficult to identify those at risk.

In France, Michele Arnoe (Senior Principal, Global Real World Data) – said, “Privacy is essential, but it reduces granularity. When you harmonize data to make it comparable, you sometimes lose utility.”

Back in the USA, Brian Hannah added, “There’s no single pathway to diagnosis. Each patient’s journey is unique. We need tools that can make sense of all those data points.”

IQVIA’s predictive models are trained on vast, diverse datasets and can be tailored to specific conditions, geographies, and populations—helping teams anticipate needs and act early.

Challenge 7: Comparing Patient Cohort Trends and Patterns

No two patient journeys are the same—and that makes comparison a challenge. “There isn’t one patient journey—there are a million,” said Brian Hannah. “That makes it hard to compare and target effectively.”

In France, Ludovic Prevost warned of the risk of “boiling the ocean” with too much data. “We need advanced analytics, especially Gen AI, to dive deep and find what matters.”

Whilst in the USA, Mercury Williams emphasized the need for flexibility. “You need to be able to adjust your cohort definitions on the fly and compare them meaningfully.”

Analytics Research Accelerator’s cohort comparison tools allow users to define, refine, and validate patient groups using consistent criteria. With Gen AI, it surfaces key differences and similarities—helping teams focus on what matters most.

Challenge 8: Providing Actionable Insights with Generative AI

Generative AI is transforming how we understand and act on patient data.

In the USA, Joe Imperato explained, “It’s one thing to have innovations in treatment. The trick is getting the right treatment to the right patient. Gen AI helps us create specialized cohorts and understand where to find them.” Ludovic Prevost added, “We’re working with thousands of patients. Gen AI helps us classify, group, and compare them more effectively.” Brian Hannah highlighted the power of automation: “Gen AI surfaces differences and similarities across patient journeys almost instantaneously. That’s incredibly powerful for improving care.”

Over in EMEA, Ludovic Prevost added, “We’re working with thousands of patients. Gen AI helps us classify, group, and compare them more effectively.”

IQVIA’s AI-Driven Patient Journey and Analytics Research Accelerator platforms are built with Gen AI at their core—helping teams move from data to decision faster than ever before.

From Insight to Action

This webinar made one thing clear: while the challenges of patient insights are complex, they are not insurmountable. Around the world, healthcare leaders are leveraging AI, real-world data, and cross-functional collaboration to build a more connected, patient-centric future.

Whether it’s a hospital in São Paulo, a clinic in Tokyo, or a research hub in London, the mission is the same: to understand patients better, so we can serve them better.

Are you ready to transform your approach to patient insights and healthcare analytics? Explore IQVIA's innovative solutions to enhance patient care, streamline identification processes, and leverage advanced analytics for actionable insights. Visit our AI-Driven Patient Journey, AI-Driven Predictive Patient Finding, HCP Targeting and Segmentation, and Analytics Research Accelerator platforms to learn more and get started today!

Let’s reimagine what’s possible in patient care—together.