Welcome back to another episode of Theoretically Speaking. Every day, life sciences teams look at massive datasets to track how their therapies perform in the real world. But too often those spreadsheets only tell a fraction of the story. We can see that a patient stopped taking a medication or when they switched treatments, but we’re left guessing as to the human realities behind those numbers. In this episode, we sit down with Becky Hollenberg, senior RWD strategy lead at Norstella, for a deep dive into an incredibly valuable topic. Becky walks us through how breaking down the traditional walls between claims, EMRs, and payer data completely changes how we view the patient journey.
Becky, thank you so much for your time today. I’m really excited to get into this discussion. Yeah, so great to speak with you today. Okay, so the pharmaceutical industry certainly isn’t hurting for data right now. But having data and having the whole story are two different things. So I really wanted to start the discussion there. For pharma companies, there’s more data available today than ever before. However, most real-world evidence captures only part of the patient journey. So where do these gaps exist and how can they be filled Yeah, so most real-world evidence is generated from fragmented data sources that, like you said, are only capturing parts of the patient journey. So this can often answer who’s receiving treatments, when do treatments occur, how much do treatments cost. But they struggle to answer kind of the why behind those questions. So why does therapy initiated, why do patients discontinue, what clinical characteristics drove outcomes, how do payer restrictions impact access, and which patients never received therapy despite clinical need. So the root issue isn’t the volume of the data, it’s that it’s fragmented. So sources capture isolated pieces of the journey that aren’t connected. So our approach at Norstella is integrating those data sources to kind of create a complete picture of the why behind the patient journey. So that’s linking the claims, the EMR clinical notes, labs, and payer coverage access data on the payer level and then rolling it up to whatever level the client needs.
Got it. That totally makes sense. And it’s clear that this integration is is key to understanding the why behind the patient journey, and it isn’t just an internal goal for Pharma. There’s also a lot of external pressures to deliver these deeper insights that are continuously mounting. So looking at that broader landscape, how are evidence expectations among payers, HTA bodies, and internal stakeholders? Yeah. So I think the why is becoming more central for external stakeholders and internal teams The increasingly want evidence of real-world effectiveness, appropriate patient identification, outcome drivers, and impact of access restrictions, and There is a real risk there because incomplete evidence can lead to mischaracterized patient populations, bias outcomes, missing access barriers and value stories that are only telling half the pictures, in some cases, telling the wrong story that’s not really capturing what’s truly happening to the patient when you connect everything together. So, in short, data access is no longer the differentiator, the usability of the evidence and the applicability and generalizability of that evidence will be.
And if usability and understanding the why’s is the new baseline expectation, we have to look a lot closer at the raw materials we’re working with. So we know things like claims and EMRs are powerful but limited when they’re on their own. Um, so wanting to break that down a bit. Each dataset, like I mentioned, claims EMR data, labs, clinical notes, and policies and access data, they all have individual strengths, but it doesn’t tell the full patient story, like you’ve mentioned previously. So how does connecting real-world data sources to build an integrated360 degree view of the patient journey work? Yeah, so it’s each source is kind of answering a different question about the patient journey. So claims are gonna really help ground into what happened and when. Um, EMR is gonna show more of that patient status and vital side of it and lab values. are gonna show what’s happening biologically. Um, the clinical notes is where we really see a lot of the depth unlocked um in terms of things you wouldn’t see typically in a structured data source. So that could be anything from disease severity to treatment decision making, treatment rationale, Symptoms, clinical presentation that the patient’s going through. and then the payer and policy data is gonna understand what what access barriers are shaping care and how do those play into those treatment decisions and the rationale that the physician is making um. individually, there are partial data sources, but the value comes from connecting them into one clinical record that has all the clinical, lab and narrative access signals uh for one patient all combined um. So that’s gonna lead to more accurate cohort definitions, better confounder adjustment, stronger outcomes capture, clear access and barrier identification, and a more defensible value story because you’re seeing more of a complete picture and more of the holistic patient journey. So, if we look across a patient journey, for example, ICD 10s plus labs could show the confirmed diagnosis based on phenotypes and uh ICD 10 codes notes will kind of unlock why a treatment was chosen or why a switch happened, whether it was an efficacy signal, a tolerability signal, right, access problem. Um, and then claims will, we can then track how that uh how that switch occurred, did the patient get on therapy um, and then using labs and progress notes, we can see the outcomes of that, and how did the patient respond to their treatment switch.
Got it. And seeing how that comprehensive timeline comes together is really impressive, especially from a data science perspective. But I know its real power really lies in that commercial and clinical application like you were mentioning. So when you unlock that360 degree view, what does it actually mean for the people on the ground doing the research? How do different business functions, market access, HEOR, medical affairs, medical comms team benefit from that 360 degree patient view Yeah, so for market access teams, it’s gonna be focused on defending access against payer restrictions. So that could could be quantifying the impact of payer restrictions, identifying the unmet need populations, understanding drivers of abandonment, building a payer dossier grounded in clinical reality, and informing contracting and access strategy. On the HOR side, it’s going to mean sharper evidence that’s more defensible to scrutiny from external stakeholders. So. That could mean improved cohort definitions and identification, reducing misclassification bias. Adjusting for disease severity within our cohort definitions linking to real world outcomes and access past- pathways more comparative effectiveness studies of stronger with their evidence and overall more credible economic evidence From a medical affairs side, it’s kind of combining the clinical and the access story. so understanding treatment rationale and unmet need, identifying if there are any gaps between guidelines and how physicians are actually practicing characterizing disease burden and informing evidence generation priorities so that they can equip their MSL teams to be able to speak to that. So the unifying point here is that all three work off of one unified value story. So the same underlying data, even though, the actions based on those takeaways might be different the takeaways individually should be the same and kind of create that-that unified story.
That completely makes sense. It’s fascinating to see how one unified value story can align with so many different departments and how they all work together from yeah market access to all the way through to medical affairs. And to ground this concept and to show what it looks like in practice, I wanted to look at a real life scenario. So can you give us an example of a use case of how connected data can provide a more complete picture of a treatment journey Yeah, so for example, we’re looking at uh treatment discontinuation that we see in a moderate to severe immunology patient. So if we look at claims alone, we might see that the patient discontinued therapy. They had one fill. They didn’t refill it, but we don’t really understand the reason why and that’s kind of all we’re left with. There’s not really any layer there. If we add on EMR data, we can understand, based on lab values and the patient had PR visit showing that their disease was worsening, um. We can see that their discontinuation was linked to a flare. And so then we can kind of rule out that that’s not due to poor adherence or the patient didn’t pick up the drug. They actually had a real-life outcome that led to that discontinuation. Within the clinical notes, we can then look and see the progress note that physician notice said. The patient might have had an injection site reaction. So we can understand that that switch was clinically warranted and had a reason behind it that we weren’t seeing within the structured data. And then with the payer access data, we can see maybe the physician notes that they’re gonna switch the patient to a new therapy. And then in the claims we see that that therapy was denied and when we layer in the access data there, we understand that that was denied because the patient didn’t have the proper step therapy allowing them for insurance to cover it. So we can see how the access barrier leads to the patient not getting on the switch therapy. So in some, you know, each level-layer of evidence as we layer on different pieces of this disparate data source, we see how this patient interaction can be reframed from a lost patient to something that can actually be an access barrier that can be defended against and kind of utilized by teams to then have more effective engagement. Yeah, and like you said, help to engage and solve for future barriers down the line. Um, so hopefully we can avoid, use that information to to educate different policies and procedures. Great. Amazing Becky, thank you so much for your time. I’ve learned a lot from our conversation and I’m sure our audience will as well Thank you.
It’s clear that looking at the patient journey through a single lens doesn’t cut it anymore. When teams can look at a single cohesive narrative, one that respects both clinical realities and paired complexities, It completely changes the game for how therapies are valued, defended, and delivered. A huge thank you to Becky Hollenberg from Norstella for sharing her expertise with us today. And to our listeners, thank you for tuning in to Theoretically Speaking. If you found value in today’s episode, please take a moment to subscribe, rate us, and leave a review on your favorite podcast platform. Until next time.
