Stacy Justo
Meghana Shamsunder
Marten
van den Berg
The project underscores how connected RWD can move beyond observation to drive meaningful change for patients.”
By Stacy Justo, Meghana Shamsunder, and Marten van den Berg
For patients with metastatic non-small-cell lung cancer (mNSCLC), timely treatment can make a significant difference in outcomes. But identifying where and why delays occur has traditionally been difficult because the patient journey spans disconnected systems, from clinical records and insurance claims to administrative approval processes.
We recently tackled this challenge using real-world data (RWD) from NorstellaLinQ and Panalgo’s Instant Health Data (IHD) platform, presenting our research findings at ISPOR 2026. Throughout the course of our project, we found meaningful treatment delays among some of the most vulnerable lung cancer patients and demonstrated how connected RWD can help improve care.
Connecting the Full Patient Journey
One of the biggest barriers to studying treatment delays in cancer care is that the necessary information is often fragmented across separate systems. Clinical severity may exist in electronic medical records (EMRs), while insurance coverage, claims approvals, and medication timelines are captured elsewhere. Having disparate sources of data makes it difficult to determine whether delays are due to clinical need, system inefficiencies, or access barriers.
For our study, we overcame this issue by using NorstellaLinQ’s integrated data ecosystem, which connects EMR data, closed claims, medication events, and payer information into a single longitudinal view of the patient journey. This allowed us to track patients from diagnosis through treatment initiation and analyze how factors such as insurance type and comorbidities affected delays in care.
The study leveraged data representing approximately 245 million patients across commercial insurance, Medicare, and Medicaid populations, giving us a broad, real-world view of cancer care delivery in the U.S.
What the Study Found
Our analysis showed that treatment delays were longest among patients with high comorbidity burdens and among patients covered by Medicare or Medicaid. These findings highlight how both clinical complexity and administrative barriers can delay access to life-saving therapies. Prior authorization requirements, denied claims, and coordination challenges across providers may all contribute to slower treatment initiation for patients.
Knowing the problem exists and understanding the scale and factors involved is the first step to solving it, so by identifying which patients were most at risk for delays, healthcare organizations, policymakers, and pharma manufacturers can take steps to improve care coordination, streamline administrative processes, and make sure therapies reach patients faster.
Why Real-World Data Made the Difference
Traditional research datasets often rely on relatively small patient cohorts collected under controlled conditions. While those datasets can provide detailed information, they may not reflect what actually happens in everyday clinical practice. Real-world data is so valuable because it captures the story as it is, in real time. It’s a real representation of these patients and their story.
Instead of studying a limited group of patients from a single research setting, we analyzed data from millions of patients across the U.S. That scale allowed us to identify treatment delays occurring across diverse populations and payer types, rather than isolated cases in a small cohort. Having integrated data sources was crucial. By combining EMR data with claims data and longitudinal patient tracking, we created a true 360-degree patient view, which is difficult or impossible with traditional siloed datasets.
Faster Insights With IHD
Designing the study actually took longer than running the analysis itself because IHD allowed us to quickly explore raw data, build cohort definitions, create custom variables, and validate results within a single platform. IHD let us apply custom methodologies to identify mNSCLC patients, even without oncology-specific patient flags built into the source data. This ability to rapidly analyze large-scale RWD could help healthcare stakeholders identify barriers to care faster and take action sooner.
Beyond Commercial Insights
While RWD is often associated with commercial strategy and market analytics, this study shows how valuable it can also be in health services research and policy. The findings not only provide insight into how cancer care is delivered in the real world, but also create opportunities to improve access for patients who may otherwise face delays in receiving critical therapies.
Most importantly, the project underscores how connected RWD can move beyond observation to drive meaningful change for patients. By uncovering hidden treatment barriers and identifying high-risk populations earlier in the care journey, RWD is helping healthcare organizations better understand where intervention is needed, and how to get therapies to patients faster.
Contact us to find out how IHD and NorstellaLinQ can help you find more patients, faster.