Seeing the billed charges is one thing. Knowing what actually got paid and why some claims didn’t is what turns data into actionable intelligence. Remitted claims data provides that level of transparency. It shows what was paid, what was denied and what patients were expected to pay out of pocket.
For lab teams, this means you can assess contract performance and detect billing gaps that impact revenue and provider satisfaction. Specialty pharma teams can use this data to spot payer behavior tied to site of care, identify geographic pockets of poor access and monitor trends that lead to therapy abandonment. On the medical device side, this insight supports analysis of approval rates, payer-specific challenges and how quickly systems are reimbursed after procedures.
This kind of visibility helps uncover trends that are not available in public datasets. Coding issues, shifting payer policies and regional inconsistencies become visible — allowing teams to respond faster, refine their strategy and better support providers and patients.
The final and arguably most important layer is the why. Why are certain claims being denied? Why are patients abandoning therapies? Why do access challenges spike in certain regions or payer plans?
For diagnostic labs, remitted claims data provides concrete evidence to support provider education and value conversations. By showing how payers are reimbursing your test in practice, you can make a stronger case for coverage and help your referring providers navigate payer policies with confidence.
In specialty pharma, teams can use this data to identify high-denial regions and adjust market access strategies accordingly. Denials tied to prior authorizations or specific sites of care may signal the need for targeted education or payer engagement. These insights also help field teams better prioritize accounts and align messaging with real-world access dynamics.
Medical device manufacturers can use remit data to support health economics and outcomes research (HEOR), reinforce clinical value messaging and adjust forecasting models to account for regional payment trends. When you understand why reimbursement is breaking down, you can mitigate it — or avoid it altogether.
Another global consideration or influence is the fact that global supply chains are evolving, especially for medical devices. With over 70 percent of U.S. medical devices manufactured overseas1, disruptions in shipping, material sourcing and geopolitical policy can impact more than just delivery timelines.
Remitted claims data doesn’t capture manufacturing costs, but it does show the downstream effects. Shifts in denial rates, delayed payments or coverage changes from major hospital systems may be early indicators of supply chain–driven stress. For medical device companies in particular, this insight helps teams adapt faster and align with payer priorities amid cost pressure and resource constraints.
Real-world reimbursement data gives life sciences teams the visibility they need to navigate today’s complexity with confidence. It’s not just about understanding pricing pressure or payer behavior in theory. It’s about seeing what’s happening at the ground level — and responding in a way that’s both data-driven and patient-focused.
When you know who is paying, what is being reimbursed and why challenges occur, you’re in a stronger position to improve access, accelerate time to revenue and support the providers and patients who rely on your product.
References:
Please fill out the form below and we'll be in touch shortly, or call us for immediate assistance at
1-866-396-7703