In Part 1, Samuel broke down what actually matters when you’re trying to turn messy clinical RWD into evidence that holds up under scrutiny. In Part 2, he goes deeper on what makes device-level RWE uniquely hard, and what changes when you can reliably connect device identification, procedural context, unstructured clinical notes, and longitudinal follow-up.

11. What surprised you about the “longitudinal” aspect?

A: For many devices, longitudinal follow-up is critical to understanding performance and clinical benefits over the expected lifetime of the device—patient recovery and return to physical activity, reinterventions, complications.

12. How does epidemiology shape how you look at device evidence?

A: Thank you for asking that; I approach each project with fundamentals of epidemiology. Start by framing the research questions or hypotheses, identify relevant outcomes and data elements, then build a study plan around those. Also, don’t lose sight of QA/QC, bias, confounding, and generalizability. The platform helps with all of these because clarity and context reduce ambiguity in understanding clinical experiences and outcomes, and how confidently they can be assessed.

13. What do you mean by “fit-for-purpose” RWE for MedTech?

A: Data that aligns to the study objective and endpoints, is sufficiently complete and high quality, and is transparent enough that you can defend to regulators and stakeholders any conclusions drawn from the research.

14. What surprised you about data quality work at 3Aware?

A: How central it is. We’re not just “using data”—we’re continuously assessing whether it meets the needs of our customers and the standards needed for global regulatory frameworks and market access decisions. That means rigorous QA/QC on our end, and keeping up with evolving regulations and guidance from FDA, EU, and elsewhere.

15. What’s a common misconception about RWE for medical devices?

A: That it’s either “too messy to use” or “a shortcut.” High-quality device RWE takes rigorous methods—done right, it can be both efficient and credible. Always start with a fully-developed study protocol and clearly define research questions/hypotheses, outcomes, and data elements.

16. How does 3Aware support both pre-market and post-market objectives?

A: The same foundation—device-specific cohorts + longitudinal context + defensible methods—can support PMCF, indications expansion, algorithm validation, and other lifecycle evidence needs.

17. What’s different about partnership building when evidence is the product?

A: It requires alignment on objectives and transparency between partners on what is achievable (or not) with a particular data set. The best collaborations happen when everyone is clear on what questions we’re answering and what “good evidence” looks like.

18. How do you handle “evidence gaps” in real-world settings?

A: First, define the gap precisely. Then decide whether you can address it with existing RWD, targeted data collection, or a refined design. The key is being explicit about study objectives, data quality, and limitations, and ensuring that any conclusions are defensible and reproducible.

19. What’s one thing you’d tell peers still doing evidence generation the old way?

A: Don’t start with the deliverable—start with the decision and the endpoint. If you design evidence around the actual regulatory and clinical questions, the rest becomes more coherent. 3Aware can perform a thorough feasibility assessment for any study plan, so you can confidently gauge the likelihood of success in working with us versus other methodologies.

20. If you had to summarize the biggest surprise in one sentence?

A: A platform built for MedTech RWE can make rigorous, product-specific evidence generation feel practical—without compromising methodological standards. Five years ago, I’d have been surprised to hear anyone in medtech saying that a RWD-based approach is their go-to method, rather than a fallback, but this is now doable with the combination of high quality data, 3Aware platform tools, and well-crafted study designs.

Ready to take a closer look at the 3Aware Clinical Research Workbench? Request a demo here.