The selected Demonstration Projects test two approaches to leveraging Real-World Data and generating Real-World Evidence: The first project is focused on developing an electronic health record (EHR) based network in a large hospital system to support evidence generation for medical devices across the Total Product Life Cycle (TPLC). The second project tests the feasibility of using a mobile health (mHealth) application that aggregates multiple sources of health data, with patient consent, to augment post-market surveillance.
While these projects make use of data generated post-approval, the methods have the potential to produce generalizable knowledge to inform requirements and decisions in the pre-market phases and potentially across multiple medical device classes and medical technologies such as imaging and diagnostics. We believe that these initial projects will:
- Help develop methods of evidence generation and data use
- Scale across health systems, device types, and small and large manufacturers
- Potentially demonstrate impact on patients’ health outcomes, and better engage patients in research
- Identify gaps to help target critical areas and inform NESTcc’s strategy moving forward
None of these projects will provide a competitive advantage to a specific manufacturers. Furthermore, NESTcc will not provide funding for the core research activities for these Demonstration Projects, as the projects are already funded and underway but will work collaboratively with the project teams to establish learnings and resources for NESTcc as we move forward.
Use of EHR-Based Data Network to support Evidence Generation across the TPLC
A collaboration between a medical device manufacturer and a large hospital health system, this project aims to develop, test, and validate the use of an EHR-based data network to support evidence generation for medical devices across the TPLC. A test case involves heart failure patients receiving Chronic Resynchronization Therapy (CRT).
Impact for NESTcc:
The systematic process deployed to validate and test the pathways for evidence generation is producing a scalable model to inform an industry-wide roadmap toward the use of EHR-based data networks for the responsible access and use of practice data, in both the pre-market and post-market space. While the test case is in the post-market space, the infrastructure and learnings will be used to inform future use-cases in the pre-market space.
Medtronic*, Mercy, SAP/HANA, Linguamatics
Darrell Johnson (Medtronic); Joseph Drozda, MD (Mercy)
Testing mHealth for post-market surveillance
These two feasibility projects involve collaborations between medical device manufacturers, academic medical centers, and vendors to A) test and validate the use of an mHealth app to aggregate data from multiple data sources (with patient consent), then B) evaluate the potential use of this data to inform or augment post-market surveillance.
One project will compare the quality and reliability of data acquired via the mHealth app to data acquired in an industry-owned post-market surveillance registry, Medtronic’s Product Surveillance Registry (PSR). This study is enrolling 30 patients from Yale New Haven hospital who are also registered in Medtronic’s PSR.
The second project will test the feasibility of using the mHealth app for post-market surveillance in patients (1) after sleeve gastrectomy and (2) after catheter-based atrial fibrillation ablation. Outcomes collected will include enrollment times, patient participation, dropout, completion of patient-reported outcome measure queries, and user satisfaction and burden. This study is enrolling 60 patients at Yale New Haven Hospital and Mayo Clinic.
Impact for NESTcc:
The systematic process used to test and validate the mHealth app and validate its feasibility of use will provide insight and produce a framework for future use of mHealth apps in the post-market setting. Learnings will be extendable to pre-market evidence generation use-cases in the future.
Part A: Medtronic*, Yale University, Me2Health
Part B: Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation (CERSI)*, FDA, Me2Health, Johnson & Johnson
Part A: Rachael Lampert, MD (Yale)
Part B: Joseph Ross, MD, MHS (Yale); Nilay Shah, PhD (Mayo)