The MDEpiNet PPP construct promotes a critical step forward for regulatory science, to facilitate both medical device safety surveillance and innovation. Within this construct a number of traditional research and development (R&D) boundaries can be recognized as barriers to both the quality and efficiency of device evaluation and surveillance. In particular boundaries that inhibit informative data pooling (data silos, differing nomenclature, case report forms and endpoint definitions), that unnecessarily partition information gathered over the total product life cycle (pre-market vs. post-market), and that fragment information across international borders, all constitute barriers to the accrual of device-related knowledge, especially with regard to safety information. All of these areas thus provide important targets for efforts that support a higher quality, more seamless and global approach to device registration and surveillance. Pre-competitive collaboration across stakeholders in conjunction with regulatory and other governmental authorities in a transparent public-private partnership (PPP) promotes an "ecosystem" approach well fitted to both the conceptual and pragmatic transformation of these barriers. Tools such as national and international electronic registries, consensus definitions applied within such electronic infrastructure, statistical methodologies suited to such data sources and actual device evaluation "proof of concept" programs or other related research projects with deliverables that enhance regulatory science as applied to human clinical trials are well fit to engineer this transformation. This proposal will address the strategy, scale, scope, resources, organizational structure, deliverables and timelines to develop and support systems to facilitate a in-depth understanding of medical device use and associated health outcomes through the Medical Device Epidemiology Network (MDEpiNET) initiative.
1. ABSTRACT With increasing device complexity and a rapidly accelerating pace of design iteration and innovation, it has become increasingly apparent that current device evaluation paradigms must evolve1. The traditional, fragmented approach to device development and surveillance has led to a proliferation of data systems that have come to promote gaps in evaluation and redundancy of infrastructure. The impact of these trends over time has been a slowing of research and development (R&D) time to bedside while increasing R&D costs, a combination that ultimately both increases healthcare costs while undermining the quality of healthcare itself. Further, while traditional approaches produce a tremendous quantity of data on emerging medical devices, fragmentation of data sources undermines the ability to aggregate data, and hence undermines the accrual of knowledge, in particular knowledge about safety. The impact of more data creating less information is particularly relevant as a barrier to understanding how devices are used and how they perform in real world practice. The FDA has responded to this situation with a number of initiatives, including the recently released report on Strengthening Our National System for Medical Device Postmarket Surveillance. (http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDRH/CDRHReports/ucm 301912.htm). Integral to this report and other FDA initiatives has been the awareness that the proliferation of independent electronic data capture systems and databases are not only the source of the problem, but also provide unique opportunities for solutions that respond to current and future needs related to understanding device-related outcomes in real world practice. In particular, a focus on linking and leveraging already existing device registries and data systems with respect to advancing national and international infrastructure in conjunction with attention to methodologies of signal analysis and interpretation could not only support the National Postmarket Surveillance initiative, but through the iterative nature of medical device development and regulation, the linking and integration of data systems could positively impact the quality and efficiency of R&D efforts throughout the total product life cycle, speeding time to bedside and reducing R&D/healthcare costs while actively improving the quality of safety and performance information. FDA also has recognized that integration of currently fragmented data systems through national infrastructure could not only facilitate R&D efforts, but could be usefully directed to serve as ongoing informative resources for multiple key stakeholders, including patients, hospitals, third party payers, professional societies and international regulatory authorities, through carefully developed and secure access over time. More integrated infrastructure combined with advanced methodologic applications has the potential to transform current barriers to knowledge into a uniquely informative and critically needed mechanism for ongoing accrual of information-in particular information about long term device performance and rare but catastrophic safety issues. From patients who may want to know more about the device they had implanted to payers, manufacturers, professional society best practice guidelines and federal authorities, this transformation from fragmented to linked, integrated and appropriately accessible information is a critical objective to be achieved. Finally, through this FOA and other initiatives FDA clearly recognizes the potential to accomplish the transformation from fragmented data repositories into a more informative national infrastructure through collaborative mechanisms such as focused, pre-competitive public-private partnerships (PPP) that include the broad range of interested stakeholders. This approach is consistent with FDA Commissioner Dr. Margaret Hamburg's overview of FDA's approach to innovation in medical therapeutics as the address of an ecosystem .(http://www.fda.gov/AboutFDA/ReportsManualsForms/Reports/ucm274438.htm). The inclusiveness of a pre-competitive PPP, combined with organizational structure that facilitates collection of expertise and experience around disease-specific, device-specific interests with deliverables that both impact the specific device and that establish generalizable predicates, creates an efficient working environment capable of leveraging existing resources rather than having to invent or develop new resources. 1