The Medical Device Innovation Consortium (MDIC) is conducting this survey to gather insights about the utilization of external data.  As such “external data” includes the following:
  • Prospective or existing data from a device or disease registry
  • Patient-level or summary level data from historical clinical studies; i.e., data from clinical studies conducted in the past
  • Laboratory data
  • Claims data
  • Electronic health records (EHR) data
  • Modeling and simulation (M&S) data
Note that many real-world data (RWD) sources could be considered external data, and that we are interested in RWD sources, but not limiting our search to these sources. External evidence is clinical evidence synthesized by appropriate analysis of external data.

MDIC External Evidence Methods (EEM) program aims to develop an MDIC EEM framework document that will categorize and catalog existing statistical methods for the use of external data in regulatory decision-making for medical devices.  This will help establish a more streamlined pathway for the use of external data in regulatory submissions. 

MDIC would like to conduct this survey to ascertain information from you and/or study statistician who provides support to your company on the use of external evidence. We seek to collect information on the use of external data for making statistical inference for primary safety and/or primary effectiveness endpoints:

  1. In clinical studies that were associated with a medical device approved or cleared by the US FDA via applications such as PMA, PMA supplement, 510k, HDE and De Novo.
  2. In pre-market investigational device clinical studies currently being conducted for FDA approval/clearance or completed, but device not yet approved by the FDA (e.g., IDE and Q-submissions).
More specifically, we are collecting information on the types of external data source and the statistical methods (including Bayesian and Frequentist) used for leveraging/synthesizing external evidence to support regulatory decision-making.  Gaining better understanding of the data sources and analytical approaches that are currently being used in this space will make it easier for us to develop preferred processes and descriptions of best practices.  This information will further help summarize the current use of external data in order to identify gaps in the suitability of methods or their usage and need for developing new methods.

T