Evaluation of Uptake of Unique Device Identifiers (UDIs) by Health Systems

  • Overview

    This project seeks to understand the implementation and use of UDIs in clinical care to address barriers to implementation so as to improve research employing real-world data to evaluate medical device safety and effectiveness.

    Adoption and use of UDIs across health care systems could help enhance the ability to generate high-quality real-world evidence for regulated medical devices as well as improve local and national safety surveillance and tracking efforts by facilities, clinicians, manufacturers and regulators, including management of product recalls and purchasing. However, UDIs are not routinely collected and available in existing Electronic Health Record (EHR) data at most health systems. Further, when UDIs are used they are often only collected for a limited number of clinical care settings.

    This project will conduct semi-structured key informant interviews with NESTcc Network Collaborators to characterize the current use of UDIs within electronic data sources, including availability within EHRs and other health information technology systems and within structured data extractions. Interviews will address perceived benefits of UDI availability and challenges met, including administrative, financial and organizational. The results of these interviews will be used to develop a large-scale health system survey. The survey will characterize whether, how and for what clinical areas medical device UDIs are collected within health systems’ electronic data sources.

    This project is being conducted as a NEST Collaborative Community initiative and, as part of that initiative, will seek feedback from the community at various points throughout the project.

  • Resources

    Sanket Dhruva, M.D., MHS, assistant professor of medicine at UCSF School of Medicine, provided an overview of the UDI project as part of the NEST Collaborative Community event “Emerging Issues in UDI” on October 15, 2020.  Watch the recording.

  • Topic of Interest

    Unique Device Identification

  • Research Team

    Mayo Clinic, Mercy, UCSF, Yale New Haven Hospital, Arizona State University