• Integrating the Healthcare Enterprise (IHE) Cardiology Profiles
• National Cardiovascular Data Registry® (NCDR) Implantable Cardioverter Defibrillator (ICD) Registry™ V2.1 Coder’s Data Dictionary
• ACC/AHA/SCAI 2014 Health Policy Statement on Structured Reporting for the Cardiac Catheterization Laboratory: A Report of the American College of Cardiology Clinical Quality Committee
• ACCF/AHA 2011 Key Data Elements and Definitions of a Base Cardiovascular Vocabulary for Electronic Health Records: A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards
• Most Frequent Operating Room Procedures Performed in U.S. Hospitals, 2003-2012

• Integrating the Healthcare Enterprise (IHE) Quality, Research, and Public Health Technical Framework Supplement: Structured Data Capture (SDC)
• Office of the National Coordinator (ONC) Structured Data Capture (SDC) Initiative
• Clinical Data Interchange Standards Consortium, Inc. (CDISC) Healthcare Link Profiles

• Kaiser Permanente National Total Joint Replacement Registry: Aligning Operations With Information Technology

• AccessGUDID
• Global Unique Device Identification Database
• Advancement of Innovative Methodologies and Medical Device Specific Infrastructure for Evidence-Based Regulatory Science and Public Health Surveillance: Implementation of Unique Device Identification Demonstration Projects Lessons Learned
• Mercy SUDID Data
• Unique Device Identifiers (UDIs): A Roadmap for effective implementation
• Premier Research Institute – Unique Device Identifier: Implementation Guide
• Learning UDI Community

Device Data Capture Efforts

• Promoting the capture of unique device identification in health care data sources
• Using automated methods and electronic systems for capturing detailed information on medical devices through the Unique Device Identifier
• Acquiring and analyzing data collected and stored within medical devices.
• Developing and implementing databases of clinical attributes for a deeper understanding of medical device design characteristics
• Communicating lessons learned/best practices  to inform National Medical Device Evaluation System

FAQs

• Can the device identifier (DI) portion of a Unique Device Identifier (UDI) be part of a limited or de-identified data set as defined under HIPAA? Yes. Please find additional information at https://www.hhs.gov/hipaa/for-professionals/faq/2071/can-device-identifier-di-portion-unique-device-identifier-udi-be-part-limited-or-de-identified/index.html

• National Medical Device Surveillance System (MDS) Action Plan
• Office of the National Coordinator (ONC) – Connecting Health and Care for the Nation: A Shared Nationwide Interoperability Roadmap

• Evaluating  selected medical devices based on public health importance/need and availability of existing data sources
• Obtaining safety and effectiveness estimates throughout the total product life cycle
• Developing and applying modeling techniques to enhance understanding and context of medical device benefit/risk balance
• Translating the results of modeling for regulators, physicians and patients and disseminate the results
• Communicating lessons learned/best practices  to inform National Medical Device Evaluation System

• Adapting existing patient centered total product life cycle framework to evaluate selected medical devices
• Accounting for comparator selection, device characteristics, operator characteristics, procedure/intervention characteristics, intervention setting characteristics, patient characteristics and appropriate outcome measures selection
• Communicating lessons learned/best practices  to inform National Medical Device Evaluation System

• Developing scientifically valid analytical methods for evaluating medical device exposure and clinical outcome characteristics across multiple data sets across different types of data systems
• Utilizing appropriate statistical techniques to compare performance and clinical outcomes between comparator or exposure groups and translate the modeling results for regulators, physicians and patients and publicize the results
• Evaluating  existing gaps in approaches to medical device studies of approved medical devices by developing innovative methodologies using existing data sources and infrastructure
• Identifying  and describing unique challenges and gaps in studying various classes of medical devices
• Identifying sustainable data and methods for evaluation of selected classes of medical devices
• Validating endpoints/outcomes using variety of data sources
• Communicating lessons learned/best practices  to inform National Medical Device Evaluation System

MDEpiNet- HIVE is a technology that provides a secure healthcare biomedical data archival ecosystem. MDEpiNet- HIVE maintains a standardization and harmonization framework, high performance analytics, and an integrator platform.

The recent implementation of HIVE hardware and software at the FDA presents a great opportunity for exploring new ways of analyzing vast amounts of data and deriving evidence that is more comprehensive to characterize a medical product. HIVE is a distributed storage and computation environment and a multicomponent cloud infrastructure, which provides secure web access for authorized users to deposit, retrieve, annotate, and compute on biomedical big data. Importantly, it also allows users to analyze the outcomes using web interface visual environments appropriately built in collaboration with internal and external end users.

In addition to the initial HIVE applications to next generation sequencing, the current universe of HIVE projects covers tailor-made applications involving dimensionality analysis, federated and integrated data mapping, modeling and simulations that are applicable to basic research, biostatistics, epidemiology, clinical studies, post-market evaluation, manufacturing consistency, environmental metagenomics, outbreak detection, etc.

MDEpiNet Coordinating Center currently supports various HIVE pilot projects in women’s health technologies and cancer settings. Patient and physician registry platforms are being developed as well as infrastructure for hosting registry and claims data and conducting data linkages that are distributed and centralized to support national and international collaborations.

Pilot approaches are set to develop a customized FHIR app for projects such as POP and SUI. These are being tested on mobile and connected devices through work with clinical teams to finalize the data elements for terminology and refine the app with feedback on usability.