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On this page
  • About the Dataset
  • Dataset Features
  • Data Quality and Maintenance
  • Business Applications
  • Example Use Cases
  • Data Structure
  • Entity Relationship Diagram
  • Sample Queries
  • Support and Contact
  • About Dataplex
  1. Snowflake Catalog

FDA Device Dataset

About the Dataset

The FDA Device Dataset is a comprehensive collection of data related to FDA-regulated medical devices. It includes information on device approvals, classifications, adverse events, recalls, and more, dating back to 1976. This dataset is updated daily, providing the most current information available from the FDA.

Key features of the dataset include:

  • 510(k) Clearances

  • Device Classifications

  • Adverse Event Reports

  • Pre-market Approvals (PMA)

  • Recall Information

  • Registration and Listings

  • COVID-19 Serological Testing Evaluations

  • Unique Device Identifiers (UDI)

Dataset Features

  • Comprehensive Coverage: Includes data on all FDA-regulated devices since tracking began.

  • Daily Updates: All tables are refreshed daily to reflect the latest FDA information.

  • Historical Data: Device data dates back to 1976, providing a rich historical context.

  • Easily Queryable: Data is flattened for quick integration and analysis.

  • Diverse Event Types: Covers various device-related events from pre-market approval to post-market surveillance.

Data Quality and Maintenance

  • Daily updates ensure the most current FDA device information is available.

  • Automated data quality checks are implemented to maintain data integrity.

  • The dataset is monitored daily by the Dataplex Consulting team to ensure timely and accurate delivery.

Business Applications

  • Track pre-market FDA device approvals

  • Monitor and analyze device recalls

  • Identify firms associated with specific devices or events

  • Assess results of COVID-19 serology tests

  • Conduct market research on medical device manufacturers

  • Perform risk analysis on medical devices

  • Support regulatory compliance efforts

Example Use Cases

  1. Analyze trends in 510(k) clearances for specific device types or manufacturers.

  2. Investigate adverse events related to particular medical devices.

  3. Track recall patterns for high-risk medical devices.

  4. Assess the market landscape for specific device categories.

  5. Conduct due diligence on medical device companies.

Data Structure

The FDA Device Dataset consists of multiple tables, each focusing on a specific aspect of medical device regulation. Key tables include:

  • DEVICE__510K_CLEARANCES

  • DEVICE__CLASSIFICATIONS

  • DEVICE__ADVERSE_EVENTS

  • DEVICE__PREMARKET_APPROVALS

  • DEVICE__RECALLS

  • DEVICE__REGISTRATIONLISTINGS

  • DEVICE__UDIS

Entity Relationship Diagram

Sample Queries

1. Count of 510(k) clearances for Class III devices by advisory committee

SELECT advisory_committee_description, COUNT(*)
FROM dwv.device__510k_clearances
WHERE openfda_device_class = '3'
GROUP BY advisory_committee_description;

2. Recent recalls for a specific manufacturer

SELECT event_date_initiated,
       event_date_posted,
       openfda_device_name,
       product_description,
       openfda_device_class,
       reason_for_recall,
       product_quantity
FROM dwv.device__recalls
WHERE recalling_firm ILIKE 'Inspire Medical Systems Inc.'
ORDER BY event_date_initiated DESC
LIMIT 10;

3. Adverse events related to a specific device type

SELECT event_type, COUNT(*)
FROM dwv.device__adverse_events e,
LATERAL FLATTEN(e.device) d
WHERE d.value:generic_name::string ILIKE 'replacement%heart%valve'
GROUP BY event_type;

Support and Contact

For questions, support, or assistance with the FDA Device Dataset, please contact:

Our team monitors ingestion and ETL jobs daily to ensure quality and timeliness of data delivery.

About Dataplex

Dataplex Consulting & Data Products is a comprehensive data consulting firm that empowers clients with reliable cloud data and analytics solutions. Our team of certified experts in data engineering and analytics offers tailored services to support data-driven enterprises.

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Last updated 3 months ago

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