Use case package 2 (UC2): Empirical application of the Sentinel EHR and claims Data Partner network to enhance ARIA insufficient inferential requests and atypical descriptive requests
Description
This AI project is designed to solve the problem of translating theoretical innovative methods into practical, real-world applications within the Innovation Center (IC) development network. It aims to create concrete, evidence-based examples that demonstrate how new technologies and approaches can be effectively implemented to address specific pharmacoepidemiologic and drug safety surveillance challenges.
Detailed example
EHR data elements; EHR-linked to claims data
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Developing advanced methods including machine learning to address incomplete information in drug safety studies, validating health outcome algorithms using Natural Language Processing (NLP)-assisted chart review, and applying NLP to analyze cannabis-derived product exposures in electronic health records, ultimately improving FDA's drug safety surveillance capabilities.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
EHR data elements; EHR-linked to claims data