HHS · no agency ID · record R0817

Renamed: Risk-based FAR Review & Decision Support Previously: Field Alert Reports (FAR) Prioritization Model

Department of Health and Human Services · HHS/FDA/CDER

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-10 (month precision)Source: Oct-24
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Health and Medical
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual and subjective assessment process for Field Alert Reports (FARs) can lead to inconsistency in prioritizing and assessing reports, potentially leading to ineffective resource allocation where the same level of formality is being applied for all issues, regardless of risk.

Expected benefits

Assist Field Alert Report (FAR) reviewers by providing objective intelligence and insights that help prioritize the highest risk reports, potentially reducing response time to high-risk issues while maintaining human oversight of all decisions and leading to Agency resources being used more efficiently.

System outputs

AI-based machine learning classification of FAR risk into low, medium, and high; provides insights on problem clusters, rare-events, and source variables.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): CDEROne Analytics: FISMA-high environment
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): In-house (CDER staff) and contractor teams
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Internal Field Alert Reports data from LSMV
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported