HHS · no agency ID · record R0898

AI identification of "High-Risk" Health Centers

Department of Health and Human Services · HHS/HRSA

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: Forecasting and prediction, Risk scoring and triage, Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual identification of high-risk health centers is resource-intensive and may miss key indicators across large datasets. Would support a proactive, data-driven approach to inform site visit schedules and technical assistance planning.

Expected benefits

AI-driven risk identification would allow BPHC to better allocate resources, prioritize site visits, and provide tailored technical assistance. This will help improve compliance, operational performance, and ultimately the quality of care delivered by health centers

System outputs

The system would use predictive analytics and risk modeling to generate a prioritized list of health centers considered "high-risk" based on predefined indicators (e.g., patient safety concerns, poor quality metrics, application anomalies). Outputs will support more targeted oversight and TA deployment schedules.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
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: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
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