HHS · no agency ID · record R0736

Publication Portfolio Analytics

Department of Health and Human Services · HHS/CDC

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: 2023-06 (month precision)Source: Jun-23
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The Data Strategy and Analytics Team (DSAT) within OS employs natural language processing (NLP) topic modeling techniques to help programs identify common themes within their publication data. By combining these efforts with bibliometric analysis, we standardize the reporting of media attention, as well as policy and academic citations, by theme and/or CDC organization. Automating these efforts helps the CDC library to optimize their allocation of resources and avoid duplication of effort.

Expected benefits

OS DSAT utilizes NLP to generate organization-specific reports and maintain an agency-wide dashboard. In the case of the agency-wide publication impact dashboard, NLP topic modeling was used to identify common publishing themes for the agency using 10+ years of CDC publication data. This allows users to see trends in publishing topics have changed over time and, when connected to media attention and citation data, allows communication teams, leadership, and scientists interested in assessing the impact of their program’s publications. This dashboard has proven to be impactful, with 105 unique CDC staff across several CIOs and divisions using the dashboard between 7/1/2025 and 8/1/2025.

System outputs

The outputs of the OS DSAT Publication Portfolio Analysis work include a pipeline/ PowerBI dashboard workflow and several center/divisional organizational specific reports and presentations.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): EDAV (Enterprise Data Analytics and Visualization Platform)
Custom-developed code: Yes
Public source code: github.com ↗

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
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: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
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