CC BY-NC-ND 4.0 · Appl Clin Inform 2021; 12(04): 944-953
DOI: 10.1055/s-0041-1735973
State of the Art/Best Practice Paper

Health Intelligence Atlas: A Core Tool for Public Health Intelligence

Gabriela M. Wilson
1  Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, Arlington, Texas, United States
,
Marion J. Ball
1  Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, Arlington, Texas, United States
,
Peter Szczesny
2  Public Affairs, RAD Team, Ipsos, New York, New York, United States
,
Samuel Haymann
2  Public Affairs, RAD Team, Ipsos, New York, New York, United States
,
Mark Polyak
3  Global Public Affairs, Ipsos, Washington, District of Columbia, United States
,
Talmage Holmes
4  Tarrant County Public Health, Fort Worth, Texas, United States
,
John S. Silva
1  Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, Arlington, Texas, United States
› Author Affiliations
Funding This project was funded from institutional money. No additional funding was received from external sources.

Abstract

Background The dramatic increase in complexity and volume of health data has challenged traditional health systems to deliver useful information to their users. The novel coronavirus disease 2019 (COVID-19) pandemic has further exacerbated this problem and demonstrated the critical need for the 21st century approach. This approach needs to ingest relevant, diverse data sources, analyze them, and generate appropriate health intelligence products that enable users to take more effective and efficient actions for their specific challenges.

Objectives This article characterizes the Health Intelligence Atlas (HI-Atlas) development and implementation to produce Public Health Intelligence (PHI) that supports identifying and prioritizing high-risk communities by public health authorities. The HI-Atlas moves from post hoc observations to a proactive model-based approach for preplanning COVID-19 vaccine preparedness, distribution, and assessing the effectiveness of those plans.

Results Details are presented on how the HI-Atlas merged traditional surveillance data with social intelligence multidimensional data streams to produce the next level of health intelligence. Two-model use cases in a large county demonstrate how the HI-Atlas produced relevant PHI to inform public health decision makers to (1) support identification and prioritization of vulnerable communities at risk for COVID-19 spread and vaccine hesitancy, and (2) support the implementation of a generic model for planning equitable COVID-19 vaccine preparedness and distribution.

Conclusion The scalable models of data sources, analyses, and smart hybrid data layer visualizations implemented in the HI-Atlas are the Health Intelligence tools designed to support real-time proactive planning and monitoring for COVID-19 vaccine preparedness and distribution in counties and states.

Protection of Human and Animal Subjects

This work was reviewed by the Institutional Review Board and concluded it was not humans subjects research.




Publication History

Received: 03 March 2021

Accepted: 11 August 2021

Publication Date:
06 October 2021 (online)

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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