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Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system

BACKGROUND: Early threat detection and situational awareness are vital to achieving a comprehensive and accurate view of health-related events for federal, state, and local health agencies. Key to this are public health and syndromic surveillance systems that can analyze large data sets to discover...

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Autores principales: Lucero-Obusan, Cynthia, Oda, Gina, Mostaghimi, Anoshiravan, Schirmer, Patricia, Holodniy, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8830960/
https://www.ncbi.nlm.nih.gov/pubmed/35144575
http://dx.doi.org/10.1186/s12889-022-12578-2
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author Lucero-Obusan, Cynthia
Oda, Gina
Mostaghimi, Anoshiravan
Schirmer, Patricia
Holodniy, Mark
author_facet Lucero-Obusan, Cynthia
Oda, Gina
Mostaghimi, Anoshiravan
Schirmer, Patricia
Holodniy, Mark
author_sort Lucero-Obusan, Cynthia
collection PubMed
description BACKGROUND: Early threat detection and situational awareness are vital to achieving a comprehensive and accurate view of health-related events for federal, state, and local health agencies. Key to this are public health and syndromic surveillance systems that can analyze large data sets to discover patterns, trends, and correlations of public health significance. In 2020, Department of Veterans Affairs (VA) evaluated its public health surveillance system and identified areas for improvement. METHODS: Using the Centers for Disease Control and Prevention (CDC) Guidelines for Evaluating Public Health Surveillance Systems, we assessed the ability of the Praedico Surveillance System to perform public health surveillance for a variety of health issues and evaluated its performance compared to an enterprise data solution (VA Corporate Data Warehouse), legacy surveillance system (VA ESSENCE) and a national, collaborative syndromic surveillance platform (CDC NSSP BioSense). RESULTS: Review of system attributes found that the system was simple, flexible, and stable. Representativeness, timeliness, sensitivity, and Predictive Value Positive were acceptable but could be further improved. Data quality issues and acceptability present challenges that potentially affect the overall usefulness of the system. CONCLUSIONS: Praedico is a customizable surveillance and data analytics platform built on big data technologies. Functionality is straightforward, with rapid query generation and runtimes. Data can be graphed, mapped, analyzed, and shared with key decision makers and stakeholders. Evaluation findings suggest that future development and system enhancements should focus on addressing Praedico data quality issues and improving user acceptability. Because Praedico is designed to handle big data queries and work with data from a variety of sources, it could be enlisted as a tool for interdepartmental and interagency collaboration and public health data sharing. We suggest that future system evaluations include measurements of value and effectiveness along with additional organizations and functional assessments.
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spelling pubmed-88309602022-02-11 Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system Lucero-Obusan, Cynthia Oda, Gina Mostaghimi, Anoshiravan Schirmer, Patricia Holodniy, Mark BMC Public Health Research BACKGROUND: Early threat detection and situational awareness are vital to achieving a comprehensive and accurate view of health-related events for federal, state, and local health agencies. Key to this are public health and syndromic surveillance systems that can analyze large data sets to discover patterns, trends, and correlations of public health significance. In 2020, Department of Veterans Affairs (VA) evaluated its public health surveillance system and identified areas for improvement. METHODS: Using the Centers for Disease Control and Prevention (CDC) Guidelines for Evaluating Public Health Surveillance Systems, we assessed the ability of the Praedico Surveillance System to perform public health surveillance for a variety of health issues and evaluated its performance compared to an enterprise data solution (VA Corporate Data Warehouse), legacy surveillance system (VA ESSENCE) and a national, collaborative syndromic surveillance platform (CDC NSSP BioSense). RESULTS: Review of system attributes found that the system was simple, flexible, and stable. Representativeness, timeliness, sensitivity, and Predictive Value Positive were acceptable but could be further improved. Data quality issues and acceptability present challenges that potentially affect the overall usefulness of the system. CONCLUSIONS: Praedico is a customizable surveillance and data analytics platform built on big data technologies. Functionality is straightforward, with rapid query generation and runtimes. Data can be graphed, mapped, analyzed, and shared with key decision makers and stakeholders. Evaluation findings suggest that future development and system enhancements should focus on addressing Praedico data quality issues and improving user acceptability. Because Praedico is designed to handle big data queries and work with data from a variety of sources, it could be enlisted as a tool for interdepartmental and interagency collaboration and public health data sharing. We suggest that future system evaluations include measurements of value and effectiveness along with additional organizations and functional assessments. BioMed Central 2022-02-10 /pmc/articles/PMC8830960/ /pubmed/35144575 http://dx.doi.org/10.1186/s12889-022-12578-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lucero-Obusan, Cynthia
Oda, Gina
Mostaghimi, Anoshiravan
Schirmer, Patricia
Holodniy, Mark
Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title_full Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title_fullStr Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title_full_unstemmed Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title_short Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system
title_sort public health surveillance in the u.s. department of veterans affairs: evaluation of the praedico surveillance system
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8830960/
https://www.ncbi.nlm.nih.gov/pubmed/35144575
http://dx.doi.org/10.1186/s12889-022-12578-2
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