4.6 Article

Public health surveillance in the US Department of Veterans Affairs: evaluation of the Praedico surveillance system

期刊

BMC PUBLIC HEALTH
卷 22, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12889-022-12578-2

关键词

Big data; Health informatics; Public health; Surveillance; Syndromic surveillance; System evaluation; Electronic health records; Veterans

资金

  1. intramural VHA funds

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Praedico is a customizable surveillance and data analytics platform built on big data technologies. The system has been evaluated and found to be simple, flexible, and stable, with acceptable performance in terms of representativeness, timeliness, sensitivity, and Predictive Value Positive. However, there are still areas for improvement, including data quality and user acceptability. The system has the potential to be used for interdepartmental and interagency collaboration and public health data sharing.
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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