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Development of Automated Data Quality Indicators and Visualizations using Florida's ESSENCE System


Understanding your data is a fundamental pillar of disease surveillance success. With the increase in automated, electronic surveillance tools many public health users have begun to rely on those tools to produce reports that contain processed results to perform their daily jobs. These tools can focus on the algorithm or visualizations needed to produce the report, and can easily overlook the quality of the incoming data. The phrase “garbage in, garbage out” is often used to describe the value of reports when the incoming data is not of high quality. There is a need then, for systems and tools that help users determine the quality of incoming data.


The objective of this project was to develop visualizations and tools for public health users to determine the quality of their surveillance data. Users should be able to determine or be warned when significant changes have occurred to their data streams, such as a hospital converting from a free-text chief complaint to a pick list. Other data quality factors, such as individual variable completeness and consistency in how values are mapped to standard system selections should be available to users. Once built, these new visualizations should also be evaluated to determine their usefulness in a production disease surveillance system.

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