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This study presents a novel RShiny dashboard prototype to address challenges in collecting and visualizing catheter-associated urinary tract infection (CAUTI) surveillance data, improving health policy decisions.

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Area of Science:

  • Public Health Surveillance
  • Health Informatics
  • Data Visualization

Background:

  • Health care-associated infections, particularly catheter-associated urinary tract infections (CAUTIs), contribute significantly to patient mortality and morbidity.
  • Existing methods for CAUTI surveillance data collection, storage, and visualization present substantial challenges for informing health policy.

Purpose of the Study:

  • To introduce a prototype dashboard solution for public health surveillance data.
  • To address the need for standardized data visualization in CAUTI surveillance.
  • To enhance clinical and policy-level decision-making through improved data accessibility.

Main Methods:

  • Development of a dashboard prototype using open-source R software, RStudio, and the RShiny package.
  • Description of the surveillance system design, rationale for choosing R, and dashboard development process.
  • Implementation of interactive features, including dynamic filters and reactive updates, for user engagement.

Main Results:

  • The prototype dashboard features multiple interactive tabs for data visualization.
  • User interaction is facilitated through dynamic filters and controls, allowing real-time data exploration.
  • The RShiny framework ensures reactive updates, automatically adjusting visualizations based on user-selected parameters.

Conclusions:

  • The developed prototype dashboard demonstrates potential for enhancing clinical and policy decision-making.
  • Interactive data visualization and user-friendly features facilitate better guidance for healthcare professionals and policymakers.
  • Improved data accessibility and visualization are key to addressing CAUTI surveillance challenges.