Analyzing process and outcome measures for patients suspected of or having an infection in an entire hospital requires processing large datasets and accounting for numerous patient parameters and guidelines. Rapid, reproducible and adaptable analyses usually need substantial technical expertise but can yield valuable insight for infection management and antimicrobial stewardship (AMS) teams.
This shiny app was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions. Users can filter patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results including antimicrobial resistance, and outcome in length of stay. Results can easily be stratified and grouped to compare defined patient groups based on individual patient features.
All graphs and tables as well as the filtered dataset can be downloaded in various formats. AMS teams can use RadaR to identify areas within their institutions that might benefit from increased support and targeted interventions. Diagnostic and therapeutic procedures can be assessed and analyses can easily be visualized and communicated.
A full description of the entire app can be found here as a preprint: https://preprints.jmir.org/preprint/12843 (We really submitted this app to a scientific journal to show a proof of principle that R, shiny, and open source software can effectively be used in this field.)