JMIR Publications

ABSTRACT

Background:

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.

Objective:

We describe a software application (RadaR - Rapid analysis of diagnostic and antimicrobial patterns in R) for infection management allowing user-friendly, intuitive and interactive analyses of large datasets without prior in-depth software or programming knowledge.

Methods:

RadaR was built in the open source programming language R using Shiny, an additional package to implement web-application frameworks in R. RadaR was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions.

Results:

RadaR visualizes analytical graphs and statistical summaries in a rapid and interactive manner. 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.

Conclusions:

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. RadaR demonstrates the feasibility of developing software tools for infection management and AMS teams in an open source approach making it free to use and adaptable to different settings.