ricu: R's Interface to Intensive Care Data

TL;DR

The 'ricu' R package provides a flexible, extensible framework for handling diverse ICU datasets, enabling reproducible, multi-center machine learning research in intensive care medicine.

Contribution

It introduces a new R package that standardizes ICU data access, supporting multiple datasets and facilitating robust, reproducible research in intensive care.

Findings

Supports around 100 patient variables across 319,402 ICU admissions.

Enables dataset-agnostic analysis code for multi-center validation.

Facilitates addition of new datasets and clinical concepts.

Abstract

Providing computational infrastructure for handling diverse intensive care unit (ICU) datasets, the R package 'ricu' enables writing dataset-agnostic analysis code, thereby facilitating multi-center training and validation of machine learning models. The package is designed with an emphasis on extensibility both to new datasets as well as clinical data concepts, and currently supports the loading of around 100 patient variables corresponding to a total of 319,402 ICU admissions from 4 data sources collected in Europe and the United States. By allowing for the addition of user-specified medical concepts and data sources the aim of 'ricu' is to foster robust, data-based intensive care research, allowing the user to externally validate their method or conclusion with relative ease, and in turn facilitating reproducible and therefore transparent work in this field.