eICU Collaborative Research Database Demo

Abstract

This project is a demo version of the eICU Collaborative Research Database, a multi-center database comprised of deidentified health data for over 200,000 admissions to ICUs across the United States between 2014-2015. The database includes vital sign measurements, care plan documentation, severity of illness measures, diagnosis information, and treatment information. Data is collected through the Philips eICU program, a critical care telehealth program that delivers information to caregivers at the bedside. This open access demo allows researchers to ascertain whether the eICU Collaborative Research Database is suitable for their work. It includes over 2,500 unit stays selected from 20 of the larger hospitals in the eICU Collaborative Research Database.

Background

Philips Healthcare has developed an eICU telehealth system for critically ill patients, which provides 24 hour support for caregivers at the bedside. It is a supplement — not a replacement — to the bedside team, and the data utilized by the remote caregivers is archived for research purposes. A subset of the data is made available to researchers via the eICU Collaborative Research Database, a multi-center intensive care unit database covering over 200,000 admissions to ICUs monitored by eICU Programs across the United States [1]. The database is deidentified, and includes vital sign measurements, care plan documentation, APACHE severity of illness measures, diagnosis information, and treatment details. This open access demo allows researchers to ascertain whether the eICU Collaborative Research Database is suitable for their work.

Methods

The demo dataset contains data associated with (ICU) stays for over 2,500 unit stays selected from 20 of the larger hospitals in the eICU Collaborative Research Database. All tables are deidentified to meet the safe harbor provision of the US Health Insurance Portability and Accountability Act (HIPAA). These provisions include the removal of all protected health information. Hospital and unit identifiers have also been removed to protect the privacy of contributing organizations. The schema was established in collaboration with Privacert (Cambridge, MA), who certified the re-identification risk as meeting safe harbor standards (HIPAA Certification no. 1031219-2).

Data Description

Data include vital signs, laboratory measurements, medications, APACHE components, care plan information, admission diagnosis, patient history, time-stamped diagnoses from a structured problem list, and similarly chosen treatments. Data from each patient is collected into a common warehouse only if certain "interfaces" are available. Each interface is used to transform and load a certain type of data: vital sign interfaces incorporate vital signs, laboratory interfaces provide measurements on blood samples, and so on. It is important to be aware that different care units may have different interfaces in place, and that the lack of an interface will result in no data being available for a given patient, even if those measurements were made in reality. The data is provided as CSVs that can be loaded into a relational database using code provided in the eICU Code Repository [2]. An gzipped SQLite version of the database is also provided in the sqlite folder for convenience.

Usage Notes

The demo provides an opportunity to review the structure and content of the eICU Collaborative Research Database before deciding whether or not to carry out an analysis on the full version. The demo also provides a useful sample dataset to demonstrate that code developed for the eICU Collaborative Research Database is functional and returning expected results (for example, for verifying behaviour in unit tests and demonstrating reproducibility in published papers).

Release Notes

This demo is associated with eICU-CRD v2.0.

Version 2.0.1

• Added an SQLite3 version of the dataset.
• Removed unnecessary spacing in the admissionDx, allergy, and customLab tables.

Acknowledgements

The authors would like to thank the Philips eICU Research Institute and Philips Healthcare for contribution of the data. The authors would also like to thank Andrew A. Kramer for insightful comments regarding the data and Dina Demner-Fushman for helpful feedback on the deidentification process.

Conflicts of Interest

The work was supported by grants NIH-R01-EB017205, NIH-R01-EB001659, and NIH-R01-GM104987 from the National Institutes of Health. The MIT Laboratory for Computational Physiology received funding from Philips Healthcare to undertake work on the database described in this paper. O.B. is an employee of Philips Healthcare.

References

1. Pollard TJ, Johnson AEW, Raffa JD, Celi LA, Mark RG and Badawi O. The eICU Collaborative Research Database, a freely available multi-center database for critical care research. Scientific Data (2018). DOI: http://dx.doi.org/10.1038/sdata.2018.178.
2. eICU Code Repository on GitHub. https://github.com/MIT-LCP/eicu-code [Accessed: 1 April 2021]