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Multicenter Study
. 2018 Sep 11:5:180178.
doi: 10.1038/sdata.2018.178.

The eICU Collaborative Research Database, a freely available multi-center database for critical care research

Tom J Pollard  1 , Alistair E W Johnson  1 , Jesse D Raffa  1 , Leo A Celi  1   2 , Roger G Mark  1   2 , Omar Badawi  1   3   4
Affiliations
Multicenter Study

The eICU Collaborative Research Database, a freely available multi-center database for critical care research

Tom J Pollard et al. Sci Data. .

Abstract

Critical care patients are monitored closely through the course of their illness. As a result of this monitoring, large amounts of data are routinely collected for these patients. Philips Healthcare has developed a telehealth system, the eICU Program, which leverages these data to support management of critically ill patients. Here we describe the eICU Collaborative Research Database, a multi-center intensive care unit (ICU)database with high granularity data for over 200,000 admissions to ICUs monitored by eICU Programs across the United States. The database is deidentified, and includes vital sign measurements, care plan documentation, severity of illness measures, diagnosis information, treatment information, and more. Data are publicly available after registration, including completion of a training course in research with human subjects and signing of a data use agreement mandating responsible handling of the data and adhering to the principle of collaborative research. The freely available nature of the data will support a number of applications including the development of machine learning algorithms, decision support tools, and clinical research.

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Conflict of interest statement

The research and development 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.

Figures

Figure 1
Figure 1. Organization of patient tracking information.
Each patient is identified by a unique integer: the uniquePid. For each uniquePid, a patient may have distinct hospitalizations denoted by patientHealthSystemStayId. Finally, for each hospitalization, a patient may have distinct unit stays, denoted by patientUnitStayId. patientUnitStayId is the primary identifier used for linking data across tables.
Figure 2
Figure 2. Visualization of a single patient's stay.
Data shown are a subset of all data available, and include: high granularity vital signs (dashed lines, sourced from vitalPeriodic and vitalAperiodic), nurse validated vital signs (solid markers, sourced from nurseCharting), blood product administration (green cross, sourced from intakeOutput), and laboratory measurements (sourced from lab).
See this image and copyright information in PMC

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References

Data Citations

    1. Pollard T. J., Johnson A. E. W., Raffa J., Badawi O. 2018. PhysioNet. https://doi.org/10.13026/C2WM1R - DOI

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