Name
Abstract | ||
|---|---|---|
Patients in hospital intensive care units (ICUs) are physiologically fragile and unstable, generally have life-threatening conditions, and require close monitoring and rapid therapeutic interventions. Staggering amounts of data are collected in the ICU daily: multi-channel waveforms sampled hundreds of times each second, vital sign time series updated each second or minute, alarms and alerts, lab results, imaging results, records of medication and fluid administration, staff notes and more. Reducing the barriers to data access has the potential to accelerate knowledge generation and ultimately improve patient care. In this interactive tutorial we introduce the eICU Collaborative Research Database: a large, publicly available database created by the MIT Laboratory for Computational Physiology in partnership with the Philips eICU Research Institute. The database contains routinely collected data from over 200,000 admissions to intensive care units across the United States, with representation from 10-12% of US ICU beds. The data facilitates a breadth of research studies, such as investigations into treatment efficacy, discovery of clinical markers in illnesses, and the development of decision support models. Participants in the tutorial gain an overview of the eICU Collaborative Research Database, in particular being introduced to its structure, content, and limitations. Following this overview, participants explore a demo version of the database using a laptop in a hands-on project. This exercise requires minimal technical expertise and gives an insight into the type of study that can be carried out using the database. We also highlight the growing online community centered around secondary analysis of this data. All tutorial materials are open source and publicly available. The eICU Collaborative Research Database offers an unparalleled insight into ICU care. Access to the database is granted to legitimate researchers who request it, following completion of a training course in human subjects research and acceptance of a data use agreement. We anticipate that the research community will use this unique resource to further human knowledge in the field of critical care. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3107411.3107494 | BCB |
Keywords | Field | DocType |
Critical care,data mining,electronic health record | Data science,Psychological intervention,Online community,Laptop,Computer science,Decision support system,Bioinformatics,General partnership,Data access,Intensive care,Database,Interactive Tutorial | Conference |
ISBN | Citations | PageRank |
978-1-4503-4722-8 | 1 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alistair E. W. Johnson | 1 | 58 | 7.15 |
| Tom Pollard | 2 | 10 | 2.66 |
| Leo Anthony Celi | 3 | 53 | 12.79 |
| Roger G. Mark | 4 | 243 | 30.74 |