The eICU collaborative research database, a freely available multi-center database for critical care research

Scientific Data

Volumn 5, Issue , 2018, Pages

  Pollard, Tom J ^a   Johnson, Alistair E W ^a   Raffa, Jesse D ^a   Celi, Leo A ^a,b   Mark, Roger G ^a,b   Badawi, Omar ^a,c,d  

^a Massachusetts Institute of Technology Cambridge   (United States)

^b BETH ISRAEL DEACONESS MEDICAL CENTER   (United States)

^c PHILIPS HEALTHCARE   (United States)

^d UNIVERSITY OF MARYLAND SCHOOL OF PHARMACY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL TRIAL; CRITICAL ILLNESS; FACTUAL DATABASE; HUMAN; INTENSIVE CARE; INTENSIVE CARE UNIT; MULTICENTER STUDY; TELEMEDICINE; UNITED STATES;

CRITICAL CARE; CRITICAL ILLNESS; DATABASES, FACTUAL; HUMANS; INTENSIVE CARE UNITS; TELEMEDICINE; UNITED STATES;

EID: 85053358651     PISSN: None     EISSN: 20524463     Source Type: Journal    
DOI: 10.1038/sdata.2018.178     Document Type: Article

References (22)

1. Kelly, F. E., Fong, K., Hirsch, N. & Nolan, J. P. Intensive care medicine is 60 years old: the history and future of the intensive care unit. Clinical medicine 14, 376–379 (2014).
2. Adhikari, N. K., Fowler, R. A., Bhagwanjee, S. & Rubenfeld, G. D. Critical care and the global burden of critical illness in adults. The Lancet 376, 1339–1346 (2010).
3. Celi, L. A., Mark, R. G., Stone, D. J. & Montgomery, R. A. “Big Data” in the Intensive Care Unit: Closing the Data Loop. Am J Respir Crit Care Med 187, 1157–1160 (2013).
4. Johnson, A. E. W. et al. Machine learning and decision support in critical care. Proceedings of the IEEE 104, 444–466 (2016).
5. Lilly, C. M. et al. A multicenter study of icu telemedicine reengineering of adult critical care. CHEST Journal 145, 500–507 (2014).
6. McShea, M., Holl, R., Badawi, O., Riker, R. R. & Silfen, E. The eICU research institute-a collaboration between industry, healthcare providers, and academia. IEEE Engineering in Medicine and Biology Magazine 29, 18–25 (2010).
7. Saeed, M. et al. Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II): a public-access intensive care unit database. Critical care medicine 39, 952–960 (2011).
8. Johnson, A. E. W. et al. MIMIC-III, a freely accessible critical care database. Scientific Data 3 (2016).
9. United States. Cong. House. Health Insurance Portability and Accountability Act of 1996. 104th Congress https://www.gpo.gov/fdsys/pkg/PLAW-104publ191/html/PLAW-104publ191.htm (1996).
10. Neamatullah, I. et al. Automated de-identification of free-text medical records. BMC medical informatics and decision making 8, 1–32 (2008).
11. Finney, J. M., Walker, A. S., Peto, T. M. & Wyllie, D. H. An efficient record linkage scheme using graphical analysis for identifier error detection. BMC Medical Informatics and Decision Making 11, 7 (2011).
12. Johnson, A. E. W. & Pollard, T. J. MIT-LCP/eicu-data-paper: eICU-CRD Code for Data Descriptor. Zenodo https://doi.org/10.5281/zenodo.1248994 (2018).
13. Pollard, T. J. et al. MIT-LCP/eicu-code: eICU-CRD Code Repository. Zenodo https://doi.org/10.5281/zenodo.1249016 (2018).
14. Pollard, T. J., Johnson, A. E. W., Raffa, J. & Mark, R. G. tableone: An open source Python package for producing summary statistics for research papers. JAMIA Open 1(1) https://doi.org/10.1093/jamiaopen/ooy012 (2018).
15. Zimmerman, J. E., Kramer, A. A., McNair, D. S. & Malila, F. M. Acute physiology and chronic health evaluation (APACHE)IV: hospital mortality assessment for today's critically ill patients. Critical Care Medicine 34, 1297–1310 (2006).
16. Goldberger, A. L. et al. PhysioBank, PhysioToolkit, and PhysioNet. Circulation 101, e215–e220 (2000).
17. Johnson, A. E. W., Pollard, T. J. & Badawi, O. eICU Collaborative Research Database: Documentation and Website https://eicucrd.mit.edu (2018).
18. Braunschweiger, P. & Goodman, K. W. The CITI program: an international online resource for education in human subjects protection and the responsible conduct of research. Academic Medicine 82, 861–864 (2007).
19. Wilson, G. et al. Best practices for scientific computing. PLOS Biology 12, e1001745 (2014).
20. Johnson, A. E. W., Pollard, T. J. & Mark, R. G. Reproducibility in critical care: a mortality prediction case study. Proceedings of Machine Learning Research 68, 361–376 (2017).
21. Pérez, F. & Granger, B. IPython: a system for interactive scientific computing. Computing in Science and Engineering 9, 21–29 (2007).
22. Kluyver, T. et al. Jupyter notebooks-a publishing format for reproducible computational workflows. In ELPUB, pages 87–90 (2016).