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MIMIC-III, a freely accessible critical care database

Written for the Research library (claude-opus-5-5) from the paper text. Original — nature.com/articles/sdata201635.pdf

Summary

Hospitals have moved quickly to electronic records, but systems rarely interoperate. As a result, clinical data seldom become usable for research, and closed datasets make studies hard to reproduce. This data descriptor presents MIMIC-III (Medical Information Mart for Intensive Care), the successor to MIMIC-II. The MIT Laboratory for Computational Physiology built it from routine care records at Beth Israel Deaconess Medical Center in Boston.

The team gathered data from three kinds of sources:

  • two ICU information systems, Philips CareVue and iMDsoft MetaVision;
  • the hospital's electronic health record databases;
  • the Social Security death file.

They deidentified the records and organized them into relational tables. These cover vital signs, lab results, medications, fluid balance, billing codes, and free-text notes and reports.

The result is a critical care resource spanning over ten years. Any qualified researcher can obtain it after completing training and signing a data use agreement. Its value is that it supports reproducible clinical studies, teaching and method development at a scale otherwise unavailable. This includes NLP on clinical notes. A shared community code repository supports this work.

Key points

  • Scale: 38,597 adult patients, 49,785 hospital admissions and 53,423 ICU stays (2001–2012), plus 7,870 neonates (2001–2008). Adults have a median age of 65.8 years, 55.9% are male, and in-hospital mortality is 11.5%.
  • Detail per admission: each admission averages about 4,579 charted observations (CHARTEVENTS) and 380 lab measurements (LABEVENTS). Free text is stored in NOTEEVENTS. Fluid intake data could not be merged across the two ICU systems, so it is kept in separate tables (INPUTEVENTS_CV and INPUTEVENTS_MV).
  • Access: the data come as CSV files with import scripts for PostgreSQL, MySQL and MonetDB. Downloads go through PhysioNetWorks after the researcher completes a human-subjects course that covers HIPAA and signs a data use agreement. Approval takes at least a week.
  • Community: the GitHub repository MIT-LCP/mimic-code provides code for severity scores, comorbidity scores, and ventilation and vasopressor durations. The project also runs datathons and supports mapping to OMOP-CDM. MIMIC is already used in courses at Stanford, MIT, Georgia Tech, UT Austin and Columbia.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Other

Cited by

527 papers of our library cite it (of the 140673 whose bibliographies we read); 9 of them have a page here, 518 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1038/sdata.2016.35

@inproceedings{johnson2016mimic,
  title = {{MIMIC-III, a freely accessible critical care database}},
  author = {Johnson, Alistair E. W. and Pollard, Tom and Shen, Lu and Lehman, Li-wei H. and Feng, Mengling and Ghassemi, Mohammad M. and Moody, Benjamin and Szolovits, Peter and Celi, Leo Anthony and Mark, Roger G.},
  booktitle = {Scientific Data},
  year = {2016},
  doi = {10.1038/sdata.2016.35},
  url = {https://doi.org/10.1038/sdata.2016.35}
}

References

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  14. Aboab, J. et al. A ‘datathon’ model to support cross-disciplinary collaboration. Science Translational Medicine 8, 333–ps8 (2016). Data Citation 1. Pollard, T. J. & Johnson, A. E. W. The MIMIC-III Clinical Database http://dx.doi.org/10.13026/C2XW26 (2016). \#\# Acknowledgements This research and devel… — [doi:10.13026/c2xw26](https://doi.org/10.13026/c2xw26) ↗