• Joon Lee, Daniel J Scott, Mauricio Villarroel, Gari D Clifford, Mohammed Saeed, and Roger G Mark.
• Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA. joonlee@mit.edu
• Conf Proc IEEE Eng Med Biol Soc. 2011 Jan 1; 2011: 8315-8.

AbstractThe critical state of intensive care unit (ICU) patients demands close monitoring, and as a result a large volume of multi-parameter data is collected continuously. This represents a unique opportunity for researchers interested in clinical data mining. We sought to foster a more transparent and efficient intensive care research community by building a publicly available ICU database, namely Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II). The data harnessed in MIMIC-II were collected from the ICUs of Beth Israel Deaconess Medical Center from 2001 to 2008 and represent 26,870 adult hospital admissions (version 2.6). MIMIC-II consists of two major components: clinical data and physiological waveforms. The clinical data, which include patient demographics, intravenous medication drip rates, and laboratory test results, were organized into a relational database. The physiological waveforms, including 125 Hz signals recorded at bedside and corresponding vital signs, were stored in an open-source format. MIMIC-II data were also deidentified in order to remove protected health information. Any interested researcher can gain access to MIMIC-II free of charge after signing a data use agreement and completing human subjects training. MIMIC-II can support a wide variety of research studies, ranging from the development of clinical decision support algorithms to retrospective clinical studies. We anticipate that MIMIC-II will be an invaluable resource for intensive care research by stimulating fair comparisons among different studies.

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