The objective of this Bioengineering Research Partnership, established in October 2003, is to develop and evaluate advanced ICU patient monitoring and decision support systems that will improve the efficiency, accuracy, and timeliness of clinical decision-making in critical care. The partnership combines the resources of a powerful interdisciplinary team from academia (MIT), industry (Philips Medical Systems and Philips Research North America), and clinical medicine (Beth Israel Deaconess Medical Center). During the initial funding period of this BRP substantial progress has been achieved, including the development of a massive new research database from more than 30,000 ICU patients (the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II database) and a number of promising advanced monitoring concepts and algorithms. Our initial work has substantiated the hypothesis that sophisticated analysis of the rich multi-parameter data gathered from ICU patients can illuminate their changing pathophysiologic state, and can even provide alerts of impending changes in state. The major goals for the second phase of this BRP are to develop and demonstrate the effectiveness of advanced monitoring concepts and algorithms in laboratory studies utilizing the resources of MIMIC II, and then to carry successful concepts forward into clinical tests in the ICUs of Beth Israel Deaconess Medical Center (BIDMC) and elsewhere with the collaboration of our clinical and industrial partners. We also will enhance the value and availability of the MIMIC II database by adding new adult and neonatal data, designing and improving sophisticated data mining and signal processing tools, and freely distributing to the research community the database and its associated exploration tools via PhysioNet (www.physiionet.org).

Public Health Relevance

The objective of this Bioengineering Research Partnership, established in October 2003, is to develop and evaluate advanced ICU patient monitoring and decision support systems that will improve the efficiency, accuracy, and timeliness of clinical decision-making in critical care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB001659-09
Application #
8120808
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Pai, Vinay Manjunath
Project Start
2003-09-30
Project End
2013-07-31
Budget Start
2011-08-01
Budget End
2012-07-31
Support Year
9
Fiscal Year
2011
Total Cost
$1,173,108
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Other Health Professions
Type
Schools of Arts and Sciences
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Zalewski, Aaron; Long, William; Johnson, Alistair E W et al. (2017) Estimating Patient's Health State Using Latent Structure Inferred from Clinical Time Series and Text. IEEE EMBS Int Conf Biomed Health Inform 2017:449-452
Marshall, Dominic C; Salciccioli, Justin D; Goodson, Ross J et al. (2017) The association between sodium fluctuations and mortality in surgical patients requiring intensive care. J Crit Care 40:63-68
Johnson, Alistair E W; Pollard, Tom J; Shen, Lu et al. (2016) MIMIC-III, a freely accessible critical care database. Sci Data 3:160035
Clifford, Gari D; Silva, Ikaro; Moody, Benjamin et al. (2016) False alarm reduction in critical care. Physiol Meas 37:E5-E23
Aboab, JerĂ´me; Celi, Leo Anthony; Charlton, Peter et al. (2016) A ""datathon"" model to support cross-disciplinary collaboration. Sci Transl Med 8:333ps8
Ghosh, Shameek; Feng, Mengling; Nguyen, Hung et al. (2016) Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure. IEEE J Biomed Health Inform 20:1416-1426
Lynch, Katherine E; Ghassemi, Fatimah; Flythe, Jennifer E et al. (2016) Sodium modelling to reduce intradialytic hypotension during haemodialysis for acute kidney injury in the intensive care unit. Nephrology (Carlton) 21:870-7
Danziger, John; Chen, Ken; Cavender, Susan et al. (2016) Admission Peripheral Edema, Central Venous Pressure, and Survival in Critically Ill Patients. Ann Am Thorac Soc 13:705-11
Chen, Kenneth P; Cavender, Susan; Lee, Joon et al. (2016) Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness. Clin J Am Soc Nephrol 11:602-8
Danziger, John; Chen, Ken P; Lee, Joon et al. (2016) Obesity, Acute Kidney Injury, and Mortality in Critical Illness. Crit Care Med 44:328-34

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