Closing the data loop: An integrated open access analysis platform for the MIMIC database

We describe a new model for collaborative access, exploration, and analyses of the Medical Information Mart for Intensive Care — III (MIMIC III) database for translational clinical research. The proposed model addresses the significant disconnect between data collection at the point of care and translational clinical research. It addresses problems of data integration, preprocessing, normalization, analyses (along with associated compute back-end), and visualization. The proposed platform is general, and can be easily adapted to other databases. The pre-packaged analyses toolkit is easily extensible, and allows for multi-language support. The platform can be easily federated, mirrored at other locations, and supports a RESTful API for service composition and scaling.

[1]  Sabina Hunziker,et al.  Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients , 2012, Critical Care.

[2]  Peter Szolovits,et al.  MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.

[3]  Shamim Nemati,et al.  A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction , 2014, IEEE Journal of Biomedical and Health Informatics.

[4]  Michael Eisenstein,et al.  Big data: The power of petabytes , 2015, Nature.

[5]  Marzyeh Ghassemi,et al.  Metadata Correction: Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference , 2015, JMIR medical informatics.

[6]  L. Celi,et al.  A Clinical Database-Driven Approach to Decision Support: Predicting Mortality Among Patients with Acute Kidney Injury. , 2011, Journal of healthcare engineering.

[7]  R. Mark,et al.  An investigation of patterns in hemodynamic data indicative of impending hypotension in intensive care , 2010, Biomedical engineering online.

[8]  Leo Anthony Celi,et al.  A Database-driven Decision Support System: Customized Mortality Prediction , 2012, Journal of personalized medicine.

[9]  Michael Stonebraker,et al.  A Demonstration of the BigDAWG Polystore System , 2015, Proc. VLDB Endow..

[10]  Andrew James,et al.  Big Data in the Intensive Care Unit , 2017, AMIA.

[11]  M. Saeed,et al.  Multiparameter Intelligent Monitoring in Intensive Care Ii (Mimic-Ii): A Public-Access Intensive Care Unit Database , 2011 .

[12]  Adam Wilcox,et al.  Mission and Sustainability of Informatics for Integrating Biology and the Bedside (i2b2) , 2014, EGEMS.

[13]  Henrik Loeser,et al.  "One Size Fits All": An Idea Whose Time Has Come and Gone? , 2011, BTW.

[14]  David J. Stone,et al.  "Big data" in the intensive care unit. Closing the data loop. , 2013, American journal of respiratory and critical care medicine.