Skip to main content
Top
Published in: BMC Medical Informatics and Decision Making 1/2016

Open Access 01-12-2015 | Software

A web-based data visualization tool for the MIMIC-II database

Authors: Joon Lee, Evan Ribey, James R. Wallace

Published in: BMC Medical Informatics and Decision Making | Issue 1/2016

Login to get access

Abstract

Background

Although MIMIC-II, a public intensive care database, has been recognized as an invaluable resource for many medical researchers worldwide, becoming a proficient MIMIC-II researcher requires knowledge of SQL programming and an understanding of the MIMIC-II database schema. These are challenging requirements especially for health researchers and clinicians who may have limited computer proficiency. In order to overcome this challenge, our objective was to create an interactive, web-based MIMIC-II data visualization tool that first-time MIMIC-II users can easily use to explore the database.

Results

The tool offers two main features: Explore and Compare. The Explore feature enables the user to select a patient cohort within MIMIC-II and visualize the distributions of various administrative, demographic, and clinical variables within the selected cohort. The Compare feature enables the user to select two patient cohorts and visually compare them with respect to a variety of variables. The tool is also helpful to experienced MIMIC-II researchers who can use it to substantially accelerate the cumbersome and time-consuming steps of writing SQL queries and manually visualizing extracted data.

Conclusions

Any interested researcher can use the MIMIC-II data visualization tool for free to quickly and conveniently conduct a preliminary investigation on MIMIC-II with a few mouse clicks. Researchers can also use the tool to learn the characteristics of the MIMIC-II patients. Since it is still impossible to conduct multivariable regression inside the tool, future work includes adding analytics capabilities. Also, the next version of the tool will aim to utilize MIMIC-III which contains more data.
Literature
2.
go back to reference Lee J, Scott DJ, Villarroel M, Clifford GD, Saeed M, Mark RG. Open-access MIMIC-II database for intensive care research. IEEE Eng Med Biol Soc. 2011;2011:8315–8. Lee J, Scott DJ, Villarroel M, Clifford GD, Saeed M, Mark RG. Open-access MIMIC-II database for intensive care research. IEEE Eng Med Biol Soc. 2011;2011:8315–8.
3.
go back to reference Lee J, Maslove DM, Dubin JA. Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric. PLoS One. 2015;10, e0127428.PubMedCentralCrossRefPubMed Lee J, Maslove DM, Dubin JA. Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric. PLoS One. 2015;10, e0127428.PubMedCentralCrossRefPubMed
4.
go back to reference Mandelbaum T, Lee J, Scott DJ, Mark RG, Malhotra A, Howell MD, et al. Empirical relationships among oliguria, creatinine, mortality, and renal replacement therapy in the critically ill. Intensive Care Med. 2013;39:414–9.PubMedCentralCrossRefPubMed Mandelbaum T, Lee J, Scott DJ, Mark RG, Malhotra A, Howell MD, et al. Empirical relationships among oliguria, creatinine, mortality, and renal replacement therapy in the critically ill. Intensive Care Med. 2013;39:414–9.PubMedCentralCrossRefPubMed
5.
go back to reference Lee J, De Louw E, Niemi M, Nelson R, Mark RG, Celi LA, et al. Association between fluid balance and survival in critically ill patients. J Intern Med. 2014. Lee J, De Louw E, Niemi M, Nelson R, Mark RG, Celi LA, et al. Association between fluid balance and survival in critically ill patients. J Intern Med. 2014.
6.
go back to reference Danziger J, William JH, Scott DJ, Lee J, Lehman L-W, Mark RG, et al. Proton-pump inhibitor use is associated with low serum magnesium concentrations. Kidney Int. 2013;83:692–9.CrossRefPubMed Danziger J, William JH, Scott DJ, Lee J, Lehman L-W, Mark RG, et al. Proton-pump inhibitor use is associated with low serum magnesium concentrations. Kidney Int. 2013;83:692–9.CrossRefPubMed
7.
go back to reference Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:E215–20.CrossRefPubMed Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:E215–20.CrossRefPubMed
8.
go back to reference Scott DJ, Lee J, Silva I, Park S, Moody GB, Celi LA, et al. Accessing the public MIMIC-II intensive care relational database for clinical research. BMC Med Inform Decis Mak. 2013;13:9.PubMedCentralCrossRefPubMed Scott DJ, Lee J, Silva I, Park S, Moody GB, Celi LA, et al. Accessing the public MIMIC-II intensive care relational database for clinical research. BMC Med Inform Decis Mak. 2013;13:9.PubMedCentralCrossRefPubMed
9.
go back to reference Lowe HJ, Ferris TA, Hernandez PM, Weber SC. STRIDE--An integrated standards-based translational research informatics platform. AMIA Annu Symp Proc. 2009;2009:391–5.PubMedCentralPubMed Lowe HJ, Ferris TA, Hernandez PM, Weber SC. STRIDE--An integrated standards-based translational research informatics platform. AMIA Annu Symp Proc. 2009;2009:391–5.PubMedCentralPubMed
10.
go back to reference Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S, et al. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc. 2010;17:124–30.PubMedCentralCrossRefPubMed Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S, et al. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc. 2010;17:124–30.PubMedCentralCrossRefPubMed
11.
go back to reference Warner JL, Zhang P, Liu J, Alterovitz G. Classification of hospital acquired complications using temporal clinical information from a large electronic health record. J Biomed Inform. 2016;59:209–17.CrossRef Warner JL, Zhang P, Liu J, Alterovitz G. Classification of hospital acquired complications using temporal clinical information from a large electronic health record. J Biomed Inform. 2016;59:209–17.CrossRef
Metadata
Title
A web-based data visualization tool for the MIMIC-II database
Authors
Joon Lee
Evan Ribey
James R. Wallace
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2016
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-016-0256-9

Other articles of this Issue 1/2016

BMC Medical Informatics and Decision Making 1/2016 Go to the issue