Big data in healthcare - the promises, challenges and opportunities from a research perspective: A case study with a model database

Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremen...

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Published in:AMIA ... Annual Symposium proceedings Vol. 2017; p. 384
Main Authors: Adibuzzaman, Mohammad, DeLaurentis, Poching, Hill, Jennifer, Benneyworth, Brian D
Format: Journal Article
Language:English
Published: United States 2017
Subjects:
Big Data
Confidentiality
Data Collection
Databases, Factual
Electronic Health Records
Health Information Interoperability
Humans
Intensive Care Units
ISSN:1942-597X, 1559-4076
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Abstract Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.
AbstractList Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.
Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.
Author Adibuzzaman, Mohammad
DeLaurentis, Poching
Benneyworth, Brian D
Hill, Jennifer
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  surname: DeLaurentis
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  organization: Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana, USA
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  fullname: Benneyworth, Brian D
  organization: Children's Health Services Research Group, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, USA
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SubjectTerms Big Data
Confidentiality
Data Collection
Databases, Factual
Electronic Health Records
Health Information Interoperability
Humans
Intensive Care Units
Title Big data in healthcare - the promises, challenges and opportunities from a research perspective: A case study with a model database
URI https://www.ncbi.nlm.nih.gov/pubmed/29854102
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