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"Big data" and the electronic health record.

M K Ross1, W Wei, L Ohno-Machado

  • 1Lucila Ohno-Machado, Division of Biomedical Informatics, 9500 Gilman Drive, MC 0505, La Jolla, California, 92037-0505, USA, Tel: +1 858 822 4931,

Yearbook of Medical Informatics
|August 16, 2014
PubMed
Summary
This summary is machine-generated.

Electronic Health Record (EHR) systems generate vast amounts of data. This review explores "big data" in EHRs, highlighting applications in data mining and clinical decision support to improve patient care.

Keywords:
Electronic health recordsdata miningnatural language processingprivacyquality improvementsecurity

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Area of Science:

  • Biomedical Informatics
  • Health Data Science
  • Clinical Data Analytics

Background:

  • The widespread implementation of Electronic Health Record (EHR) systems has led to the accumulation of extensive patient data.
  • Transforming this clinical data into actionable knowledge for improved patient care is a long-standing goal in biomedical informatics.
  • The concept of
  • big data
  • in the context of EHR systems is gaining increasing recognition.

Purpose of the Study:

  • To review the literature on
  • big data
  • within EHR systems over the past three years.
  • To identify and report on practical examples of secondary data use from EHRs.
  • To categorize current research themes related to EHR big data.

Main Methods:

  • A systematic search of the PubMed database was conducted for articles published between January 1, 2011, and November 1, 2013.
  • Initial keywords included
  • big data
  • and EHR, with subsequent keyword expansion based on retrieved articles.
  • Articles were manually selected based on predefined inclusion and exclusion criteria.

Main Results:

  • The review identified articles focusing on data mining techniques such as pharmacovigilance, phenotyping, and natural language processing.
  • Key application areas included clinical decision support, personal health monitoring, and social media data integration.
  • Research also addressed critical aspects of privacy and security in handling large-scale health data.

Conclusions:

  • The global adoption of EHRs facilitates the collection of substantial clinical data, fueling the growth of
  • big data
  • research in healthcare.
  • The interpretation and application of concepts within healthcare big data are diverse.
  • The crucial next step involves translating healthcare big data into practical, actionable knowledge to enhance patient outcomes.