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Analytics

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Clinical Informatics Study Guide

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Abstract

The analysis of data in healthcare, in both operations and research, comprises a major function throughout the industry. The analysis of data (analytics) and the management and curation of data (informatics) are closely associated and confront similar challenges. Chief among them are issues of data quality, particularly the comparability and consistency of the underlying data. There are myriad applications of analytics, ranging from biomedical research and discovery to fiscal management. The methodologies encompassed by analytics range from tabulation to machine learning, with variations on visualization, statistical models, and dashboards in between. Analytics play a crucial role in healthcare operations, the most high profile examples being case mix determination and clinical decision support. The emerging trends of “big data,” ubiquitous computing, and the anticipated deluge of data streams from omics sciences, continuous wireless monitoring, and personal and home health devices will continue to see analytics transform in the future.

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Authors and Affiliations

  1. Division of General Internal Medicine, Johns Hopkins Medicine, Johns Hopkins University, 2024 E Monument St, Baltimore, MD, 21287, USA

    Christopher G. Chute MD, DrPH

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  1. Christopher G. Chute MD, DrPH
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Correspondence to Christopher G. Chute MD, DrPH .

Editor information

Editors and Affiliations

  1. Department of Emergency Medicine, Indiana University, Indianapolis, Indiana, USA

    John T. Finnell

  2. Richard M. Fairbank School of Public Health, Indiana University, Indianapolis, USA

    Brian E. Dixon

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Chute, C.G. (2016). Analytics. In: Finnell, J., Dixon, B. (eds) Clinical Informatics Study Guide. Springer, Cham. https://doi.org/10.1007/978-3-319-22753-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-22753-5_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22752-8

  • Online ISBN: 978-3-319-22753-5

  • eBook Packages: MedicineMedicine (R0)

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