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Big Data-Enabled Nursing

Education, Research and Practice

  • Book
  • © 2017

Overview

Editors:
  1. Connie W. Delaney

    1. School of Nursing, University of Minnesota School of Nursing, Minneapolis, USA

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  2. Charlotte A. Weaver

    1. Issaquah, USA

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  3. Judith J. Warren

    1. School of Nursing, University of Kansas School of Nursing, Plattsmouth, USA

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  4. Thomas R. Clancy

    1. School of Nursing, University of Minnesota, Minneapolis, USA

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  5. Roy L. Simpson

    1. Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, USA

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  • Dedicated to teaching the application of big data within nursing
  • Makes extensive use of illustrations to expand on key thematic points
  • Contextualizes strategies for effective modern nursing practice
  • Provides a strategic study of the use of big data across healthcare

Part of the book series: Health Informatics (HI)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xxxv
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  2. The New and Exciting World of “Big Data”

    1. Front Matter

      Pages 1-1
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    2. Why Big Data?: Why Nursing?

      • Connie W. Delaney, Roy L. Simpson
      Pages 3-10

    3. Big Data in Healthcare: A Wide Look at a Broad Subject

      • Marisa L. Wilson, Charlotte A. Weaver, Paula M. Procter, Murielle S. Beene
      Pages 11-31

    4. A Big Data Primer

      • Judith J. Warren
      Pages 33-59

  3. Technologies and Science of Big Data

    1. Front Matter

      Pages 61-61
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    2. A Closer Look at Enabling Technologies and Knowledge Value

      • Thomas R. Clancy
      Pages 63-78

    3. Big Data in Healthcare: New Methods of Analysis

      • Sarah N. Musy, Michael Simon
      Pages 79-101

    4. Generating the Data for Analyzing the Effects of Interprofessional Teams for Improving Triple Aim Outcomes

      • May Nawal Lutfiyya, Teresa Schicker, Amy Jarabek, Judith Pechacek, Barbara Brandt, Frank Cerra
      Pages 103-114

    5. Wrestling with Big Data: How Nurse Leaders Can Engage

      • Jane Englebright, Edmund Jackson
      Pages 115-137

    6. Inclusion of Flowsheets from Electronic Health Records to Extend Data for Clinical and Translational Science Awards (CTSA) Research

      • Bonnie L. Westra, Beverly Christie, Grace Gao, Steven G. Johnson, Lisiane Pruinelli, Anne LaFlamme et al.
      Pages 139-155

    7. Working in the New Big Data World: Academic/Corporate Partnership Model

      • William Crown, Thomas R. Clancy
      Pages 157-180

  4. Revolution of Knowledge Discovery, Dissemination, Translation Through Data Science

    1. Front Matter

      Pages 181-181
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    2. Data Science: Transformation of Research and Scholarship

      • Lynda R. Hardy, Philip E. Bourne
      Pages 183-209

    3. Answering Research Questions with National Clinical Research Networks

      • Katherine K. Kim, Satish M. Mahajan, Julie A. Miller, Joe V. Selby
      Pages 211-226

    4. Enhancing Data Access and Utilization: Federal Big Data Initiative and Relevance to Health Disparities Research

      • Rosaly Correa-de-Araujo
      Pages 227-251

    5. Big Data Impact on Transformation of Healthcare Systems

      • Gay L. Landstrom
      Pages 253-263

    6. State of the Science in Big Data Analytics

      • C. F. Aliferis
      Pages 265-284

  5. Looking at Today and the Near Future

    1. Front Matter

      Pages 285-286
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    2. Big Data Analytics Using the VA’s ‘VINCI’ Database to Look at Delirium

      • Charlene Weir, Joanne LaFluer, Bryan Gibson, Qing Zeng
      Pages 287-299
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Keywords

About this book

Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing.  It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. 

Editors and Affiliations

  • School of Nursing, University of Minnesota School of Nursing, Minneapolis, USA

    Connie W. Delaney

  • Issaquah, USA

    Charlotte A. Weaver

  • School of Nursing, University of Kansas School of Nursing, Plattsmouth, USA

    Judith J. Warren

  • School of Nursing, University of Minnesota, Minneapolis, USA

    Thomas R. Clancy

  • Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, USA

    Roy L. Simpson

About the editors

Five editors are national and international experts in nursing & health informatics, representing  all sectors including  health systems,  corporate and vendors, academia,  policy, and professional associations.  All invited authors are recognized experts.

Bibliographic Information

  • Book Title: Big Data-Enabled Nursing

  • Book Subtitle: Education, Research and Practice

  • Editors: Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson

  • Series Title: Health Informatics

  • DOI: https://doi.org/10.1007/978-3-319-53300-1

  • Publisher: Springer Cham

  • eBook Packages: Medicine, Medicine (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-53299-8Published: 10 November 2017

  • Softcover ISBN: 978-3-319-85120-4Published: 30 August 2018

  • eBook ISBN: 978-3-319-53300-1Published: 02 November 2017

  • Series ISSN: 1431-1917

  • Series E-ISSN: 2197-3741

  • Edition Number: 1

  • Number of Pages: XXXV, 488

  • Number of Illustrations: 13 b/w illustrations, 48 illustrations in colour

  • Topics: Health Informatics, Health Informatics, Nursing

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