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Big Data-Enabled Nursing

Overview of attention for book
Cover of 'Big Data-Enabled Nursing'

Table of Contents

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    Book Overview
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    Chapter 1 Why Big Data?: Why Nursing?
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    Chapter 2 Big Data in Healthcare: A Wide Look at a Broad Subject
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    Chapter 3 A Big Data Primer
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    Chapter 4 A Closer Look at Enabling Technologies and Knowledge Value
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    Chapter 5 Big Data in Healthcare: New Methods of Analysis
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    Chapter 6 Generating the Data for Analyzing the Effects of Interprofessional Teams for Improving Triple Aim Outcomes
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    Chapter 7 Wrestling with Big Data: How Nurse Leaders Can Engage
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    Chapter 8 Inclusion of Flowsheets from Electronic Health Records to Extend Data for Clinical and Translational Science Awards (CTSA) Research
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    Chapter 9 Working in the New Big Data World: Academic/Corporate Partnership Model
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    Chapter 10 Data Science: Transformation of Research and Scholarship
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    Chapter 11 Answering Research Questions with National Clinical Research Networks
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    Chapter 12 Enhancing Data Access and Utilization: Federal Big Data Initiative and Relevance to Health Disparities Research
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    Chapter 13 Big Data Impact on Transformation of Healthcare Systems
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    Chapter 14 State of the Science in Big Data Analytics
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    Chapter 15 Big Data Analytics Using the VA’s ‘VINCI’ Database to Look at Delirium
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    Chapter 16 Leveraging the Power of Interprofessional EHR Data to Prevent Delirium: The Kaiser Permanente Story
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    Chapter 17 Mobilizing the Nursing Workforce with Data and Analytics at the Point of Care
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    Chapter 18 The Power of Disparate Data Sources for Answering Thorny Questions in Healthcare: Four Case Studies
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    Chapter 19 What Big Data and Data Science Mean for Schools of Nursing and Academia
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    Chapter 20 Quality Outcomes and Credentialing: Implication for Informatics and Big Data Science
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    Chapter 21 Big Data Science and Doctoral Education in Nursing
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    Chapter 22 Global Society & Big Data: Here’s the Future We Can Get Ready For
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    Chapter 23 Big-Data Enabled Nursing: Future Possibilities
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Title
Big Data-Enabled Nursing
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-53300-1
ISBNs
978-3-31-953300-1, 978-3-31-953299-8
Editors

Connie White Delaney, Charlotte A. Weaver, Judith Warren, Tom Clancy, Roy Simpson

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 19 29%
Student > Master 8 12%
Student > Ph. D. Student 5 8%
Student > Doctoral Student 4 6%
Student > Bachelor 3 5%
Other 9 14%
Unknown 18 27%
Readers by discipline Count As %
Nursing and Health Professions 26 39%
Medicine and Dentistry 8 12%
Computer Science 4 6%
Social Sciences 2 3%
Agricultural and Biological Sciences 1 2%
Other 3 5%
Unknown 22 33%