Big Data, Big Challenges: A Healthcare Perspective

Name: Big Data, Big Challenges: A Healthcare Perspective | Background, Issues, Solutions and Research Directions
Brand: Springer
Price: 160.49 EUR
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Background, Issues, Solutions and Research Directions

Mowafa Househ Andre W. Kushniruk Elizabeth M. Borycki(Herausgeber*in)

Springer (Verlag)

1. Auflage

Erschienen am 26. Februar 2019

VIII, 144 Seiten

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978-3-030-06109-8 (ISBN)

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Beschreibung

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Inhalt

Intro
Preface
Contents
Health Professional Perspective
1 Big Data Challenges from a Nursing Perspective
1 Introduction
2 Data Governance and Data Science Infrastructure and Pipeline
3 Case Examples
3.1 Electronic Health Records and Symptom Science
3.2 Omics
3.3 Twitter and Dementia Caregiving
3.4 Prediction and Sepsis Campaign Guideline
3.5 Intelligent Sensors and Aging in Place
3.6 Dashboards and Nurse Numeracy and Graph Literacy
4 Cross-Cutting Issues
4.1 Ethical Conduct of Research
4.2 Data Science Competencies
5 Conclusion
Acknowledgements
References
2 Big Data Challenges for Clinical and Precision Medicine
1 Introduction
1.1 Other Related Areas in Health Innovation Are Equally Hyped
1.2 Basic Resources Needed to Deliver Big Data
1.3 Trust, Privacy and Governance Issues
2 Defining Clinical Big Data
3 Long-Term Technical Concerns
4 Trust/Privacy/Governance
5 Is It Worth the Effort?
6 The Future
References
3 Big Data Challenges from a Pharmacy Perspective
1 The Promises of Big Data from a Pharmacy Perspective
2 Medication-Related Data are Complicated
3 Prescription-Related Data are Even More Complicated
4 Databases of Medications Prescribed
5 Databases of Medication Dispensed and Administered
6 Making Sense of the Ocean of Data
7 The Disruptive Potential-Patient-Related Data
8 In Conclusion
References
4 Big Data Challenges from a Public Health Informatics Perspective
1 Big Data: A Macro Trend Impacting Public Health in the Era of Automated Data Exchanges
2 Empowering Detection of Signal or Noise? The Example of Syndromic Surveillance
3 Technological Change Occurs Quickly . Too Much, Too Quickly?
4 Reality Isn't Always as Attractive as the Model
5 What Does What You Might See Mean?
6 Big Data Resources for Health Service Applications
7 Conclusion
References
5 Big Data Challenges from a Healthcare Administration Perspective
1 Introduction
2 Objectives of This Chapter
3 What Are Administration and Leadership in Health Care Systems?
3.1 Definitions
4 What Opportunities and Challenges Do Big Data Promise Administration in Health Care?
5 Population Focus
5.1 Opportunities-The Promise of Mobilizing Social Determinants of Health
5.2 Challenges-The Perils of Breaking Out of the Path Dependency
6 Accessibility
6.1 Opportunities-The Right Service at the Right Time at the Right Place
6.2 Challenges-Liberate the Data
7 Safety
7.1 Opportunities
7.2 Challenges-Communicate and Share Complete and Unbiased Information with Me
8 Worklife
8.1 Opportunities-Life-Long Learning Is Here to Stay and Treat Me with Dignity and Respect
8.2 Challenges-Ensure the Big Data Is Fit for Purpose
9 Client-Centered Services
9.1 Opportunities-As a Patient I Am Your Partner in My Care
9.2 Challenges-Establish Common Interoperable Ontologies and Standards for My Care and Health Status
10 Continuity
10.1 Opportunities-Please Don't Make Me Repeat My History, Again!
10.2 Challenges-Identify Me but Protect Me
11 Appropriateness
11.1 Opportunities-Provide Me the Best Care Current Knowledge and Skills Can Provide
11.2 Challenges-OK Google, Should I Have My Prosthetic Hip Resurfaced or Replaced?
12 Efficiency-Minimize Inputs, Maximize Outputs, Outcomes and Value
12.1 Opportunities-You Can Only Spend a Dollar Once
12.2 Challenges-Be Prepared to Speak Truth to Power
13 Concluding Remarks
References
6 Big Data Challenges from a Healthcare Governance Perspective
1 Introduction
2 Objectives of This Chapter
3 What Are the Role and Responsibilities of Governance Bodies in Health Care Systems?
3.1 Definitions
4 What Opportunities and Challenges Do Big Data Promise Governance in Health Care?
5 Population Focus
5.1 Opportunities-The Promise of Mobilizing Social Determinants of Health
5.2 Challenges-The Perils of Breaking Out of the Path Dependency
6 Accessibility
6.1 Opportunities-Provide Me with Timely and Necessary Services When I Need Them
6.2 Challenges-Give Me My Data
7 Safety
7.1 Opportunities-First Do no Harm
7.2 Challenges-Communicate and Share Complete and Unbiased Information with Me
8 Worklife
8.1 Opportunities-Life-Long Learning Is Here to Stay and Treat Me with Dignity and Respect
8.2 Challenges-Ensure the Big Data Is Fit for Purpose
9 Client-Centered Services
9.1 Opportunities-As a Patient I Am Your Partner in My Care
9.2 Challenges-Establish Common Interoperable Ontologies and Standards for My Care and Health Status
10 Continuity
10.1 Opportunities-Please Don't Make Me Repeat My History, Again!
10.2 Challenges-Identify Me but Protect Me
11 Appropriateness
11.1 Opportunities-Provide Me the Best Care Current Knowledge and Skills Can Provide
11.2 Challenges-"Hey Google", Should I Have My Prosthetic Hip Resurfaced or Replaced?
12 Efficiency-Minimize Inputs, Maximize Outputs, Outcomes and Value
12.1 Opportunities-You Can Only Spend a Dollar Once
12.2 Challenges-Be Prepared to Speak Truth to Power
13 Concluding Remarks
References
Human Factors and Ethical Perspectives
7 Big Data and Patient Safety
1 Introduction
2 Motivation
3 Existing Sources of Data
4 Challenges
5 Discussion and Conclusion
References
8 Big Data Challenges from a Human Factors Perspective
1 Introduction
2 Cognitive and Informational Aspects of Big Data and Application of the User-Task-Context Matrix
3 Case Study: The Promises and Challenges in Generating Useful and Usable Genomic Results to Support Human Decision Making
4 Challenges for Big Data from a Human Factors Point of View
5 Future Directions for Work in the Human Factors of Big Data
6 Conclusion
References
9 Big Data Privacy and Ethical Challenges
1 Introduction
2 Privacy and Big Data Management
3 Ethical Approaches to Big Data
4 Emerging Digital Ethics
5 Challenges for Healthcare Providers
6 Conclusion
References
Technological Perspectives
10 Health Lifestyle Data-Driven Applications Using Pervasive Computing
1 Introduction
2 Types of Lifestyle Applications Based on Pervasive Health Data
2.1 Data-Driven Population-Scale Using Pervasive Health Data
2.2 Data-Driven Pervasive Health for Behavioral Change
2.3 Visualization of Pervasive Health Data
2.4 Diabetes Management
3 Discussion on Barriers to Data-Driven Health Lifestyle Applications
4 Conclusions
References
11 Big Data Challenges from an Integrative Exposome/Expotype Perspective
1 Introduction
2 New Methods and Data Sources to Collect Individual Exposomes
3 Annotating Data and Representing Knowledge
4 Creating Individual Exposome Profiles from Electronic Health Records
5 Analyzing and Visualizing Data
6 Addressing Ethical, Legal and Social Issues
7 Using Exposome Data in Biomedical Research, Precision Medicine and Clinical Care
8 Educating Biomedical Informaticians in These Matters
9 Being Aware of Relevant Initiatives in This Area
10 Conclusion
References
Glossary

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