Big Data in Otolaryngology

1st Edition - July 17, 2024
Editor: Jennifer A. Villwock
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 0 5 2 0 - 3
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 0 5 2 1 - 0

Big data plays an increasingly important role in today’s practice of otolaryngology and in all of healthcare. In Big Data in Otolaryngology, Dr. Jennifer Villwock leads a team of… Read more

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Big data plays an increasingly important role in today’s practice of otolaryngology and in all of healthcare. In Big Data in Otolaryngology, Dr. Jennifer Villwock leads a team of expert authors who provide a comprehensive view of many key impacts of big data in otolaryngology—including understanding what big data is and what we can and cannot learn from it; best practices regarding analysis; translating findings to clinical care and associated cautions; ethical issues; and future directions.

Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1. Big data—Science fiction or clinically relevant?
Introduction
Limitations of big data
Opportunities in big data
Looking ahead
Chapter 2. Large administrative datasets: Lessons and limitations
Introduction
Overview of large databases
Strengths of large databases
Limitations of large databases
National cancer database
Surveillance, epidemiology, and end results program
SEER-medicare
National ambulatory medical care survey/National hospital ambulatory medical care survey
Pediatric health information system
Reg-ent clinical data registry
Conclusion
Chapter 3. Sources of high-dimensional data—The electronic health record, health systems, and insurance and payor data
Insurance and payment databases
Electronic health records
Surveys
National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey: General ambulatory databases
Registry data
Reg-ent: An otolaryngology-specific registry
Primary uses: Advancing research, improving patient outcomes, and quality improvement
Logistics and data access
General methods for classifying patients and cases
Summary overview
Chapter 4. Best practices when interpreting big data studies: Considerations and red flags
Introduction
Rapid expansion in big data research and areas where big data is most useful
Common pitfalls in big data studies
Steps to incorporating big data research into your clinical practice
Conclusion
Chapter 5. Current big data approaches to clinical questions in otolaryngology
Introduction
Chapter 6. Bias in big data: Historically underrepresented groups and implications
Ethical principles and big data
Biases and missing data concerns in big data studies
Addressing the problem
Chapter 7. Artificial intelligence in otolaryngology
Introduction
Fundamentals of artificial intelligence
Interpreting artificial intelligence models
AI in medicine: General applications and commonly used terms
Applications of AI in otolaryngology
Regulatory and ethical considerations
Challenges and future directions
Conclusion
Chapter 8. The patient perspective on big data and its use in clinical care
Privacy
Demographics and bias within big data
Trust
Patient vulnerability
Liability and accountability
Data ownership/epistemic inequities
Shift in paradigm: Community engagement
Index

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health

Big Data in Otolaryngology

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Jennifer A. Villwock