Big Data in ehealthcare: Challenges and Perspectives

This book explores the current state-of-the-art technology and research challenges in handling big data in healthcare.

\n Format: Hardback
\n Length: 236 pages
\n Publication date: 02 January 2019
\n Publisher: Taylor & Francis Inc
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This comprehensive book delves into the multifaceted realm of managing large volumes of healthcare data. It presents a comprehensive overview of the state-of-the-art technology employed for storing and organizing health records, as well as the diverse health data models used in the healthcare industry. Furthermore, it sheds light on the significant research challenges associated with acquiring, storing, managing, and analyzing big data in healthcare.

The book begins by providing an in-depth exploration of the origins and evolution of big data in healthcare. It discusses the increasing demand for efficient and effective data management solutions as healthcare organizations strive to improve patient care, reduce costs, and enhance research outcomes.

Chapter 1: Introduction to Big Data in Healthcare
This chapter provides a foundational understanding of big data and its significance in healthcare. It defines big data as a vast collection of structured and unstructured data generated by various sources, such as medical devices, electronic health records (EHRs), social media, and patient surveys. It highlights the potential benefits of leveraging big data in healthcare, including improved patient care, personalized medicine, and enhanced research capabilities.

Chapter 2: Current State-of-the-Art Technology for Storing Health Records
In this chapter, the book explores the various technologies used for storing health records. It discusses the advantages and disadvantages of traditional paper-based systems, as well as the emerging digital technologies such as cloud computing, blockchain, and artificial intelligence (AI). It also provides an overview of the different storage architectures, such as hierarchical, relational, and NoSQL databases, and their suitability for different types of healthcare data.

Chapter 3: Health Data Models and their Applications
This chapter delves into the development and application of health data models. It discusses the importance of standardized data models in facilitating data exchange and interoperability between different healthcare systems. It explores the various data models used in healthcare, such as the Health Level Seven International (HL7) standard, the International Classification of Diseases (ICD), and the Systematized Nomenclature of Medicine (SNOMED). It also highlights the challenges associated with model development, validation, and maintenance.

Chapter 4: Research Challenges in Big Data Acquisition, Storage, Management, and Analysis
In this chapter, the book addresses the research challenges associated with big data acquisition, storage, management, and analysis. It discusses the difficulties in capturing and extracting meaningful information from large datasets, the challenges in managing data security and privacy, and the challenges in analyzing data using advanced analytics techniques. It also provides an overview of the emerging research trends in big data healthcare, such as machine learning, natural language processing, and data visualization.

Chapter 5: Case Studies and Real-World Examples
This chapter presents case studies and real-world examples of big data applications in healthcare. It discusses the successful implementations of big data projects in healthcare organizations, such as hospitals, clinics, and research institutions. It highlights the benefits and challenges encountered during these implementations, and provides insights into the future directions of big data in healthcare.

Chapter 6: Conclusion and Future Outlook
In this chapter, the book summarizes the key findings and conclusions of the previous chapters. It discusses the potential impact of big data on healthcare in the coming years and the challenges that need to be addressed to fully realize its potential. It also provides recommendations for healthcare professionals, researchers, and policymakers on how to effectively leverage big data in healthcare.

Overall, this book provides a comprehensive and up-to-date overview of the various aspects of handling big data in healthcare. It is an invaluable resource for healthcare professionals, researchers, and policymakers interested in leveraging the power
This comprehensive book delves into the multifaceted realm of managing large volumes of healthcare data. It presents a comprehensive overview of the state-of-the-art technology employed for storing and organizing health records, as well as the diverse health data models used in the healthcare industry. Furthermore, it sheds light on the significant research challenges associated with acquiring, storing, managing, and analyzing big data in healthcare.

The book begins by providing an in-depth exploration of the origins. It discusses the increasing demand for efficient and effective data management solutions as healthcare organizations strive to improve patient care, reduce costs, and enhance research outcomes.

Chapter 1: Introduction to Big Data in Healthcare
This chapter provides a foundational understanding of big data and its significance in healthcare. It defines big data as a vast collection of structured and unstructured data generated by various sources, such as medical devices, electronic health records (EHRs), social media, and patient surveys. It highlights the potential benefits of leveraging big data in healthcare, including improved patient care, personalized medicine, and enhanced research capabilities.

Chapter 2: Current State-of-the-Art Technology for Storing Health Records
In this chapter, the book explores the various technologies used for storing health records. It discusses the advantages and disadvantages of traditional paper-based systems, as well as the emerging digital technologies such as cloud computing, blockchain, and artificial intelligence (AI). It also provides an overview of the different storage architectures, such as hierarchical, relational, and NoSQL databases, and their suitability for different types of healthcare data.

Chapter 3: Health Data Models and their Applications
This chapter delves into the development and application of health data models. It discusses the importance of standardized data models in facilitating data exchange and interoperability between different healthcare systems. It explores the various data models used in healthcare, such as the Health Level Seven International (HL7) standard, the International Classification of Diseases (ICD), and the Systematized Nomenclature of Medicine (SNOMED). It also highlights the challenges associated with model development, validation, and maintenance.

Chapter 4: Research Challenges in Big Data Acquisition, Storage, Management, and Analysis
In this chapter, the book addresses the research challenges associated with big data acquisition, storage, management, and analysis. It discusses the difficulties in capturing and extracting meaningful information from large datasets, the challenges in managing data security and privacy, and the challenges in analyzing data using advanced analytics techniques. It also provides an overview of the emerging research trends.

Chapter 5: Case Studies and Real-World Examples
This chapter presents case studies and real-world examples of big data applications in healthcare. It discusses the successful implementations of big data projects in healthcare organizations, such as hospitals, clinics, and research institutions. It highlights the benefits and challenges encountered during these implementations, and provides insights into the future directions of big data in healthcare.

Chapter 6: Conclusion and Future Outlook
In this chapter, the book summarizes the key findings and conclusions of the previous chapters. It discusses the potential impact of big data on healthcare in the coming years and the challenges that need to be addressed to fully realize its potential. It also provides recommendations for healthcare professionals, researchers, and policymakers on how to effectively leverage big data in healthcare.

Overall, this book provides a comprehensive and up-to-date overview of the various aspects of handling big data in healthcare. It is an invaluable resource for healthcare professionals, researchers, and policymakers interested in leveraging the power health data to drive innovation and improve patient outcomes.

\n Weight: 522g\n
Dimension: 162 x 240 x 22 (mm)\n
ISBN-13: 9780815394402\n \n