Healthcare Data Analytics and Management

Nilanjan Dey, Amira S. Ashour, Simon James Fong, Chintan Bhatt

• Publisher: Academic Press
• Year: 2018
• Print ISBN: 9780128153680
• eBook ISBN: 9780128156360
• Topic: Biological Sciences
• Subtopic: Biotechnology
• Index: Biological Sciences

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data.- Covers data analysis, management and security concepts and tools in the healthcare domain- Highlights electronic medical health records and patient information records- Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining- Includes multidisciplinary contributions in relation to healthcare applications and challenges

Chapter 1

Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare

Pijush Kanti Dutta Pramanik⁎; Bijoy Kumar Upadhyaya^†; Saurabh Pal^‡; Tanmoy Pal^{‡ ⁎} National Institute of Technology, Durgapur, India
^† Tripura Institute of Technology, Agartala, India
^‡ Bengal Institute of Technology, Kolkata, India

Abstract

Advances in smart medical devices and pervasive systems are turning connected healthcare into a prospering platform for pervasive healthcare. The Internet of Things (IoT), smart sensors, and wearables have augmented the healthcare system, enabling remote monitoring and supporting the medical condition of the patient in and out of clinics. This chapter aims to serve as a brief primer on the development of smart and pervasive healthcare systems. The chapter starts with an overview of IoT, smart sensors, and pervasive systems and also their interrelationships. The differences between IoT and pervasive systems are meticulously laid out to clear any confusion between these two computing paradigms. The chapter highlights the challenges faced by today's healthcare systems and analyzes how to overcome these with the help of pervasive healthcare. It discusses the basics of mobile and pervasive healthcare, including context-aware and connected healthcare, while distinguishing them from telemedicine. It elaborates on the role of IoT in healthcare while discussing a number of sensors and smart devices used in healthcare, fitness, and medical care units. The benefits of and challenges involved in pervasive healthcare are reviewed comprehensively. Several real-life applications and use cases of IoT and smart sensors are presented, showing the effectiveness of pervasive healthcare. The chapter also presents an assessment of the current and future IoT healthcare market along with a listing of the key players.

Keywords

Pervasive computing; Remote healthcare; Smart healthcare; Mobile healthcare; Smart sensor; Health sensor; Biosensor; Medical Robotics; e-Health; Telehealth; Telemedicine; Wearable; Implantable; Healthcare market

Chapter Outline

• 1 Introduction
• 2 IoT, Smart Sensors, and Pervasive Computing
  • 2.1 IoT
  • 2.2 Smart Sensors Augmenting the IoT
  • 2.3 Pervasive Systems
  • 2.4 Difference Between Pervasive Systems and IoT
  • 2.5 IoT and Pervasive Systems: Complementing Each Other
• 3 Challenges in Traditional Healthcare Systems
• 4 Mobile and Pervasive Healthcare
  • 4.1 Context-Awareness in Healthcare
  • 4.2 Connected Healthcare
  • 4.3 Pervasive Healthcare Vs Telemedicine
• 5 Role of IoT in Healthcare
  • 5.1 Clinical Care
  • 5.2 Remote Monitoring
  • 5.3 IoT and Medical Robotics
• 6 Different Healthcare Sensors
  • 6.1 Basic Health Sensors
  • 6.2 Other Sensors Used in Medical Care Units
  • 6.3 Different Fitness Devices
• 7 Benefits of Connected Healthcare
• 8 Challenges in Connected Healthcare
• 9 Healthcare Applications of Smart Sensors and IoT
  • 9.1 Smart Needle
  • 9.2 iTBra
  • 9.3 Coronary Artery Disease and IoT
  • 9.4 Personalized Medical Care
  • 9.5 Patient Monitoring
  • 9.6 Cardiac Rhythm Monitoring
  • 9.7 Cardiac Rehabilitation
  • 9.8 Handling COPD Problems
  • 9.9 Smart Contact Lens for Diabetics
• 10 Use Cases
  • 10.1 Mississippi Blood Service: Maintaining Logistics Smartly
  • 10.2 Finding Treatment for COPD
  • 10.3 Lahey Clinic Medical Center: Tracking Healthcare Equipment in Real-Time
  • 10.4 Irin General Hospital: Improving Healthcare Quality
  • 10.5 Jefferson University Hospital: Providing Cognitive Environment of Care
• 11 The IoT Healthcare Market: Present and Future
• 12 Conclusion
• Acknowledgments
• References

Acknowledgments

We would like to thank Matt Benardis, CEO, Cyrcadia Health and Marie Johnson, Ph.D., CEO, AUM Cardiovascular Inc. for giving permission to use the images of iTBra and CADence respectively.

1 Introduction

Digitization of healthcare data over the past decade has brought revolutionary transformations to the healthcare industry. It has facilitated healthcare data to be more open and easily accessible. Not only have the private players bitten into a share of this apple, but also the government and the public stakeholders of the healthcare industry have progressed towards transparency by making the healthcare data generated and collected from different sources and stored at isolated data islands more usable, searchable, and actionable to all those concerned. Smartphones and tablets, convenient medical apps, wearable devices, and the development of a variety of wireless monitoring services have made healthcare services omnipresent. Medical devices are increasingly being connected to each other [1]. In fact, the trend in the adoption of connected medical devices is set to grow drastically in the coming years. And this rising number of connected medical devices, along with supported software and services, is turning connected healthcare into a proliferating platform for pervasive healthcare.

The objective of an ideal healthcare system should be not only to provide effective healthcare services but also to support patients with quality of life by ensuring optimal functioning of overall health monitoring. This goal has led to the concept of a pervasive healthcare system that is able to monitor health status, provide medical facilities, and ensure sound health regardless of the location of the beneficiary. The traditional healthcare systems are highly concentrated in hospitals and clinics [2], but most people prefer to receive health services at their own residences as much as possible. Even if they are required to use institutional medical facilities, they wish to minimize the time spent there. Typically, the direct clinical healthcare received by humans, on average, is negligible in comparison to the overall healthcare needed during a lifetime. Smart sensors [3], Internet of Things (IoT) [4, 5], and wearables [6, 7] have augmented the healthcare system, enabling remote monitoring and supporting the medical condition of patients in and out of clinics [8]. For instance, the blood glucose monitor may send a reminder to a diabetic patient to take insulin. If the patient is a pediatric diabetic, the system might suggest that parents recheck the diet plan if the sugar level continuously approaches higher levels. Similarly, a wearable sensor allows an orthopedic physician to monitor a patient as to whether the patient is doing prescribed exercises properly and regularly. Smart sensors and the IoT will allow clinicians to have passable and unified access to the details of their patients, including food habits and lifestyles. This means that collecting only the clinical data is insufficient. To get the real picture of the health status of an individual or the mass public, peoples’ health data need to be collected and analyzed on a regular basis, even if they are not a clinical patient [9]. Using current technology, patients can continuously be monitored even they are not under clinical care. The pervasive health applications have significantly increased health data liquidity, which ...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Foreword
• Preface
• Chapter 1: Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare
• Chapter 2: Migration of healthcare relational database to NoSQL cloud database for healthcare analytics and management
• Chapter 3: Developing a decision support system for big data analysis and cost allocation in national healthcare
• Chapter 4: Securing large datasets involving fast-performing key bunch matrix block cipher
• Chapter 5: Comparative analysis of semantic frameworks in healthcare
• Chapter 6: Smart ambulance system using concept of big data and internet of things
• Chapter 7: Mathematical methods of ECG data analysis
• Chapter 8: Smart information technology for universal healthcare
• Chapter 9: Handling uncertainty in IoT design: An approach of statistical machine learning with distributed second-order optimization
• Chapter 10: A reversible and secure electronic patient record embedding technique using histogram bin shifting and RC6 encryption
• Chapter 11: Secure and reversible data hiding scheme for healthcare system using magic rectangle and a new interpolation technique
• Index