Patient-Centered Digital Healthcare Technology: Novel Applications for Next Generation Healthcare Systems

Contents
Preface: Patient-Centered Digital Healthcare Technology: Novel Applications for Next Generation Healthcare Systems Featuring the Game Changers of Emerging Technologies in Medicine and Public Health
About the Editors
1. Information systems in health: what do you need and how will you get it?
	1.1 Introduction
	1.2 Healthcare as a sociotechnical pursuit
	1.3 A simple model of what information someone in healthcare needs
	1.4 A way of thinking about the role of information in care provision
	1.5 Knowledge and process in care delivery
	1.6 Conclusion and critical design questions
	Acknowledgments
	References
2. Hybrid usability methods: practical techniques for evaluating health information technology in an operational setting
	2.1 Introduction
	2.2 Commonly used methods
	2.3 Hybrid techniques
	2.4 Case studies
	2.5 Conclusions
	References
3. Advancing public health in the age of big data: methods, ethics, and recommendations
	3.1 Introduction
	3.2 Overview of big data analytics
	3.3 Enabling technologies
	3.4 Data sources and collection methods
	3.5 Advantages of big data in public health
	3.6 Ethical risks and issues
	3.7 Recommendations
	3.8 Conclusion
	References
4. Preferential hyperacuity perimetry: home monitoring to decrease vision loss due to age-related macular degeneration
	4.1 Introduction
	4.2 Background
	4.3 Diagnostic testing
	4.4 Age-related macular degeneration
	4.5 Treatment for exudative age-related macular degeneration
	4.6 The importance of early detection of exudative age-related macular degeneration to improve visual outcomes
	4.7 The unmet needs for better early detection of exudative AMD
	4.8 Preferential hyperacuity perimetry (PHP)
	4.9 ForeseeHomeTM
	4.10 Clinical trial results
	4.11 Impact, reimbursement and cost effectiveness of ForeseeHomeTM monitoring
	4.12 Additional applications for ForeseeHomeTM
	4.13 Conclusions and future of home monitoring in ophthalmology
	References
5. Enhancing the reach and effectiveness of behavioral health services for suicidal persons by incorporating mobile applications (apps) technology
	5.1 Technology landscape
	5.2 Technology and behavioral healthcare
	5.3 Evidence for behavioral health apps for suicide prevention
	5.4 Discussion
	5.5 Conflict of interest
	Acknowledgments
	References
6. The gamification of mental health prevention and promotion
	6.1 Introduction
	6.2 Making it playful
	6.3 Use of Wellness Center activities
	6.4 Platform
	6.5 Mitigating liabilities to protect the end user
	References
7. Minimally disruptive medicine: how mHealth strategies can reduce the work of diabetes care
	7.1 Introduction
	7.2 The diabetic lower extremity
	7.3 Our approach
	7.4 MIMOSA in practice and overcoming barriers to mHealth adoption
	7.5 Change is on the horizon
	7.6 Conclusions
	References
8. Innovations in medical robotics: surgery, logistics, disinfection, and telepresence
	8.1 The medical robotics landscape
	8.2 Surgery
	8.3 Logistics
	8.4 Disinfection robots
	8.5 Telepresence
	8.6 Conclusion
	References
9. New reality for surgical training and assessment using immersive technologies
	9.1 History of surgical training
	9.2 Emerging industry trends
	9.3 State of surgical education
	9.4 Emerging approaches in surgical simulation
	9.5 Immersive technology
	References
10. Applications of blockchain in healthcare
	10.1 Introduction to blockchain
	10.2 When is it appropriate to use blockchain?
	10.3 Introduction to blockchain solution models
	10.4 Healthcare provider data use cases
	10.5 Healthcare provider directories
	10.6 Healthcare provider credentialing
	10.7 Walmart supply chain: one non-healthcare example
	10.8 Pharmaceutical supply chain management
	10.9 Patient identity and consent management
	10.10 Electronic health record exchange
	10.11 Real-time claims adjudication
	10.12 Reducing of fraud, waste, and abuse in healthcare
	10.13 Conclusion
	References
	Further Reading
11. A practical introduction to artificial intelligence in medicine
	Prologue
	11.1 Why does medicine need AI and why are radiologists leading the forefront?
	11.2 Basics of artificial intelligence
	11.3 Problem identification
	11.4 Data collection
	11.5 Data labeling
	11.6 Validation
	11.7 Deployment and integration
	References
12. Under the hood: developing the engine that drives personalized medicine
	12.1 Introduction
	12.2 Sequencing
	12.3 Secondary analysis
	12.4 Tertiary analysis
	12.5 Technical implementation
	12.6 Challenges
	12.7 How this engine will redefine healthcare
	References
Afterword: The impacts of novel and emerging technologies on a pandemic
Index