Digital Health
Telemedicine and Beyond
- 1st Edition - October 21, 2024
- Editor: Dipu Patel
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 3 9 0 1 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 3 9 0 2 - 1
Digital Health: Telemedicine and Beyond describes practical ways to use digital health tools in clinical practice. With a strong focus on case studies and patient outcomes,… Read more
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Request a sales quoteDigital Health: Telemedicine and Beyond describes practical ways to use digital health tools in clinical practice. With a strong focus on case studies and patient outcomes, this title provides an overview of digital medicine, terms, concepts, and applications for the multidisciplinary clinical practitioner. Chapters provide a concise, yet comprehensive understanding of digital health, including telemedicine, mHealth, EHRs, and the benefits and challenges of each. The book gives insights on risks and benefits associated with storing and transmitting patient information via digital tools and educates clinicians in the correct questions to ask for advocacy regarding state laws, scope of practice, and medicolegal implications.
It also addresses the ethical and social challenges that digital health raises, how to engage patients to improve shared decision-making models and how digital health tools can be integrated into clinical practice. This book is a valuable resource for clinicians and medical educators of all health professions, including physicians, physician associates, nurses, pharmacists, physical therapists, occupational therapists, speech therapists, students, and all those who wish to broaden their knowledge in the allied field.
- Provides a clinical perspective on digital health
- Written by clinicians for clinicians with the patient in mind
- Describes practical ways to use digital health tools in clinical practice
- Includes case studies to incorporate workflows into practice to improve patient outcomes
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- Foreword
- A transformative era in medicine—The cognitive age
- John Nosta
- The historical canvas of medicine
- AI and the transformation of medical practice
- The legal and ethical implications of AI in medicine
- AI and the patient journey
- The future of diagnosis—The promise of disease stage zero
- The human element in the age of AI
- Customizing patient education with AI
- The role of AI in primary care
- The intersection of joy and purpose in medicine
- The promise and challenges of AI in healthcare
- Embracing the new era of medicine
- Preface
- Acknowledgments
- Reviewers
- Chapter 1. Digital health: Ancient wisdom, modern medicine
- Introduction
- Significance of digital health in modern healthcare
- Importance of digital health for both professionals and individuals
- Evolution of health and care: From traditional to digital
- Historical perspective on traditional healthcare delivery methods
- Emergence and impact of digital technologies in healthcare
- Key technologies driving digital health
- Major technologies shaping digital health
- Artificial intelligence (AI) and Machine Learning (ML) in healthcare
- Internet of things (IoT) and its applications in healthcare
- Big data and analytics in improving patient outcomes
- Telemedicine and remote patient monitoring (RPM)
- Wearable devices and mobile health (mHealth) applications
- Personalized medicine and precision healthcare
- Revolutionizing healthcare professionals and workforce
- Ethical, legal, and regulatory considerations in digital health
- Benefits, opportunities, and challenges in digital health
- Conclusion
- Chapter 2. Diagnosing the future: The role of artificial intelligence in the forthcoming medical epoch
- Introduction
- Inevitable hesitancy
- From AI-adjacent to AI-empowered
- Diagnosing the future
- Discussion questions
- Chapter 3. AI in medical education: Challenges and opportunities
- Design and implementation principles
- Adaptive systems thinking
- The importance of the ethical compass
- Evidence-based learning
- Human-centered design
- An integrative approach
- Change leadership
- Learning about AI
- Learning with AI
- Knowledge on demand
- AI powered simulations
- Adaptive learning and assessment
- Conclusion
- AI disclosure
- Chapter 4. Telemedicine: History, foundation, and clinical implementation
- History of telemedicine
- Introduction
- Early concepts and precursors (prior to 1960s)
- Emergence and development (1960–1980s)
- Recognition and integration (1990–2010s)
- Current landscape
- Future of telemedicine
- Telemedicine basics
- Types
- Synchronous versus asynchronous
- Audio only versus audio–video
- Technology and video platforms
- Video platforms
- Remote patient monitoring
- Backup plans
- Practice license considerations
- Key telemedicine practice and licensure considerations
- Settings
- Outpatient
- Rural and underserved areas
- Emergency department (ED)
- Operating room
- Global health and disaster response
- Mental healthcare
- Other
- Barriers
- Benefits
- Patients
- Providers
- Other stakeholders
- Conducting a telemedicine visit
- Previsit preparation
- Technological readiness
- Patient education and consent
- Safety planning
- Webside manner
- Visit structure
- Interview
- Examination
- Documentation
- Resources
- Assessments and questions
- Assessment 1
- Case study: Telemedicine in primary care
- Assessment 2
- Case study: Examination and documentation
- AI disclosure
- Chapter 5. Beyond the wrist: Wearables in healthcare
- Introduction
- Background
- Types of wearable devices
- Smartwatches
- Fitness trackers
- Smart glasses
- Smart clothing
- Health monitoring devices
- Remote patient monitoring devices
- Digital tattoos
- Benefits and applications
- Challenges and considerations
- Future trends and innovations
- Conclusion
- AI disclosure
- Chapter 6. mHealth - a pocket-sized revolution
- Introduction
- A brief overview of mHealth
- Historical development and importance of mHealth
- Early beginnings of mHealth (1990–2000s)
- Rapid growth and adoption (2005–present)
- Integration with telemedicine
- Global initiatives and collaborations
- Importance in modern healthcare
- Understanding mHealth
- Definition and explanation of mHealth
- The role of smartphones and wearable devices in mHealth
- Key components of mHealth
- Technological innovations in mHealth
- Recent advancements in mHealth technology
- The impact of artificial intelligence (AI) and machine learning (ML) on mHealth
- Future trends in mHealth technology
- Clinical applications of mHealth
- Chronic disease management
- Mental health services
- Emergency medicine
- Public health
- Design frameworks and software development kits in mHealth
- Design frameworks in mHealth
- Apple HealthKit and ResearchKit
- Android—Google Health Connect
- Open health stack and Android FHIR SDK
- Samsung
- Other mobile vendors
- Behavioral design thinking for mHealth
- Regulatory and ethical considerations in mHealth
- Data privacy and security issues in mHealth
- Regulatory frameworks for mHealth
- Ethical dilemmas and considerations in mHealth
- Challenges and limitations of mHealth
- Technological challenges
- Societal challenges
- Health system challenges
- The future of mHealth
- Emerging opportunities in mHealth
- EU projects—Label2Enable
- Future challenges and how to overcome them
- Envisioning mHealth's role in the future of healthcare
- Conclusion
- AI disclosure
- Chapter 7. Looking ahead: The future of electronic health records
- Introduction
- An overview of EHRs
- What are the benefits of EHRs?
- What are the challenges of EHRs?
- How EHRs have evolved
- The current state of EHRs
- The future of EHRs
- Emerging technologies influencing the future of EHRs
- Artificial intelligence and machine learning
- Internet of medical things (IoMT), wearable devices, and 5G/6G
- Cloud computing and big data analytics
- Blockchain technology
- The use of EHRs to improve population health
- The impact of EHRs on the healthcare workforce
- The role of policy and regulatory changes
- The way ahead
- The need for continuous research and development
- Future outlook
- AI disclosure
- Chapter 8. Bridging the gap: Empowering patients with health apps
- Introduction
- An overview of the health app market
- Market drivers
- Gaps in the market
- Current patterns of use
- Patients as consumers
- Opportunities for apps in healthcare
- Aggregated benefits
- Risks and barriers to using apps in healthcare
- Clinical risks
- Barriers among patents and clinicians
- Assuring apps in healthcare
- Data privacy
- Design and usability
- Clinical effectiveness
- Progress in medical AI
- Deploying health apps in practice
- Generalized and semitargeted approaches
- Targeted approaches
- Further reading and next steps
- Chapter 9. Remote patient monitoring
- Assessment (case examples, discussion questions, etc.)
- Future directions—assessment of patient preference and incorporation of feedback
- AI disclosure
- Chapter 10. From data to diagnosis: The power of precision medicine in digital health
- What is precision medicine?
- History of precision medicine
- Timeline of precision medicine (Figs. 10.2 and 10.3)
- Precision medicine in practice
- Implications of precision medicine to social determinants of health
- Benefits and challenges of precision medicine
- Future of precision medicine
- Education and clinical training
- Interdisciplinary approach
- Conclusion
- Assignment options
- Chapter 11. Hospital to home: Bridging the gap with personalized medicine
- Introduction
- Taylor's story
- Ethical considerations
- Cost implications
- Integration with existing healthcare systems
- Smart home
- Smart home hubs and voice assistants
- Smart pills
- Smart appliances and utensils
- Smart thermostats
- Smart lighting: Implications for health and well-being from a medical perspective
- Smart TVs and fall prevention: Integrating ambient intelligence for enhanced safety
- Smart toilets
- Smart mirrors: A medical perspective on reflective health monitoring
- Smart cars: A medical perspective on automotive health integration
- Smart rugs and floors: Ground-level health monitoring
- Smart locks
- Smart gardens
- Smart feeders and AI pets: Modern pet care
- Smart feeders
- AI pets
- Smart buildings: Advanced infrastructure and privacy considerations
- Privacy considerations
- Digital tattoos
- Research and development
- Implications on care
- Provider perspective
- Patient perspective
- Opportunities and barriers
- Future smart homes
- Chapter 12. Robot-assisted surgery: Past, present, and future
- Introduction
- A look back on the development of robot-assisted surgery
- Three main types of robotic surgical systems
- Active
- Semiactive
- Dependent (master–slave)
- Advantages of robot-assisted surgery
- Enhanced visualization
- Image
- Control
- Fluorescence capability
- Enhanced precision
- Improved ergonomics
- Limitations of robot-assisted surgery
- Haptic feedback
- Cost
- Training
- Intuitive Surgical—da Vinci systems
- Other robotic surgical systems
- Orthopedic surgery
- Neurosurgery
- Robot-assisted flexible bronchoscopy
- The future of robot-assisted surgery and the role artificial intelligence, machine learning, augmented reality, and virtual reality will play
- Haptic feedback
- Artificial intelligence
- Machine learning
- Augmented and virtual reality
- Legal and ethical considerations of robot-assisted surgery
- Patient safety
- Informed consent
- Accessibility and equity
- Liability and accountability
- Data security and privacy
- Conclusion
- Assessment
- Chapter 13. Digital therapeutics
- Understanding digital therapeutics
- Place in the digital health ecosystem
- Defining and differentiating digital therapeutics within the digital health space
- Categories
- Core principles
- Regulatory landscape
- Benefits, barriers, and challenges
- Benefits
- Barriers
- Challenges to adoption
- Trends and innovations
- Current and future trends
- Current trends
- Growth and proliferation
- Future prospects
- Expand your knowledge
- Medical education and instructor resources
- General websites
- Journals
- Regulatory information
- DTx products and companies
- Learner sample activities
- Chapter 14. Digital therapeutics: A new era of technology for treatment
- Introduction
- Definitions and keywords
- Background
- History and evolution of the industry
- Examples of DTx solutions
- Unique characteristics of DTx
- First approval and on
- International landscape
- Regulatory landscape
- Exempt devices
- Class II
- Class III
- Software as a medical device (SaMD) [11]
- Enforcement discretion
- Iterative development
- DTx that use machine learning/artificial intelligence (ML/AI)
- DTx intended to be used in combination with prescription drugs
- Special FDA programs impacting DTx
- Breakthrough devices program [19]
- Safer technologies program (SteP) [21]
- Precertification (Pre-cert) pilot program
- International considerations
- Localization requirements
- International regulations
- Germany
- South Korea [25]
- Clinical evidence generation
- Commercialization strategies
- Direct-to-consumer
- Employer partnerships
- Payer reimbursement
- Partnering with pharma
- Alternate strategies
- Other challenges for DTx companies
- Cybersecurity
- Reimbursement
- Adoption
- Sustainability/profitability
- Case study—Pear Therapeutics [38]
- Benefits of DTx
- Conclusion
- Chapter 15. The future of preventive primary care
- Introduction
- AI in the future clinic
- AI-powered reception area
- Healthcare in the metaverse
- Patient education and research with generative AI
- ChatGPT prompt: Write me a paragraph on how GPT will accelerate scientific research and cite sources
- The future state of primary care
- Elderly care
- Pediatric care
- LGTBQ+ care
- Chronic disease
- Artificial intelligence in diabetes and metabolic syndrome care
- AI navigating through diabetic retinopathy challenges
- Predictive models: Gazing into the future of diabetes and metabolic care
- Technological symbiosis in comprehensive diabetes management
- Elevating detection and mitigating complications with AI
- AI interfacing with insulin pumps and continuous glucose monitoring systems
- AI in diabetic foot care
- Multimodal generative AI (ChatGPT) in diabetes and metabolic care
- Cost-effectiveness: A balancing act in resource utilization
- Ethical and practical conundrums in AI deployment
- Gazing forward: Nurturing the future of AI in diabetes care
- Summary
- Conclusion
- Assessment options
- Chapter 16. Integrating digital medicine in rural communities
- Introduction
- Barriers and challenges to DMI adoption in rural communities
- Patient preferences and needs
- Usability and adherence
- Cost and infrastructure
- Preventative care and disease management in rural communities
- Behavioral health and substance use disorder conditions
- Primary care and women's health
- Toolkit and recommendations for success of DMI in rural communities
- Conclusion
- Questions and opportunities for additional research
- Chapter 17. CMS telehealth coding and guidelines
- Introduction
- Background of CMS and its structure: Medicare and Medicaid
- Background of Medicare
- Background of Medicaid
- Overview of the history of telehealth reimbursement within CMS
- CMS and telehealth services
- Medicaid and parity laws
- COVID and the rapid expansion of CMS telehealth codes
- CARES act and PHE
- Telehealth coding and billing
- Overview of current procedural terminology (CPT) codes for telehealth services
- Billing and reimbursement through Medicare and Medicaid
- Review of recent CMS policy changes impacting telehealth services and evaluation of temporary versus permanent telehealth policy changes since PHE
- Other CMS-based reimbursement policies
- Asynchronous telehealth
- RPM/RTM codes
- Future of CMS codes in telehealth
- Chapter 18. ICD-10 and SNOMED CT: The role of healthcare classification systems in digital health
- Introduction
- The historical context of ICD-10 and SNOMED CT
- ICD-10: A global standard
- SNOMED CT: Precision in clinical terminology
- Digital health's impact on ICD-10 and SNOMED CT
- Telemedicine
- Examples of common ICD-10 codes used in telemedicine
- Remote patient monitoring
- RPM ICD-10 and SNOMED CT coding examples
- Hospital services through telehealth/remote patient monitoring
- ICD-10 Coding for Telehealth in the Hospital [41]
- ICD-10 coding for E-consults
- Here's how ICD-10 coding applies to e-consults
- Challenges of ICD-10 and SNOMED CT codes in digital health
- The future of codes in digital health
- Conclusion
- AI disclosure
- Chapter 19. Digital health law
- Introduction and terminology
- Overview of legal framework
- State oversight
- Federal oversight
- Contractual terms and conditions
- Case law
- Front of mind legal issues in digital health
- Licensure considerations
- Consent
- Prescribing and supervision
- Modalities and practitioner–patient relationship establishment
- Corporate practice of medicine prohibition
- Privacy laws
- Artificial intelligence
- Chapter 20. Use and reuse of data: Access, ownership, value, and trust
- Introduction
- Complexities and boundaries of data
- The Data–Information–Knowledge–Wisdom pyramid
- Health data, health-related data, and other data
- Personal versus nonpersonal data
- Primary and secondary use of data
- Ownership of and access to health data
- Data ownership
- Data access and patient empowerment
- The value of data
- Monetization versus data as a public common good
- Aspects of trust
- Conclusion
- Chapter 21. Ethical issues for AI in medicine
- Introduction
- Transparency
- Fairness
- Safety and liability
- Conclusion
- Chapter 22. Health policy
- Introduction
- Recent history of digital health policy
- Digital health policy recent history overview
- Ethical considerations in health policy
- CMS policy in the digital age—National picture
- Digital health policy impacts—FQHC, RHC
- Digital health policy impacts: Private payers
- Digital health literacy considerations
- Steps for the future of digital health
- Self-directed further investigation
- Chapter 23. Regulatory considerations
- Introduction
- Digital Health Center of Excellence
- Mobile Medical Applications
- Regulatory concerns: Artificial Intelligence/Machine Learning devices
- Regulatory concerns: Cybersecurity
- Regulatory concerns: Usability
- Conclusion/key takeaways
- Chapter 24. Data validation and verification and IRB process
- Data validation, data verification, and clinical validation considerations
- Data validation
- Data verification
- Clinical validation considerations
- Risk assessment process
- Digital health scorecard
- Digital health checklist for researchers (DHC-R)
- Generated research abstracts with ChatGPT
- Big Data
- IRB process
- Ethical and regulatory review
- Determination of appropriate risk management strategies
- Chapter 25. Healthcare, trials, and digital impact
- Trial design
- Study versus trial
- Types of trials
- Clinical trial
- Phases in clinical trial
- Public health trials
- Sponsor, clinical research organizations, and participant
- Sponsors
- Clinical research organizations (CROs)
- Participants
- Bias
- Institutional review board (IRB) and protocol
- On-site, hybrid, and decentralized clinical trials (DCTs)
- Data privacy
- Digitization of trials
- Electronic records
- Electronic health record (EHR) versus electronic medical record (EMR)
- Electronic trial records
- Electronic source data (eSource)
- Clinical outcome assessment (COA) and electronic patient reported outcomes (ePRO)
- Electronic data capture (EDC)
- Wearables and IoT for data collection
- Cybersecurity
- Data lake
- Digital players
- Medable
- Medidata
- Thread
- Science 37
- Data are king! benefits of digital health tools in clinical trials or studies
- Evolution of digital health tools in clinical trials
- Technical consideration for using digital tools in clinical trials
- Benefit of digital health tools in clinical trials
- Challenges to data security
- The near future—AI/ML in clinical trials
- Use cases of AI/ML in the clinical trials
- Patient recruitment and eligibility screening
- Predictive analytics for trial outcomes
- Optimizing trial design
- Data quality and integrity assurance
- Drug safety monitoring
- Drug discovery and target identification
- Challenges and limitations of AI/ML implementation
- Data privacy and security concerns
- Interoperability and data integration
- Regulatory and compliance challenges
- Bias and fairness issues
- Chapter 26. The future of digital health
- Artificial Intelligence (AI) and Machine Learning (ML)
- Privacy, security, and regulatory issues
- Ethics and social impact
- Education and training
- Conclusion
- Chapter 27. Battling misinformation
- Objectives
- Definitions
- Battling misinformation
- Infodemic
- Misinformation
- Spreading misinformation
- Public trust
- Strategies
- Fact-checking
- Conclusion
- Chapter 28. Educating the next generation in digital medicine
- Introduction
- Understanding the key components of digital medicine
- Current challenges in educating healthcare providers in digital medicine
- Resistance to change and varied levels of digital literacy
- Resource constraints and technological advancements
- Interdisciplinary collaboration and ethical/regulatory complexities
- Balancing traditional and digital skills and patient-centered care
- Data security and privacy and assessment and evaluation
- Integrating digital medicine into healthcare education
- Challenges and ethical considerations faced in digital medicine education
- Competencies in digital medicine education
- Best practices
- Conclusion
- Chapter 29. Incorporating AI and ML into the classroom
- Introduction
- Ways to incorporate AI/ML into the classroom
- AI/ML in interactive teaching methods
- High-fidelity and virtual reality simulation
- Intelligent tutoring systems
- Chatbots and virtual assistants
- Benefits of incorporating AI/ML in the classroom
- Personalized learning
- Improved student engagement
- Increased efficiency and accuracy
- Navigating the ethical and practical labyrinth: Challenges and considerations for implementing AI/ML in the classroom
- Assessment
- AI disclosure
- Chapter 30. Incorporating digital health into the curriculum
- First steps in incorporating digital health education into the curriculum
- Examples of integration of digital health into the curriculum
- Digital problem-based learning in digital health education
- Use of real-world case studies
- Challenges and potential solutions for implementing digital health education into the curriculum
- Assessment
- Reflective Journal
- Chapter 31. Student perspectives of digital health: Learning through quality improvement
- Doctorate of physician assistant studies: Digital health initiatives
- Quality improvement capstone project
- Patient equity in digital health literacy
- Future initiatives in digital health documents
- Chapter 32. From classroom to clinic: A student's perspective
- Introduction
- Background
- Methods
- Results
- Study 1
- Study design
- Study results
- Study 2
- Study design
- Study results
- Study 3
- Study design
- Study results
- Discussion
- Conclusion
- Chapter 33. Interpreting the future: Navigating the tele revolution in healthcare language access
- Introduction
- Background
- Interpreter Services Department at Hennepin Healthcare System
- Transitioning from in-person to tele-interpreting: Challenges and opportunities
- The Pendulum Swing: Going too far with remote modality
- Methods
- Results
- Analysis: The case for an adaptable hybrid model
- Recommendations for flexible, patient-centered, community-based standards
- Conclusions
- Chapter 34. Organizational perspective
- Healthcare workforce implications
- Organizational benefits of digital health and AI leveraging digital health and AI for organizational advantages in healthcare: A strategic approach
- The healthcare leader's case for AI integration
- Implementing digital health
- Talent acquisition
- Time and resource allocation
- Financial considerations
- Training and education
- Workforce implications
- Conclusion
- Outcomes that matter
- Benefits of digital medicine/AI in the healthcare ecosystem
- Improved healthcare outcomes
- Increased efficiency
- Cost savings
- Patient satisfaction
- Conclusion
- Chapter 35. Patient perspectives on digital health
- Introduction—The patient perspective
- Why patient perspectives matter
- Essential reasons for including disability perspectives in digital health
- Digital health versus traditional in-person care
- The transformative potential of digital health
- Key benefits of digital health
- Bridging the gap: Digital versus traditional care
- Conclusion
- Does the shifting aging of society's demographics impact digital health?
- Benefits of embracing an aging population
- Digital health advantages for aging society
- Current aging statistics (2022)
- Projected aging statistics (by 2050)
- Benefits and obstacles of aging populations
- Can the inclusion of diverse patients' perspectives help society shift to digital health?
- Challenges
- Creating better global solutions
- How can learning from the patient's perspective be of paramount importance in the digital health journey?
- Need for digital solutions
- The power of accessible information
- Empowerment through knowledge: Accessing reliable health information
- Digital health and our health
- Digital tools for health monitoring
- Simplifying medication and appointments
- Centralizing personal health records
- Streamlining communication and collaboration in healthcare
- Navigating challenges and opportunities
- Privacy and security concerns
- Balancing trust and convenience digital health ensures privacy and trust through
- Overcoming technological barriers and digital literacy challenges
- Advocating for access and equity in digital health
- Ethical Responsibilities of healthcare providers and technology developers
- The importance of user experience and patient-centered design
- Societies expectations have changed
- Call to action: Amplifying patient voices in digital health
- Lessons from COVID-19 on digital health
- Call to action: Amplify patient voices
- A hopeful future through patient perspectives
- Final thoughts
- Index
- No. of pages: 553
- Language: English
- Edition: 1
- Published: October 21, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443239014
- eBook ISBN: 9780443239021
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