Overview
This course provides a comprehensive understanding of how digital technologies are transforming healthcare delivery, clinical practice, and health systems. It introduces key concepts, tools, and applications of digital health, while also addressing emerging technologies, data security, and future trends. Through a combination of conceptual learning, real-world case studies, and interactive activities, students will develop the ability to understand, evaluate, and apply digital health solutions in clinical and public health settings.
Curriculum
Curriculum
- 12 Sections
- 138 Lessons
- 12 Hours
Expand all sectionsCollapse all sections
- Instructions1
- Pre-Test
- Instructions:
- 1. This assessment contains 20 Multiple Choice Questions.
- 2. Each question carries 1 mark. Total marks: 20.
- 3. Select the ONE best answer for each question.
1 - Module 1: Introduction to Digital Health16
- 3.1Module Outline
- 3.21. What is Digital Health?
- 3.31.1. Definition of Digital Health
- 3.41.2. Why is Digital Health Needed?
- 3.51.3. Key Digital Health Tools
- 3.61.4. Impact of Technology in Healthcare
- 3.72. History and Evolution of Digital Health
- 3.82.1. Evolution of Digital Health
- 3.92.2. Traditional Healthcare to Digital Solutions
- 3.102.3. Sustainable Healthcare Model
- 3.113. Benefits of Digital Health and Roles of Healthcare Professionals
- 3.123.1. Benefits of Digital Health to Patients
- 3.133.2. Benefits of Digital Health to Healthcare Providers
- 3.143.3. Role of a Healthcare Practitioner in Digital Healthcare Adoption
- 3.154. Digital Health Lab 1: Remote Monitoring in Post-Discharge Care
- 3.165. Conclusion and References
- Module 2: Digital Health Tools and Technologies23
- 4.1Module Outline
- 4.21. Digital Health Tools
- 4.31.1. Broad Categorisation of Digital Health Tools
- 4.42. Hospital Management Information System (HMIS)
- 4.52.1. HMIS Workflow
- 4.63. Electronic Medical Record (EMR)
- 4.73.1. EMR Workflow
- 4.83.2. EHR vs EMR
- 4.93.3. EMR: Case Scenario
- 4.104. Telemedicine
- 4.114.1. Types of Telemedicine and Interactions
- 4.125. mHealth
- 4.135.1. Personalised Health App
- 4.145.2. Decision Support and Screening Tools
- 4.155.3. Chatbots
- 4.166. Remote Patient Monitoring
- 4.176.1. Key Features of RPM
- 4.186.2. Patient Portal and Clinician Dashboard
- 4.196.3. Point of Care Technologies
- 4.207. Clinical Decision Support System (CDSS)
- 4.217.1. Clinical Decision Support System (CDSS) Integrated into Clinical Workflow
- 4.227.2. Automation Bias
- 4.23Conclusion
- Module 3: Digital Health Architecture, Data Management and Operational Resilience16
- 5.1Module Outline
- 5.21. Architecture of Digital Health System
- 5.31.1. Technical Layer
- 5.41.2. Infrastructure Layer
- 5.52. Management of Health Data
- 5.62.1. Centralised Vs Federated System
- 5.72.2. Interoperability
- 5.82.3. Communication Standards in Healthcare
- 5.93. Data Quality Assurance in Digital Health
- 5.103.1. Data Quality Assurance: Checklist
- 5.113.2. Reducing Alert Fatigue through Good Quality Data Entry
- 5.124. Operational Resilience: Downtime, Local Caching and Power Fallback Protocols
- 5.134.1. Why Downtime Contingency Plan is Needed?
- 5.144.2. Local Caching
- 5.154.3. Power Fallback Protocols
- 5.16Conclusion
- Module 4: Global and Indian Digital Health Landscape19
- 6.1Module Outline
- 6.21. Global Landscape of Digital Health
- 6.31.1. Reasons for Global Adoption of Digital Health
- 6.41.2. Key Adopted Areas in Digital Health
- 6.51.3. International Bodies and Policies
- 6.61.4. Trends in Global Digital Healthcare: Next Big Thing!
- 6.71.5. Case Study: Takeaways from Market
- 6.82. Digital Health Landscape in India
- 6.92.1. India’s Digital Health Strategy
- 6.102.2. Ayushman Bharat Digital Mission (ABDM)
- 6.112.3. Health System Based Digital Health Initiative
- 6.122.4. Telemedicine
- 6.132.5. Decision Support System
- 6.142.6. Initiatives under National Health Programs
- 6.153. Digital Health Impact on Public Healthcare
- 6.163.1. Strengthening Primary Care in India through Digital Health
- 6.173.2. Improved Disease Surveillance in Public Health
- 6.183.3. Improved Efficiency and Cost Reduction in Healthcare Delivery
- 6.19Conclusion
- Module 5: AI In Healthcare - Part I14
- 7.1Module Outline
- 7.21. Health Data Analytics
- 7.31.1. Healthcare Data
- 7.41.2. How Much Data Do Digital Health Tools Generate?
- 7.51.3. Introduction to Health Analytics
- 7.61.4. A Stepwise Approach to Health Data Analytics
- 7.71.5. Data Mining
- 7.82. Artificial Intelligence and Machine Learning
- 7.92.1. What are AI and ML?
- 7.102.2. Data Labelling
- 7.112.3. Supervised Learning
- 7.122.4. Unsupervised Learning
- 7.132.5. AI Models Used in Healthcare
- 7.14Conclusion
- Module 6: AI in Healthcare - Part II11
- 8.1Module Outline
- 8.21. Advanced AI Techniques
- 8.31.2. Generative AI
- 8.42. AI Performance Metrics
- 8.53. Applications in Clinical Practice
- 8.63.1. Diagnosis/Screening Support
- 8.73.2. Risk Prediction
- 8.83.3. Treatment Selection and Personalisation
- 8.93.4. Population Health Management
- 8.103.5. Practical Guidance for Physicians
- 8.114. Conclusion
- Module 7: Health Data Security, Privacy and Ethics19
- 9.1Module Outline
- 9.21. The Need for Data Privacy and Security in Healthcare
- 9.31.1. Why It Matters for Patients
- 9.41.2. Why It Matters for the Healthcare Industry
- 9.51.3. Foundational Concepts
- 9.61.4. Journey of Data Protection, Frameworks, and Indian Challenges
- 9.72. Principles and Security Mechanisms
- 9.82.2. Technical Security Mechanisms
- 9.92.3. Vulnerabilities and Breaches
- 9.103. Practical Recommendations and Guidelines for Physicians
- 9.113.1. Correct Practice
- 9.123.2. Incident Escalation and Breach Response
- 9.133.3. Telemedicine Practice Guidelines
- 9.143.4. Electronic Health Record Standards in India
- 9.154. Ethical Implementation of AI
- 9.164.1. AI‑Associated Ethical Challenges
- 9.174.2. Safe Use of AI and Decision Support Systems
- 9.184.3. Daily Practice Checklist for Clinicians
- 9.19Conclusion
- Module 8: Future Trends in Digital Health18
- 10.1Module Outline
- 10.21. Intelligent & Autonomous Systems
- 10.31.1. Generative AI in Healthcare
- 10.41.2. Healthcare Agentic AI
- 10.51.3. Digital Therapeutics (DTx) – Software as a Medical Intervention
- 10.61.4. Remote & Autonomous Robotic Surgery
- 10.71.5. Quantum Computing in Medicine
- 10.82. Personalised & Predictive Care Models
- 10.92.1. Precision Medicine
- 10.102.2. Multi-Omics Analytics
- 10.112.3. Digital Twins – Virtual Replicas of Patients and Systems
- 10.122.4. Vocal Biomarkers – The Voice as a Vital Sign
- 10.132.5. Mental Health Care Using Digital Technology
- 10.143. Immersive, Virtual & Sustainable Care Delivery
- 10.153.1. Virtual Wards – Hospital at Home
- 10.163.2. Immersive Technologies – AR, VR, and the Healthcare Metaverse
- 10.173.3. Sustainability in Digital Health
- 10.18Conclusion
- Feedback Questionnaire1
- Post Test
- Instructions:
- 1. This assessment contains 20 Multiple Choice Questions.
- 2. Each question carries 1 mark. Total marks: 20.
- 3. Minimum qualifying score: 50% (10 out of 20).
- 4. Select the ONE best answer for each question.
1
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Course Features
- Lectures 138
- Quizzes 2
- Duration 12 hours
- Skill level Intermediate
- Language English
- Students 28
- Certificate Yes
- Assessments Yes