AI for Leaders and Managers in Healthcare

No prerequisite

The objectives of this course are to enable you:

• Explore the current state of AI technologies and their relevance to contemporary healthcare challenges.
• Recognize the strategic advantages of adopting AI-driven solutions in various healthcare domains.
• Evaluate potential efficiency gains, cost reductions, and revenue growth opportunities through AI implementation in healthcare.
• Analyze case studies showcasing successful AI applications in optimizing clinical decision-making, patient engagement, and population health management.
• Assess the ethical, legal, and regulatory implications of AI deployment within healthcare organizations.
• Anticipate and mitigate potential risks associated with data privacy, algorithmic biases, and AI-driven decision-making in healthcare.
• Examine how AI technologies disrupt traditional healthcare models and create new opportunities for innovation.
• Develop strategies to leverage AI for improving patient outcomes, operational efficiency, and sustainable growth within your healthcare organization.
• Identify emerging trends and opportunities for integrating AI into various facets of healthcare operations, including clinical care, patient engagement, and population health management.
• Foster a culture of innovation and continuous learning to capitalize on the transformative potential of AI-driven solutions in healthcare.

Week 1: Introduction to AI in Healthcare

• Overview of the course objectives and structure
• Understanding the importance of AI for healthcare leaders and managers
• Exploring the current state of AI technologies and their impact on the healthcare industry

Week 2: Strategic Advantages of AI Adoption in Healthcare

• Recognizing strategic advantages and opportunities of adopting AI-driven solutions in healthcare
• Case studies illustrating successful AI implementations in different healthcare domains

Week 3: Economic Impact of AI in Healthcare

• Evaluating potential efficiency gains, cost reductions, and revenue growth opportunities through AI implementation in healthcare
• Cost-benefit analysis of AI adoption in healthcare operations
• Examining economic models and forecasts related to AI-driven innovation in healthcare

Week 4: AI Applications in Clinical Decision-Making

• Analyzing case studies showcasing successful AI applications in optimizing clinical decision-making
• Understanding AI-driven clinical decision support systems and their impact on patient outcomes
• Practical exercises on identifying and prioritizing clinical processes for AI integration

Week 5: AI and Patient Engagement

• Examining AI applications in enhancing patient engagement and experience
• Case studies of AI-driven personalized care plans and remote monitoring systems

Week 6: Ethical and Regulatory Implications of AI in Healthcare

• Assessing the ethical, legal, and regulatory implications of AI deployment in healthcare
• Addressing concerns related to data privacy, algorithmic biases, and transparency in healthcare AI

Week 7: MID-TERM EXAM

Week 8: Risk Management in AI Deployment in Healthcare

• Anticipating and mitigating potential risks associated with AI deployment in healthcare
• Strategies for managing risks related to data security, compliance, and regulatory issues in healthcare

Week 9: Disruption and Innovation in Healthcare Models

• Understanding how AI technologies disrupt traditional healthcare models
• Case studies of healthcare organizations undergoing transformation due to AI innovations
• Strategic implications of AI-driven disruption and innovation in healthcare

Week 10: Leveraging AI for Population Health Management

• Developing strategies to leverage AI for improving population health outcomes
• Identifying opportunities for AI integration across different healthcare domains
• Creating a roadmap for AI adoption and implementation in your healthcare organization

Week 11: Emerging Trends in AI for Healthcare

• Identifying emerging trends and opportunities for integrating AI into healthcare operations
• Exploring AI applications in clinical care, patient engagement, and population health management
• Creating a roadmap for AI-driven healthcare solutions in your organization

Week 12: Cultivating an AI-Ready Culture in Healthcare

• Fostering a culture of innovation and continuous learning to capitalize on AI opportunities in healthcare
• Developing leadership strategies for driving AI adoption and transformation in healthcare organizations
• Final reflections and action planning for implementing AI strategies in participants' healthcare organizations

Week 13: FINAL EXAM

• At the completion of the course the student will be able to:
• Demonstrate a comprehensive understanding of AI technologies and their applications in healthcare.
• Develop strategic insights for leveraging AI to improve patient outcomes and operational efficiency in healthcare organizations.
• Evaluate the ethical, legal, and regulatory implications of AI deployment in healthcare.
• Mitigate risks associated with AI implementation in healthcare settings.
• Develop actionable strategies for AI adoption and transformation in healthcare organizations.

The online delivery blends synchronous and asynchronous components. Students complete self-directed assignments hosted on the course platform. Weekly Forums support a required active, rubric-based student contributions that foster collaboration.

Exams may include essays, short answers, or MCQs. Formats include open/closed book. Time zones are considered. Assessments are formative and summative. Students have 2 weeks to review grades and must follow the appeal process in the Student Handbook

Certificate

Please note that there are three semesters as intake periods as noted on the academic calendar.
Scholarship Awarded (Total Fee: €100)

Registration is done online.