The first day establishes the foundation for understanding healthcare burnout and how AI can address its primary drivers. Through evidence-based assessments and interactive discussions, participants analyze the current state of administrative burden in healthcare and identify high-impact opportunities for AI integration. They learn to evaluate AI tools through a healthcare-specific lens, considering regulatory compliance, data privacy, and workflow integration. These skills immediately translate to strategic technology adoption that addresses the most significant sources of professional dissatisfaction.

Unit 1: Understanding Healthcare Burnout – 1 hr

• Description: Examine the current state of healthcare burnout and its primary drivers:
  • Documentation burden and electronic health record challenges
  • Administrative demands and regulatory requirements
  • Time pressures and diminished patient interaction
  • Current impact statistics and trends
• Learning Outcome: Participants will identify personal burnout risk factors and understand the systemic challenges contributing to healthcare professional stress.

Unit 2: AI in Healthcare: Opportunities & Limitations – 1 hr

• Description: Overview of current AI capabilities specifically relevant to healthcare settings:
  • Documentation automation and assistance
  • Communication enhancement tools
  • Research synthesis and knowledge access
  • Clinical decision support capabilities
  • Current limitations and appropriate boundaries
• Learning Outcome: Participants will realistically assess where AI can provide meaningful assistance in healthcare workflows while understanding important limitations.

Unit 3: Ethical & Regulatory Considerations – 1 hr

• Description: Navigate the unique considerations for AI implementation in healthcare:
  • Patient privacy and HIPAA/PIPEDA compliance
  • Documentation requirements and medical-legal considerations
  • Appropriate delegation vs. clinical judgment
  • Patient consent and transparency
• Learning Outcome: Participants will develop a framework for ethical AI implementation that maintains compliance and professional standards.

Activities & Exercises – 2.5 hrs

• Burnout Assessment – 30 mins
  • Participants complete validated healthcare burnout measures and identify personal risk factors and warning signs.
• Task Audit & AI Opportunity Mapping – 1 hr
  • Participants inventory their daily tasks and identify high-burden administrative activities suitable for AI assistance.
• Ethical Boundary Setting – 1 hr
  • Small groups evaluate case studies of AI use in healthcare settings, identifying appropriate applications and potential concerns.

Day two focuses on mastering healthcare documentation tools and techniques that can reclaim significant time while maintaining compliance and quality. Through hands-on practice with AI tools designed for clinical documentation, participants develop customized templates and workflows that address their specific documentation needs. Healthcare organizations benefit from more complete and timely documentation, while professionals gain back hours previously lost to administrative tasks, allowing more focus on direct patient care.

Unit 1: Documentation Burden Analysis – 1 hr

• Description: Systematic approach to analyzing documentation requirements and inefficiencies:
  • Common documentation pain points across healthcare roles
  • Redundancy identification and reduction strategies
  • Quality vs. quantity considerations
  • Time tracking and efficiency metrics
• Learning Outcome: Participants will quantify their documentation burden and identify highest-impact opportunities for AI assistance.

Unit 2: AI Documentation Tools & Techniques – 1 hr

• Description: Overview of AI documentation assistants and implementation approaches:
  • Voice-to-text optimization for clinical terminology
  • Template development for common documentation needs
  • Structured data entry assistance
  • Note summarization and organization tools
• Learning Outcome: Participants will understand available documentation tools and select appropriate options for their specific clinical context.

Unit 3: Customization & Workflow Integration – 1 hr

• Description: Strategies for personalizing AI documentation tools:
  • Specialty-specific template development
  • Custom command and shortcut creation
  • Workflow integration for seamless adoption
  • Quality verification and error correction protocols
• Learning Outcome: Participants will develop customized documentation approaches that align with their practice patterns while maintaining quality standards.

Activities & Exercises – 3 hrs

• Tool Demonstration & Practice – 1.5 hrs
  • Hands-on exploration of AI documentation tools with practice creating clinical notes for sample scenarios.
• Template Development Workshop – 1 hr
  • Participants create and refine documentation templates for their most common clinical scenarios.
• Workflow Integration Planning – 30 mins
  • Each participant designs a specific plan for integrating AI documentation tools into their daily practice.

Day three addresses the challenge of maintaining meaningful patient connections while managing high workloads. Participants learn to leverage AI tools for routine communications while preserving personalized touch points. Through practice with patient education materials, follow-up protocols, and communication templates, healthcare professionals develop strategies that enhance patient satisfaction while reducing administrative time. These skills create more efficient practices with higher patient engagement and better adherence to treatment plans.

Unit 1: Communication Challenges in Modern Healthcare – 1 hr

• Description: Examine current challenges in provider-patient communication:
  • Time constraints and their impact on communication quality
  • Information overload and retention challenges
  • Follow-up barriers and continuity issues
  • Documentation requirements during patient interactions
• Learning Outcome: Participants will identify personal communication challenges and opportunities for enhancement through strategic AI support.

Unit 2: AI-Enhanced Patient Education – 1 hr

• Description: Utilizing AI tools to create and customize patient education:
  • Generating condition-specific educational materials
  • Customizing instructions for patient literacy and language needs
  • Creating visual aids and explanatory materials
  • Developing consistent messaging across team members
• Learning Outcome: Participants will efficiently create high-quality, personalized patient education materials using AI assistance.

Unit 3: Communication Templates & Protocols – 1 hr

• Description: Developing standardized yet personalized communication approaches:
  • Follow-up message frameworks
  • Previsit questionnaire development
  • Routine update and check-in protocols
  • Response templates for common inquiries
• Learning Outcome: Participants will implement communication templates that maintain personal connection while reducing repetitive messaging tasks.

Activities & Exercises – 2 hrs

• Education Material Creation – 1 hr
  • Participants develop condition-specific education materials using AI tools, tailored to different patient demographics.
• Communication Template Development – 1 hr
  • Small groups create and refine communication templates for common scenarios in their practice areas.

Day four focuses on appropriate use of AI for information management and clinical decision support. Participants learn to utilize AI tools for research synthesis, evidence review, and diagnostic consideration while maintaining clinical judgment. Through hands-on practice with research queries and differential diagnosis exercises, healthcare professionals develop skills that enhance clinical reasoning while reducing cognitive burden. These capabilities improve diagnostic accuracy and treatment planning while saving valuable time previously spent on literature searches.

Unit 1: Information Overload in Healthcare – 1 hr

• Description: Examine the challenges of keeping current with medical information:
  • Volume of medical literature and research
  • Practice guidelines and updates
  • Drug interactions and medication management
  • Rare condition identification and management
• Learning Outcome: Participants will identify personal information management challenges and develop strategies for efficient knowledge access.

Unit 2: AI for Research Synthesis & Evidence Review – 1 hr

• Description: Leveraging AI tools for navigating medical literature:
  • Formulating effective clinical queries
  • Evaluating AI-generated research summaries
  • Accessing evidence-based guidelines
  • Staying current with specialty developments
• Learning Outcome: Participants will efficiently access and synthesize medical information using AI tools while maintaining critical evaluation skills.

Unit 3: Diagnostic Reasoning Support – 1 hr

• Description: Appropriate use of AI for clinical reasoning enhancement:
  • Differential diagnosis expansion
  • Rare presentation identification
  • Structured clinical data review
  • Treatment option comparison
• Learning Outcome: Participants will utilize AI to support and enhance clinical reasoning while maintaining professional judgment and expertise.

Activities & Exercises – 2 hrs

• Research Query Workshop – 1 hr
  • Participants practice formulating effective clinical questions and using AI tools to synthesize relevant evidence.
• Clinical Reasoning Exercise – 1 hr
  • Using case studies, participants practice using AI tools to support differential diagnosis and treatment planning.

Day five addresses the personal resilience and wellbeing practices essential for sustainable healthcare careers. Participants develop personalized strategies for stress management, boundary setting, and professional fulfillment. Through reflective exercises and skills practice, healthcare professionals build a comprehensive approach to preventing burnout while enhancing engagement. These practices ensure that efficiency gains from AI implementation translate to improved wellbeing rather than increased workload, supporting long-term career sustainability and satisfaction.

Unit 1: Healthcare-Specific Wellbeing Challenges – 1 hr

• Description: Examine the unique stressors affecting healthcare professionals:
  • Emotional demands of patient care
  • Moral distress and ethical challenges
  • Work-home boundary challenges
  • Perfectionism and self-criticism
• Learning Outcome: Participants will identify personal wellbeing challenges and develop awareness of early warning signs.

Unit 2: Evidence-Based Resilience Practices – 1 hr

• Description: Explore research-supported approaches to healthcare professional wellbeing:
  • Mindfulness and present-moment awareness
  • Cognitive reframing techniques
  • Gratitude and meaning-focused practices
  • Boundary-setting strategies
  • Physical wellbeing fundamentals
• Learning Outcome: Participants will select and adapt evidence-based resilience practices aligned with their personal needs and preferences.

Unit 3: Community & Support Resources – 1 hr

• Description: Developing professional support networks and resources:
  • Peer support structure development
  • Professional coaching and mentorship
  • Specialized mental health resources
  • Organizational advocacy approaches
• Learning Outcome: Participants will establish a personal support plan that includes both immediate colleagues and expanded professional networks.

Activities & Exercises – 2 hrs

• Resilience Practice Lab – 1 hr
  • Guided practice with various wellbeing techniques, allowing participants to experience and select preferred approaches.
• Personal Wellbeing Plan Development – 1 hr
  • Each participant creates a structured wellbeing plan incorporating daily, weekly, and monthly practices.

The final day transforms learning into systematic implementation plans for both AI integration and wellbeing practices. Participants develop comprehensive approaches to technology adoption, focusing on sustainable change management and continuous improvement. Through collaborative problem-solving and personalized planning, healthcare professionals create roadmaps for implementing changes that reduce administrative burden while supporting personal resilience. This integrated approach ensures that technology becomes a meaningful support rather than another workplace demand.

Unit 1: Change Management in Healthcare Settings – 1 hr

• Description: Strategies for effective technology implementation:
  • Stakeholder identification and engagement
  • Workflow integration planning
  • Training and support requirements
  • Measuring success and impact
• Learning Outcome: Participants will develop change management approaches tailored to healthcare’s unique organizational dynamics.

Unit 2: Integration Planning – 1 hr

• Description: Creating comprehensive implementation roadmaps:
  • Prioritization and phased implementation
  • Team involvement and delegation
  • Resource requirements and investment planning
  • Compliance and quality monitoring
• Learning Outcome: Participants will create structured implementation plans that align with organizational realities and personal practice needs.

Activities & Exercises – 3.5 hrs

• Obstacle Analysis & Mitigation Planning – 1 hr
  • Participants identify potential barriers to implementation and develop specific strategies to address them.
• 30-60-90 Day Action Planning – 1.5 hrs
  • Each participant creates a detailed timeline for implementing both AI tools and wellbeing practices.
• Peer Feedback & Refinement – 1 hr
  • In pairs, participants review each other’s plans, offering feedback and suggestions for enhancement.