WHC Keynote Learn^JUnlearn and Relearn Sept 2024.pdf
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The document discusses the urgent need for unlearning and relearning in the healthcare sector to adapt to evolving practices and technologies, emphasizing the importance of structured unlearning processes to improve patient safety and care outcomes. It highlights the integration of AI-driven tools into clinical workflows to enhance productivity and decision-making while addressing ethical considerations, such as patient privacy and bias mitigation. The document also outlines implementation strategies for fostering a culture of continuous improvement and adapting medical education to prepare future healthcare professionals for an AI-augmented environment.
WHC Keynote Learn^JUnlearn and Relearn Sept 2024.pdf
- 1. by Vaikunthan Rajaratnam MBBS,FRCS(Ed),MBA,MIDT, PhD(Education). Senior Consultant, Hand & Reconstructive Microsurgery, KTPH, Singapore Program Director Instructional Design for Healthcare & AI in Healthcare NHG, Singapore Adjunct Professor/UNESCO Chair Partner, Asia Pacific University of Technology and Innovation, Malaysia Honorary Professor, De Montfort University, UK Embracing Change, Unlearning, and Relearning: Adapting to the Future of Healthcare
- 2. Warning: Unprecedented Levels of Productivity and Inspiration Ahead! Please be advised: The content of this workshop is so intensely engaging and empowering in the realm of AI in healthcare that it carries a high risk of sparking a newfound addiction to productivity and innovation. Attendees may experience an irresistible urge to apply transformative skills and insights in their professional practice, leading to significant advancements in healthcare. Proceed with enthusiasm and caution – you're stepping into a world of exhilarating empowerment! Embrace the journey, but don't say we didn't warn you!
- 3. Disclaimer • I am not an AI expert, nor do I possess coding knowledge specific to the underlying mechanisms of AI models; • My expertise lies in the utilisation of these models, such as ChatGPT, based on my extensive experience as a user within the fields of healthcare, medical education, and related research, rather than their technical development or underlying algorithms. • This workshop is intended solely for educational and informational purposes in AI and healthcare. • The views expressed herein are my own, borne from extensive experience in surgery, medical education, and instructional design, and do not necessarily reflect those of any associated institutions. • While I endeavour to provide accurate and up-to-date information, no guarantee is given regarding its applicability. • Participants acknowledge and assume responsibility for using the information provided by engaging in this workshop. Vaikunthan Rajaratnam
- 4. Innovative Digital Learning Centre Artificial Intelligence Innovative Designs for Education (AIDE) Framework
- 6. • Tools for Effective Academic Courses and Holistic Teaching • MOE Malaysia AI TEACH • For students in middle school • Indigenous School, Malaysia AI LEARN • Gerontological Optimization through Learning and Digital Assistance AI GOLD • Learning Designs • APU, Malaysia, NHG, Singapore AI LD • Health Professional • Perdana University , Malaysia, BDSSH, Bangladesh • NHG, Singapore, Sengkang, Singapore AI HP • Research • Perdana University, Malaysia, Sengkang , Singapore • University of Eswatini (Africa) AI RE •Academic Writing • APU, Perdana University, Malaysia • University of Eswatini (Africa) AI AW • Leveraging Efficiency in Administrative Proficiency • MOE, Dubai AI LEAP
- 7. Main Findings on Unlearning and Relearning in Healthcare A Summary of Key Research Insights
- 8. Unlearning Outdated Practices: Embracing a Mindset of Continuous Learning and Improvement 1 Challenge Assumptions Regularly question the status quo and be open to new approaches that challenge conventional wisdom. 2 Foster a Culture of Innovation Encourage a mindset of continuous learning and experimentation to drive meaningful change. 3 Adapt to Evolving Needs Stay agile and responsive to the changing demands of patients and the healthcare landscape.
- 9. Physician Unlearning and Clinical Practice Changes • Physicians face challenges in unlearning outdated practices. • Incomplete unlearning - increased medical errors. • Structured unlearning processes are needed to prevent patient harm. (Noteboom, Hafner, & Wahbeh, 2017; Hafner, 2016)
- 10. Organisational Unlearning Unlearning is critical for adapting to new practices and technologies. Effective unlearning improves patient safety and care outcomes. (Sharma & Lenka, 2019)
- 11. Link Between Unlearning and Innovation Unlearning is essential for fostering innovation in healthcare. Relearning fails without deliberate unlearning of obsolete practices. (Bedford, 2015)
- 12. Impact on Patient Safety Failure to unlearn outdated practices - patient safety issues. Focusing on unlearning can reduce medical errors and improve care quality. (Gupta, Boland, & Aron, 2017)
- 13. Policy Recommendations for Unlearning in Healthcare Structured Approaches to Enhance Professional Practice and Patient Safety This Photo by Unknown Author is licensed under CC BY
- 14. Structured Unlearning Processes • Develop structured processes for unlearning outdated practices. • Ensure smooth transition to new protocols and guidelines. • Focus on patient safety and reducing medical errors.
- 15. Rationale for Structured Unlearning Stay current with clinical guidelines. Reduces inefficiencies and improves resource use. Patient safety by eliminating outdated practices.
- 16. Overview of Structured Unlearning Unlearning involves intentionally discarding outdated knowledge and practices. Vital for adopting new, evidence-based practices in healthcare. Helps prevent patient harm Improves efficiency.
- 17. • Conduct regular assessments and audits. • Implement feedback systems for reporting outdated practices. Identify Outdated Practices • Develop educational programs and communication strategies. • Apply change management principles to support acceptance. Create Awareness • Establish structured unlearning programs within professional development. • Integrate unlearning into medical education curricula. Develop Unlearning Protocols • Organize workshops, simulations, and training sessions. • Set up mentorship and peer learning programs. Implement Training and Support • Continuously reinforce new practices through practice and assessments. • Monitor and evaluate the effectiveness of unlearning initiatives. Reinforce New Learning • Integrate unlearning into organisational policies and procedures. • Foster a culture of continuous improvement and open dialogue. Institutionalise Unlearning • Regularly review and update unlearning processes. • Establish a feedback loop for continuous improvement Evaluate and Update
- 18. Integrate unlearning into medical education and professional development. Establish mentorship and peer learning programs. Conduct regular audits and provide feedback on clinical practices. Implementation Strategies
- 19. Resistance to change among experienced professionals. Unlearning should be seen as an ongoing process, not a one- time event. Requires careful change management and involvement of staff. Challenges and Considerations
- 20. Embed unlearning as a core component in medical curricula. Prepare future healthcare professionals to adapt to change. Improve the transition to new clinical guidelines and technologies. Integration in Medical Education
- 21. Support Systems for Unlearning Establish mentorship and peer support programs. Provide regular assessments and feedback to ensure effective unlearning. Foster a culture of continuous improvement and adaptation.
- 22. Patient Safety Reforms Integrate unlearning strategies into patient safety policies. Mitigate risks associated with outdated practices. Focus on reducing errors and enhancing care quality.
- 23. Revolutionising Healthcare through AI AI technologies have the potential to revolutionise healthcare by enhancing diagnosis, treatment planning, and research. AI won't replace you, but someone empowered by AI undoubtedly will
- 24. Upskilling Healthcare Professionals: Adapting to the AI-Augmented Future Digital Literacy Develop proficiency in leveraging AI-driven tools and technologies to enhance patient care. Data Analytics Cultivate skills in interpreting and applying data-driven insights generated by generative AI. Ethical AI Practices Understand and implement ethical guidelines for the responsible use of AI in healthcare.
- 25. Relearning Through Data-Driven Insights: Leveraging Generative AI for Better Decision-Making Predictive Analytics Utilize generative AI to identify patterns and trends, enabling proactive and personalized care. Clinical Decision Support Empower clinicians with AI- powered recommendations and decision-making tools for improved patient outcomes. Streamlined Workflows Integrate generative AI into daily tasks to automate repetitive processes and enhance efficiency.
- 26. Integrating Generative AI into Daily Clinical Workflows 1 Data Collection Leverage AI-powered sensors and devices to gather comprehensive patient data. 2 Intelligent Insights Utilize generative AI to analyze data and provide personalized recommendations. 3 Streamlined Workflows Integrate AI-driven tools into daily clinical processes for enhanced efficiency.
- 27. Enhancing Patient Engagement and Communication with AI- Powered Tools Conversational AI Intelligent chatbots and virtual assistants for seamless patient communication. Personalized Guidance AI-powered tools that provide tailored health advice and support for patients. Increased Engagement AI-driven platforms that foster stronger patient-provider relationships.
- 28. Ethical Considerations and Responsible AI Implementation Transparency and Accountability Ensure clear communication and ethical guidelines for the use of generative AI in healthcare. Patient Privacy and Data Security Prioritize the protection of sensitive patient information and adhere to data privacy regulations. Bias Mitigation Proactively address and minimize biases in AI-driven decision-making and patient care. Continuous Monitoring Establish robust monitoring and evaluation processes to ensure responsible AI implementation.
- 29. Introduction to Generative AI
- 30. https://chat.openai.com/ https://copilot.microsoft.com/ https://bard.google.com/ Generative AI Platforms
- 31. Opening a ChatGPT Account chatgpt.com
- 34. Prompt Generation Steps Define Your Objective •Be specific •Overall goal Understand Your AI Model •Model capabilities •Data Reliability Break Down Complex Tasks •Deconstruct •Sequence Craft Clear and Concise Prompts •Avoid ambiguity •Provide context •Specify outputs Start with Examples (Few- Shot Learning) •Illustrative input/output Iterate and Refine •Analyse responses •Adjust language •Test, test, test
- 35. Checklist for Healthcare Prompt Engineering
- 36. Response Validation RI meets AI • Review response - meets your requirements. • No access to real-time data • Vaildate Validate Validate. • Prompt – response -refine - reprompt. Relevance Check Accuracy Confirmation Context Consistency Sensitivity Review Refinement for Future Queries
- 37. Review AI Output with RI •Critically assess •Relevance •Plausibility Key Term Extraction •Extract central terms Strategic Search in Academic Databases •Focused search •Using Extracted terms •Employing advanced search techniques Literature Screening •Select relevant scholarly articles •Prioritising high-quality, peer- reviewed sources •In-depth analysis. Evidence-Based Validation •Critically evaluate the literature •Corroborate or challenge the AI- generated information •Look for consistency and consensus Synthesis and Documentation •Compile and synthesise findings •Validate the AI’s responses •Document and cite the sources Evidence-based Validation
- 46. Dictate Insert prompt Upload to MyGPT Send EMR to email Review & Edit Insert to Institution EMR