Welcome !
Questionnaire Workshop MIE 2024
Will AI Adoption in Medicine Mirror the Evolution of Medical Informatics?
It might look long, but it will take only around 10 - 15 minutes.
Not mandatory to answer all questions - if not sure you can leave some questions without an answer. ABREVIATIONS: AI = Artificial Intelligence, AIM = Artificial intelligence in Medicine, MI = Medical Informatics, CDSS = Clinical Decision Support System, IoT = Internet of Things
Section 1: Participant Information
Personal data - optional
Name
First Name
Last Name
Email
example@example.com
1.1. What is your primary field of expertise or professional background?
Physician
Nurse
Healthcare Administrator
Computer Scientist/Engineer
Student
Multiple or Other (please specify)
Other
1.2. Experience with AI in Medicine
None
Beginner
Intermediate
Advanced
Expert
1.3. Would you be interested in participating in future discussions on this topic in a dedicated forum?
Yes, I would be very interested.
Yes, I might be interested.
Possible but unsure at this time.
No, I am not interested.
1.4. Any comment related to the topic of the workshop
Section 2: Workshop Content and Experience
2.1. How relevant did you find the topics discussed?
Very relevant
Somewhat relevant
Neutral
Somewhat irrelevant
Not relevant at all
2.2. Which topic was most valuable to you?
AI in clinical applications
AI in medical education
Ethical considerations of AI
Biomedical Scientific/Technological Challenges of Generative AI
Future directions of AI in medicine
Other (Please specify)
2.3. What additional topics would you like to see covered in future workshops?
2.4. Any comment related to the organization of the workshop
Section 3: Impact and Comparison of AIM and Medical Informatics - Organizational Changes
3.1. How do you perceive the impact of AIM compared to medical informatics on clinical practice?
Much greater impact
Somewhat greater impact
About the same
Less impact
No impact at all
3.2. In your view, which of the following is a greater barrier to the successful implementation of technologies in healthcare?
Data privacy and security concerns are more significant in AIM than in MI.
Interoperability and data silos pose larger challenges for MI than for AIM.
Regulatory and compliance issues are more obstructive for AIM due to its decision-making impacts and ethical/managerial/organizational repercussions.
User resistance and lack of training present equal barriers for both AIM and MI.
3.3. How do you foresee AIM affecting the roles of healthcare professionals ?
Significantly enhancing decision-making capabilities through advanced CDSS.
Shifting focus from routine tasks to more complex and critical care responsibilities.
Causing minimal changes to current roles and responsibilities.
Potentially replacing some traditional roles with largely rule-constrained and
automated systems.
3.4. In which of the following operational aspects do you expect AIM to bring the most significant improvements?
Patient scheduling and resource allocation.
Supply chain management and logistics.
Patient monitoring and real-time data analysis.
Administrative tasks and documentation processes.
Section 4: Comparison of AIM and Medical Informatics: Barriers& Potential Mistakes
4.1. Which barrier do you believe has a more profound impact on the integration of new technologies in healthcare?
Ethical considerations and algorithmic/data pre-training/selection biases in AIM
Funding and infrastructure limitations affecting both AIM and MI
Technological complexity and the need for specialized knowledge in AIM
Adoption and cultural resistance within healthcare settings for both MI and AIM
Legal and organizational constrains on MI and AIM within IoT contexts
4.2. Which strategy do you think is most effective in overcoming barriers to the implementation of AIM and MI in healthcare?
Developing comprehensive regulatory frameworks tailored to each medical specialty and related fields
Enhancing inter-professional education and training in both AIM and MI
Increasing funding and resources for infrastructure development
Fostering collaboration among tech developers, healthcare institutional managers/stakeholders, and policymakers
4.3. Which of the following do you consider to be potential mistakes in the implementationof AIM that could mirror issues faced by medical informatics?
Overlooking or inderevaluating user-centric design in the development of AI tools.
Creating data silos due to poor interoperability with existing systems.
Underestimating the importance of privacy and security measures.
Overselling AI capabilities without sufficient clinical validation.
4.4. How important do you think user-centric design is in avoiding past mistakes when implementing AIM technologies?
Extremely important
Very important
Moderately important
Slightly important
Not important at all
4.5. Which strategy is most critical to prevent data silos in AIM, similar to those experienced in medical informatics?
Ensuring interoperability standards from the onset
Regular audits and updates of AI systems
Enhanced collaboration between tech developers and healthcare providers
Comprehensive training programs for healthcare professionals on data integration and human factors and guidance in IoT processes
4.6. What approach should be taken to prevent the overselling of AI capabilities in healthcare?
Stringent regulatory and clinical validation before implementation
Transparent communication about AI limitations and capabilities
Ongoing research and updates presented to the medical community
Section 5: Comparison of AIM and Medical Informatics: Education
5.1. How necessary do you believe it is to include AI education in the medical curriculum?
Absolutely essential
Very important
Somewhat important
Not very important
Unnecessary
5.2. Evaluate the potential of AIM to transform medical education compared to past innovations in medical informatics.
Much more transformative
Somewhat more transformative
Equally transformative
Less transformative
Not transformative
5.3. What is the optimal way to integrate AI education into the medical curriculum?
As a separate course covering both basic principles and specific applications
As a separate foundational course on AI, with applications integrated into clinical specialty courses
As a module within existing medical informatics courses
Other (please specify)
5.4. Should formal recommendations for AI course content in medical education be developed similar to those for medical informatics?
Yes, detailed content guidelines are needed
Yes, but only broad outlines are necessary
No, course content should be left to individual institutions
Unsure
5.5. To what extent do you believe AI can transform medical education?
Transform completely
Significantly enhance
Moderately improve
Slightly improve
No impact
5.6. In which areas of medical education would the integration of AI be most beneficial?
Diagnostic techniques
Treatment planning
Clinical decision-making
Research and data analysis
Patient management
Healthcare organizational and workflow modeling and testing
Healthcare policy-making and AIM initiatives
5.7. What are potential risks or misuses of AI in medical education that concern you?
Over-reliance on AI without understanding underlying principles
Misinterpretation of AI-generated data or recommendations
Bias in AI algorithms affecting educational outcomes
Privacy concerns with patient data used in teaching
5.8. What do you believe are the possible negative consequences of overusing AI in medical education?
Decreased critical thinking skills
Reduced interpersonal skills with patients
Overdependence on immature technologies, especially when ethical and policy implications are not well understood
Mismanagement of patient care due to overtrust in AI
5.9. Which future developments in AI do you believe will have the most impact on medical education?
Advanced simulation and VR for clinical training
Customized learning algorithms and Personal choice challenges
AI in genomics and personalized medicine
Real-time data analysis skills
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