Leveraging Generative AI Tools for Professional Development in Healthcare

Freddy Terrazas Escamilla is a Senior Director of Strategy for Mayo Clinic, and currently serves as a member of the HIMSS Professional Development Committee.

To leverage AI for professional development in healthcare, you can utilize its capabilities to analyze large datasets, provide personalized learning paths, simulate medical scenarios, offer real-time feedback on clinical decisions, automate routine tasks, and create intelligent virtual assistants that can support learning and practice outside of traditional training environments. 

Personalized Learning Plans:

AI can analyze a healthcare professional’s area of focus creating personalized learning modules that match a healthcare professional's field, experience, and knowledge gaps, making the content fit just for them. AI can track and analyze a healthcare professional's performance through patient data, providing detailed feedback on areas of strength and areas for improvement. In a busy workplace and healthcare industry, having the ability for AI to automate the development plan they wish to follow allows for augmentation in real-time while having candid conversations with colleagues and leaders to personalize development pathways.

Virtual Patient Simulations:

AI-powered virtual patients can simulate realistic medical scenarios, allowing healthcare providers to practice their clinical skills in a safe environment with diverse patient presentations and complex situations. For HIMSS members who are clinicians, utilizing AI to create a digital simulation of patient interactions allows for efficacious ways to test new and novel care interventions in a place and manner that works best for them.

Literature Review Support:

By using AI to analyze large amounts of medical information, identifying key findings, and selecting relevant studies for specific topics or clinical questions, professionals can focus on areas pertinent to their role more efficiently. Given the vast amount of information available today, it is essential for professionals to quickly sift through curated content to find what is most relevant to their field without expending excessive time.

Advanced Data Visualization:

AI can present complex patient data in clear, visual formats, enabling healthcare professionals to quickly spot patterns and trends. With AI, the time spent analyzing data is reduced, speeding up discovery and allowing for summarized insights to be shared with colleagues and leadership.

Skill-Based Training Modules:

AI has the capability to develop targeted training modules that cater to the specific skills required for healthcare professionals, such as advanced surgical techniques or complex medication management. Additionally, on the administrative front, digital twins and augmented technology can be utilized to simulate real situations, thereby ensuring safety and accuracy without causing harm to the environment, staff, organization, and most importantly, the patients.

Feedback and Assessment Tools:

Artificial Intelligence can monitor and evaluate the performance of healthcare professionals by analyzing patient data, and offering comprehensive feedback on strengths and areas needing development. Furthermore, AI tools can be utilized to furnish automated feedback on clinical performance during simulations or case reviews, thereby identifying opportunities for enhancement.

Important Considerations when using generative AI for professional development:

Data Quality:

Ensure the training data used for generative AI models is accurate, comprehensive, and representative of diverse patient populations.

Clinical Expertise:

Always verify AI-generated information against established medical knowledge and consult with clinical experts when necessary.

Ethical Implications:

Be mindful of potential biases in AI algorithms and address privacy concerns related to patient data.

User Training:

Provide adequate training for healthcare professionals on how to effectively utilize generative AI tools and interpret the generated outputs.

Sources:

• Rodriguez D, Lawrence K, Gonzalez J, Brandfield-Harvey B, Xu L, Tasneem S, Levine D, Mann D
  Leveraging Generative AI Tools to Support the Development of Digital Solutions in Health Care Research: Case Study
  JMIR Hum Factors 2024;11:e52885
  URL: https://humanfactors.jmir.org/2024/1/e52885
  DOI: 10.2196/52885

• How Companies Are Using Generative AI in Healthcare & Life Sciences
  Ryan Ries, Mission Cloud

• Generative AI tools for Healthcare Providers
  Healthcare Board of Innovation

• Tackling healthcare’s biggest burdens with generative AI
  Shashank Bhasker, Damien Bruce, Jessica Lamb, and George Stein, McKinsey & Company

• Generative AI in healthcare: benefits and top use cases
  Alexey Kozlovsky, EffectiveSoft