AI and the Clinician: Navigating Responsible Use in
Rehabilitation (Recorded Webinar)
Presented by Aimee E. Perron
This course is a recording of a previously hosted live webinar event. Polling and question submission features are not available for this recording. Format and structure may differ from those of standard Medbridge courses.
Artificial intelligence (AI) tools are increasingly appearing in clinical documentation, education, patient communication, and decision support across the rehabilitation professions. While these technologies offer opportunities to improve efficiency and access to information, their use also raises important ethical, professional, and regulatory considerations for clinicians. This webinar introduces key concepts related to the responsible use of AI for healthcare and rehabilitation professionals. Drawing from established ethical frameworks for AI, participants will explore how professional values, transparency, clinical judgment, and patient trust must remain central when integrating AI into practice. Through practice-based case examples, participants will examine current challenges, including bias, overreliance on AI outputs, and limitations in evidence validation, and explore opportunities to leverage AI as a supportive clinical tool. The session will also discuss emerging regulatory considerations and practical strategies to help clinicians thoughtfully evaluate AI tools and responsibly incorporate them into patient-centered care. By the end of the webinar, participants will be better equipped to thoughtfully evaluate and responsibly integrate AI tools while maintaining ethical standards and patient-centered care.
Learning Outcomes
- Distinguish the current and emerging roles of artificial intelligence in healthcare and rehabilitation practice, including common applications, opportunities, and limitations
- Deduce key factors that influence clinical decision-making when using artificial intelligence, including bias, data quality, transparency, and the potential for overreliance on generated outputs
- Integrate core principles that guide responsible and human-centered use of artificial intelligence, including fairness, accountability, transparency, safety, and respect for human autonomy
- Apply practical strategies to evaluate and responsibly integrate artificial intelligence into clinical practice, including AI tools that support ADL performance, functional mobility, and patient education, while maintaining clinical judgment, professional accountability, and patient-centered care
Meet your instructor
Aimee E. Perron
Aimee E. Perron is currently an assistant professor and associate director of clinical education at Northeastern University in Boston, Massachusetts. She earned her MS in physical therapy from Boston University and her DPT from Massachusetts General Hospital Institute of Health Professions. She has more than 27 years of…
Chapters & learning objectives
1. AI in Clinical Practice: Why This Matters Now
This chapter introduces the growing role of artificial intelligence in rehabilitation and healthcare practice, including documentation, communication, and decision support tools. Participants will explore both the opportunities and limitations of AI, with an emphasis on why ethical and human-centered approaches are essential for maintaining clinical judgment and patient trust.
2. What Shapes AI-Supported Clinical Decisions
This chapter examines the key factors that influence clinical decision-making when AI tools are used. Participants will explore how bias, data quality, transparency, and system design impact both clinician judgment and patient outcomes.
3. What Does “Responsible AI” Actually Mean?
This chapter introduces key approaches that guide the responsible and human-centered use of artificial intelligence in healthcare. Participants will explore how these perspectives align around shared ethical priorities such as fairness, accountability, transparency, safety, and respect for human autonomy. The discussion will also focus on how these principles inform the thoughtful integration of artificial intelligence into clinical decision-making and patient-centered care.
4. Applying AI Responsibly in Clinical Practice
This chapter translates ethical frameworks into practical clinical decision-making. Through case-based examples, participants will apply human-centered and responsible AI principles to evaluate AI tools and determine when and how they can be appropriately used in patient care.
5. Question and Answer Session
This chapter is a viewer-submitted question and answer session facilitated by the course instructor, Aimee Perron.
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