Patients' Views on AI for Risk Prediction in Shared Decision-Making for Knee Replacement Surgery: Qualitative...

Area of Science:

• Orthopedic Surgery
• Medical Informatics
• Patient Decision-Making

Background:

• Artificial intelligence (AI) is increasingly used in decision-making for knee replacement surgery.
• AI shows potential for improving patient outcome prediction.
• The definition and clinical application of AI remain subjects of ambiguity and debate.

Purpose of the Study:

• To explore patient understanding and attitudes towards AI in knee replacement surgery.
• To investigate patient perspectives on AI for risk prediction in shared clinical decision-making.

Main Methods:

• Qualitative study involving patients who underwent knee replacement surgery.
• Semistructured interviews to assess understanding and opinions on AI in decision-making.
• Thematic analysis of interview data until thematic saturation.

Main Results:

• 20 participants (55% female, median age 66) were interviewed; 55% experienced significant postoperative complications.
• Three key themes emerged: Expectations (patient self-determination), Empowerment (realistic expectations, personalized risk information), and Partnership (AI-clinician symbiosis).
• Patients demonstrated varied familiarity and conceptualizations of AI.

Conclusions:

• Patient understanding of AI in knee replacement surgery is diverse.
• Nontechnical patient education on AI is crucial for informed decision-making regarding its use in risk prediction.
• Future research should focus on AI's accuracy and its influence on patient acceptance, with surgeons playing a key role in AI integration.