Related Experiment Video
Updated: Mar 19, 2026
05:57
A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique
Published on: January 6, 2023
3.9K
Patient Perceptions of Artificial Intelligence in Orthopaedic Surgery: Identifying Potential Barriers to Acceptance
Nicole J Newman-Hung1, Charlotte F Wahle, Yifan V Mao
1From the Department of Orthopaedic Surgery, University of California, Los Angeles, CA.
Summary
Patient acceptance of artificial intelligence (AI) in orthopaedic surgery varies by demographics. Education and income influence comfort, while concerns about patient-surgeon relationships persist, necessitating targeted education for responsible AI integration.
Area of Science:
- Orthopaedic Surgery
- Artificial Intelligence
- Patient Perceptions
Background:
- Growing enthusiasm for AI in orthopaedics contrasts with a lack of understanding regarding patient attitudes.
- Patient perceptions of AI in diagnosis, treatment, and communication within orthopaedic surgery remain largely unexplored.
Purpose of the Study:
- To assess patient comfort levels and perceptions of artificial intelligence (AI) integration in orthopaedic care.
- To identify demographic factors influencing patient acceptance of AI in orthopaedic diagnosis, treatment, and communication.
- To understand patient concerns regarding AI implementation in orthopaedic surgery.
Main Methods:
- A 28-question survey was administered to 300 patients across hand surgery, orthopaedic oncology, and joint replacement clinics.
- The survey evaluated patients' baseline comfort with AI, perceived strengths, weaknesses, risks, and benefits.
- Statistical analysis examined correlations between demographics and AI acceptance, as well as common patient concerns.
Main Results:
- While 55.2% were comfortable with AI-assisted diagnosis and 58.3% with robot-assisted surgery, only 34.7% were comfortable with AI-driven communication.
- Higher education and income correlated with greater AI acceptance (P < 0.001), while lower education levels were associated with fewer perceived benefits (P = 0.03).
- Key concerns included loss of patient-surgeon relationships (70.0%), surgeon overreliance on AI (56.9%), and lack of individualized care (51.5%). Men showed higher acceptance, while women expressed more concern about bias (P = 0.05). Older patients were less comfortable with AI diagnostics (P < 0.001).
Conclusions:
- Women, older patients, and those with lower education/income may experience decreased comfort with AI in orthopaedics, potentially impacting care quality.
- A universal concern is the potential weakening of the patient-surgeon relationship due to AI integration.
- Targeted patient education is crucial for addressing concerns and enabling the responsible adoption of AI tools in orthopaedic practice.
