Patients' Views on AI for Risk Prediction in Shared Decision-Making for Knee Replacement Surgery: Qualitative Interview Study.
Daniel J GouldMichelle M DowseyMarion Glanville-HearstTimothy SpelmanJames A BaileyPeter F M ChoongSamantha BunzliPublished in: Journal of medical Internet research (2023)
Patients who underwent knee replacement surgery in this study had varied levels of familiarity with AI and diverse conceptualizations of its definitions and capabilities. Educating patients about AI through nontechnical explanations and illustrative scenarios could help inform their decision to use it for risk prediction in the shared decision-making process with their surgeon. These findings could be used in the process of developing a questionnaire to ascertain the views of patients undergoing knee replacement surgery on the acceptability of AI in shared clinical decision-making. Future work could investigate the accuracy of this patient group's understanding of AI, beyond their familiarity with it, and how this influences their acceptance of its use. Surgeons may play a key role in finding a place for AI in the clinical setting as the uptake of this technology in health care continues to grow.
Keyphrases
- end stage renal disease
- artificial intelligence
- chronic kidney disease
- ejection fraction
- newly diagnosed
- healthcare
- patients undergoing
- minimally invasive
- decision making
- peritoneal dialysis
- prognostic factors
- climate change
- systematic review
- patient reported outcomes
- coronary artery bypass
- atrial fibrillation
- patient reported
- health insurance
- acute coronary syndrome
- robot assisted
- case report
- surgical site infection
- deep learning
- quality improvement