Learning from complaints about surgical care: a large language model-assisted sequential methods analysis

Key Points

• The analysis reveals that complaints focus more on postoperative monitoring and communication than on technical errors.
• Key evidence showed a need for better handover and escalation processes to address surgical care complaints effectively.
• This observational analysis highlights the potential of large language models to enhance complaint analysis in healthcare settings.
• The findings suggest integrating LLM technology may improve organizational learning and overall quality of surgical care.

Abstract