Use of an Artificial Intelligence Conversational Agent (Chatbot) for Hip Arthroscopy Patients Following Surgery

Abstract

Purpose The purpose of this study was to evaluate the use of an AI conversational agent during the postoperative recovery of patients undergoing elective hip arthroscopy. Methods Patients undergoing hip arthroscopy were enrolled in a prospective cohort for their first 6 weeks following surgery. Patients used standard SMS text messaging to interact with an artificial intelligence (AI) chatbot (“Felix”) used to initiate automated conversations regarding elements of postoperative recovery. Patient satisfaction was measured at 6 weeks after surgery using a Likert scale survey. Accuracy was determined by measuring the appropriateness of chatbot responses, topic recognition, and examples of confusion. Safety was measured by evaluating the chatbot’s responses to any questions with potential medical urgency. Results Twenty‐six patients were enrolled with a mean age of 36 years, and 58% ( n = 15) were male. Overall, 80% of patients ( n = 20) rated the helpfulness of Felix as good or excellent. In the postoperative period, 12/25 (48%) patients reported being worried about a complication but were reassured by Felix and, thus, did not seek medical attention. Of a total of 128 independent patient questions, Felix handled 101/128 questions appropriately (79%), either by addressing them independently, or facilitating contact with the care team. Felix was able to adequately answer the patient question independently 31% of the time ( n = 40/128). Of 10 patient questions that were thought to potentially represent patient complications, in 3 cases Felix did not adequately address or recognize the health concern—none of these situations resulted in patient harm. Conclusion The results of this study demonstrate that the use of a chatbot or conversational agent can enhance the postoperative experience for hip arthroscopy patients, as demonstrated by high levels of patient satisfaction. Levels of Evidence Level IV, therapeutic case series.

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