ABSTRACT
Background The escalating overload and saturation of emergency services, primarily caused by non-urgent cases overwhelming the system, have spurred a critical necessity for innovative solutions that can effectively differentiate genuine emergencies from situations that could be managed through alternative means, such as using AI chatbots. This study aims to evaluate and compare the accuracy in differentiating between a medical emergency and a non-emergency of three of the most popular AI chatbots at the moment. Methods In this study, patient questions from the online forum r/AskDocs on Reddit were collected to determine whether their clinical cases were emergencies. A total of 176 questions were reviewed by the authors, with 75 deemed emergencies and 101 non-emergencies. These questions were then posed to AI chatbots, including ChatGPT, Google Bard, and Microsoft Bing AI, with their responses evaluated against each other and the authors' responses. A criteria-based system categorized the AI chatbot answers as "yes," "no," or "cannot determine." The performance of each AI chatbot was compared in both emergency and non-emergency cases, and statistical analysis was conducted to assess the significance of differences in their performance. Results In general, AI chatbots considered around 12-15% more cases to be an emergency than reviewers, while they considered a very low number of cases as non-emergency compared to reviewers (around 35% fewer cases). Google Bard detected the most true emergency cases (87%) and true non-emergency cases (36%). However, no real difference in performance between the three AI chatbots was found in detecting true emergencies (p-value = 0.35) and non-emergency cases (p-value = 0.16). Conclusions These AI systems require further refinement to identify emergency situations accurately, but they could potentially be an innovative tool for emergency care and improving patient outcomes. The integration of AI chatbots like ChatGPT, Google Bard, and Microsoft Bing Chat offers a promising avenue to mitigate ED strain and enhance emergency management.