Quality and Accountability of ChatGPT in Health Care in Low- and Middle-Income Countries: Simulated Patient Study

• Main Authors: Yafei Si (Author), Yuyi Yang (Author), Xi Wang (Author), Jiaqi Zu (Author), Xi Chen (Author), Xiaojing Fan (Author), Ruopeng An (Author), Sen Gong (Author)
• Format: Book
• Published: JMIR Publications, 2024-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

Using simulated patients to mimic 9 established noncommunicable and infectious diseases, we assessed ChatGPT's performance in treatment recommendations for common diseases in low- and middle-income countries. ChatGPT had a high level of accuracy in both correct diagnoses (20/27, 74%) and medication prescriptions (22/27, 82%) but a concerning level of unnecessary or harmful medications (23/27, 85%) even with correct diagnoses. ChatGPT performed better in managing noncommunicable diseases than infectious ones. These results highlight the need for cautious AI integration in health care systems to ensure quality and safety.

Item Description

1438-8871
10.2196/56121