Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/305646 
Year of Publication: 
2024
Series/Report no.: 
IZA Discussion Papers No. 17204
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
Using simulated patients to mimic nine established non-communicable and infectious diseases over 27 trials, we assess ChatGPT's effectiveness and reliability in diagnosing and treating common diseases in low- and middle-income countries. We find ChatGPT's performance varied within a single disease, despite a high level of accuracy in both correct diagnosis (74.1%) and medication prescription (84.5%). Additionally, ChatGPT recommended a concerning level of unnecessary or harmful medications (85.2%) even with correct diagnoses. Finally, ChatGPT performed better in managing non-communicable diseases compared to infectious ones. These results highlight the need for cautious AI integration in healthcare systems to ensure quality and safety.
Subjects: 
healthcare
simulated patient
generative AI
Large Language Models
ChatGPT
quality
safety
low- and middle-income countries
JEL: 
C0
I10
I11
C90
Document Type: 
Working Paper

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