Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment

• Published in: Journal of medical Internet research Vol. 23; no. 2; p. e22841
• Main Authors: Liu, Taoran, Tsang, Winghei, Huang, Fengqiu, Lau, Oi Ying, Chen, Yanhui, Sheng, Jie, Guo, Yiwei, Akinwunmi, Babatunde, Zhang, Casper JP, Ming, Wai-Kit
• Format: Journal Article
• Language: English
• Published: Canada Gunther Eysenbach MD MPH, Associate Professor 23.02.2021; JMIR Publications
• Subjects: Accuracy; Adolescent; Adult; Aged; Aged, 80 and over; Artificial Intelligence; Attributes; Big Data; China; Choice Behavior; Clinical decision making; Coronaviruses; COVID-19; Critical incidents; Diagnosis; Diagnostic Techniques and Procedures - economics; Discrete choice; Epidemics; Experiments; Female; Health care industry; Health Expenditures; Health services; Hospitals; Humans; Intelligence; Latent Class Analysis; Logistic Models; Male; Medical diagnosis; Medical research; Middle Aged; Misdiagnosis; Neural networks; Original Paper; Pandemics; Patient Preference; Physicians; Preferences; Prospects; Public health; Questionnaires; SARS-CoV-2; Severe acute respiratory syndrome; Severe acute respiratory syndrome coronavirus 2; Software; Surveys and Questionnaires; Time Factors; Waiting times; Young Adult; China; United States > US; COVID-19; app; discrete choice experiment; human clinicians; patient preference; multinomial logit analysis; questionnaire; China; latent-class conditional logit; diagnosis; artificial intelligence

Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in bi...