Shifting from Disease-Centric to Patient-Centric Healthcare: Evaluating the Acceptance of AI Doctors among Physicians for Data Collection, Diagnosis, Treatment Planning, and Follow-Up Patients
Description
This study examines physicians' attitudes toward the acceptance to use AI doctors in healthcare. Currently, physicians use smart health technologies, health data, and AI in disease-focused research hospitals, and it is aimed by industry regulators that AI technology will be used extensively for outpatients which means a shift from diseases-centric to individual-centric healthcare. The research model has been designed according to the UTAUT. To understand physicians' acceptance to use of AI doctors for data collecting, diagnosis, treatment planning, and patient follow-up. To determine the causes and consequences of physicians' attitudes, behaviors, ideas, and beliefs, the causal comparison screening technique has been used. 478 physicians' replies have been evaluated using structural equation modeling and deep learning (artificial neural network). It was found that physicians have the intention of using AI technology for all phases of the patient-doctor relationship. However, no significant relationship was found between the perceived task-technology fit and data collection constructs. According to the results, performance expectancy, perceived task technology fit, high-tech habit, and hedonic motivation are the main constructs.