What May Impact Trustworthiness of AI in Digital Healthcare: Discussion from Patients’ Viewpoint

Abstract

The healthcare industry is undergoing a transformation of traditional medical relationships from human-physician interactions to digital healthcare focusing on physician-AI-patient interactions. Patients’ trustworthiness is the cornerstone of adopting new technologies expounding the reliability, integrity, and ability of AI-based systems and devices to provide an accurate and safe healthcare environment. The main objective of this study is to investigate the various factors that influence patients’ trustworthiness in AI-based systems and devices, taking into account differences in patients’ experiences and backgrounds. First, an exploratory conceptual framework inspired by the United Theory of Acceptance and Use of Technology (UTAUT) and Health Belief Model (HBM) is established to further explain the patients’ trust to support the adoption willingness of AI. Then a case study that includes 218 samples from chronic patients is conducted. The results of the study indicate that factors such as accountability, risk perception, facilitating conditions, and social influence play a significant role in determining a patient’s trust in AI-based healthcare devices, while ease of ease may not have a direct impact to trust. And among the demographic factors, only race showed a strong correlation with the level of patient trust in AI. The contributions of this study can provide a comprehensive understanding of patients’ trustworthiness and inform the development and deployment of the technology in a way that prioritizes patients’ interests.