Trust when the healthcare ecosystem is integrated with Artificial Intelligence

Area of Science:

• Healthcare technology
• Medical ethics
• Artificial intelligence in medicine

Background:

• Trust is fundamental to the patient-physician relationship.
• The integration of Artificial Intelligence (AI) medical tools complicates this relationship.
• Existing trust models in healthcare are limited, focusing on single partners and one-sided trust perspectives.

Purpose of the Study:

• To propose a novel theoretical framework for analyzing trust in the evolving healthcare ecosystem.
• To address the gap in existing models by considering multi-partner trust dynamics involving patients, physicians, and AI medical tools.
• To conceptualize trusted behavior as an outcome of dynamic interpersonal and institutional trust relationships.

Main Methods:

• Development of the Patient-AI medical tools-Physician Interpersonal Trust (PAIP-IT) model.
• Conceptual analysis of trust relationships: patient-physician, patient-AI, physician-AI, and AI-mediated patient-physician interactions.
• Inclusion of institutional trust within the broader socio-cultural and institutional contexts.

Main Results:

• The PAIP-IT model offers a comprehensive view of trust dynamics.
• It identifies three key relational trust dynamics: direct patient-physician, dyadic trust towards AI, and AI-mediated trust.
• The model emphasizes the importance of institutional trust alongside interpersonal trust.

Conclusions:

• The PAIP-IT model provides a robust framework for understanding trust in AI-integrated healthcare.
• It highlights the complexity of trust involving multiple stakeholders and mediated interactions.
• Accounting for both interpersonal and institutional trust is crucial for navigating AI adoption in medicine.