Legal Solutions for AI and Telehealth Implementation: A PRISMA-ScR-Guided Analytical and Comparative Review

Abstract

Background: Telehealth expanded rapidly during the COVID-19 pandemic, and artificial intelligence (AI) is now moving from research settings into diagnosis, triage and patient engagement. Legal frameworks have not kept pace. Clinicians, developers and health systems work under rules written for face-to-face care and for static medical devices.

Objective: To map the principal legal obstacles to the implementation of AI-enabled telehealth, compare how three jurisdictions (the European Union, the United States and India) respond to them, and propose an implementable legal solutions framework.

Methods: A scoping review guided by PRISMA 2020 and PRISMA-ScR was combined with comparative doctrinal analysis. The evidence base comprised 106 sources: 30 records selected from a supplied corpus of 117, and 76 external pre-2025 sources (legislation, case law, policy guidance and scholarly studies).

Results: Six recurrent fault lines emerged: health-data protection; licensure and jurisdiction; liability allocation; regulation of adaptive software as a medical device; transparency and consent; and algorithmic bias with digital inequity. The three jurisdictions show convergent principles but divergent mechanisms. The evidence reveals a persistent gap between the pace of deployment and the quality of clinical and legal validation.

Conclusions: The paper advances a Layered Accountability Framework with seven pillars and three citable propositions: proportionate accountability, lifecycle legality and equity-by-design. Legal solutions will succeed only if they are risk-tiered, continuously monitored and anchored in patient-centred rights.