Toward Conceptual and Functional Clarity of Autonomous Health Workforce Technologies: A Scoping Review

Abstract

Health systems worldwide face rising workforce pressures, increasing interest in autonomous technologies that support clinical and operational tasks with minimal human input. We use the term <i>autonomous health workforce technologies</i> (AHWTs) to describe digital systems that operate with varying autonomy to assist health workers. This scoping review examined 38 peer-reviewed studies published from 2014 to 2025 that describe such technologies, though none used or defined the AHWT term. Using an inductive approach, we analyzed how autonomy, workforce integration, and technical features are reported, identifying five roles: clinical decision support, interactive patient care, surgical assistance, administrative coordination, and patient monitoring. These insights informed a classification framework covering autonomy level, cognitive function, workforce context, clinical domain, care setting, data sources, and AI methods. The framework supports comparison of diverse technologies and their relationships with the health workforce. Research remains concentrated in high-income settings, with limited attention to workforce experience and equity.

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