Humanising Digital Healthcare: A Conceptual Framework of Algorithmic Governance, Professional Autonomy, and Nurse Well-Being

Abstract

This study presents a conceptual paper that illustrates the influence of algorithmic governance on nurse wellbeing, mediated by professional autonomy. Although A.I. and algorithmic management systems are widely used in nursing, the existing ethical approaches are mostly concerned with data privacy and the incidence of algorithmic bias, leaving a theoretical gap in the area of relations between governance systems, professional autonomy, and psychological wellbeing. The framework draws on ideas from nursing ethics, critical algorithm research, and organisational behaviour theory, and categorises two archetypal algorithm-driven forms of governance: augmenting governance (strengthening clinical judgement) and automating governance (substituting or strictly governing decisions). The framework states that automation of governance reduces perceived professional autonomy, leading to an increased risk of emotional exhaustion, depersonalisation and intention to leave, while transparent and co-designed governance can help maintain or even enhance nurse wellbeing. Four propositions have been stated that can be tested. Finally, the framework reflects a shift from the efficiency-focused to autonomy-focused algorithmic governance, providing a solid theoretical foundation for subsequent empirical studies and practical auditing of AI systems in nursing.