Artificial intelligence in the operational management and quality of health services: a systematic literature review 2020–2025
Keywords:
Artificial intelligence, operational management, care quality, health servicesAbstract
The objective of this research was to analyze, through an exploratory systematic review of the literature, the relationship between artificial intelligence (AI), operational management, and the quality of healthcare services published during the period 2020–2025; for this purpose, a systematic review of scientific articles selected from specialized databases was conducted, applying eligibility criteria such as year of publication, type of study, thematic relevance, and methodological quality. The findings showed that the use of artificial intelligence technologies enabled the automation of administrative processes, the forecasting of healthcare demand, and the optimization of resource use in health systems, contributing to a reduction in operational errors, while also improving the quality of care across several attributes, particularly safety, effectiveness, and user experience. However, the studies also identified barriers that limit its adoption, including low system interoperability, insufficient training, resistance to acceptance among professionals, inequalities in implementation, and ethical challenges related to the use of sensitive data. In summary, the results demonstrated that artificial intelligence had a positive and progressive impact on operational management and the quality of healthcare services, provided that its implementation is accompanied by appropriate ethical, regulatory, and organizational frameworks.
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