De los datos a la decisión: revisión sistemática del rol de la inteligencia artificial y el machine learning en la optimización de la gestión administrativa de Instituciones de Salud

Claudia Angelica Dazza Pineda; Fabian Armando Garzón Leon

doi:10.22490/26194759.11707

La Edición Especial FIKLiv 2026 de la Revista Biociencias reúne investigaciones y experiencias interdisciplinarias en cinco ejes: 1) salud, territorio, interculturalidad y transformación social; 2) determinantes, prevención, ambiente y cuidado de la salud; 3) formación, innovación y nuevas estrategias para el cuidado; 4) inteligencia artificial, salud digital, bioética y gestión basada en datos; y 5) IA, educación, ciencia abierta y futuro de la academia.

Vol. 9 No. 1 (2026): EDICIÓN ESPECIAL FIKLIV

Published 2026-08-18

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

III.METASALUD

From data to decision: systematic review of the role of artificial intelligence and machine learning in the optimization of the administrative management of Health Institutions

DOI: https://doi.org/10.22490/26194759.11707

Claudia Angelica Dazza Pineda Universidad Nacional Abierta y a Distancia

Fabian Armando Garzón Leon Universidad Nacional Abierta y a Distancia

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Abstract
References

Objective. To analyze the role of Artificial Intelligence and Machine Learning in optimizing administrative management within Healthcare Institutions, identifying their main applications, benefits, and challenges in data-driven decision-making. Method. A systematic literature review was conducted following the PRISMA 2020 guidelines. The search was performed in the PubMed, Scopus, SciELO, and Web of Science databases, considering publications between 2016 and 2025 related to artificial intelligence, machine learning, and healthcare administrative management. The selected studies were organized into three analytical categories: resource and logistics optimization, finance and revenue cycle management, and patient experience and flow. Results. A total of 25 scientific articles were included in the final analysis. The findings showed that the main applications of Artificial Intelligence and Machine Learning focus on bed occupancy prediction, automated staff scheduling, intelligent inventory management, fraud detection, claim denial prediction, administrative chatbots, and predictive models for appointment no-shows. Additionally, benefits related to operational efficiency, financial sustainability, and improvement of the patient administrative experience were identified. Conclusions. Artificial Intelligence and Machine Learning represent strategic tools for strengthening administrative management in healthcare institutions; however, their effective implementation requires technological interoperability, reinforcement of data-driven culture, and development of institutional digital competencies

keywords: Artificial Intelligence, Machine Learning, Healthcare Administration, Decision Making, Healthcare Institutions, Process Optimization

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How to Cite

Dazza Pineda, C. A., & Garzón Leon, F. A. (2026). From data to decision: systematic review of the role of artificial intelligence and machine learning in the optimization of the administrative management of Health Institutions. Biociencias, 9(1). https://doi.org/10.22490/26194759.11707

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