De los datos a la decisión: Inteligencia Artificial y Machine Learning en la gestión administrativa en salud

Claudia Angelica Dazza Pineda; Fabian Armando Garzón Leon

doi:10.22490/26194759.11901

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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III.METASALUD

From data to decision: artificial intelligence and machine learning in administrative management in healthcare

DOI: https://doi.org/10.22490/26194759.11901

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 (AI) and Machine Learning (ML) in optimizing the administrative management of Health Institutions, identifying their main applications, benefits, and challenges for data-driven decision-making. Method. A systematic literature review was conducted following the PRISMA 2020 guidelines, drawing on the PubMed, Scopus, SciELO, and Web of Science databases, considering publications between 2016 and 2025. 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 main applications identified were bed occupancy prediction, automated staff scheduling, intelligent inventory management, fraud detection, claim denial prediction, administrative chatbots, and predictive models for appointment no-shows. Conclusions. AI and ML represent strategic tools for strengthening administrative management in healthcare institutions; however, their effective implementation requires technological interoperability, a solid data culture, and the 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: artificial intelligence and machine learning in administrative management in healthcare. Biociencias, 9(1). https://doi.org/10.22490/26194759.11901

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