Next Article in Journal
Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs
Previous Article in Journal
MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Data Science in the Management of Healthcare Organizations

1
LASI—Laboratório Associado de Sistemas Inteligentes, Centro Algoritmi, Universidade do Minho, Campus de Gualtar, Rua da Universidade, 4710-057 Braga, Portugal
2
IA&Saúde—Unidade de Investigação em Inteligência Artificial e Saúde, Instituto Politécnico de Saúde do Norte, CESPU, Rua José António Vidal, 81, 4760-409 Famalicão, Portugal
3
Departamento de Química e Bioquímica, Escola de Ciências e Tecnologia, Universidade de Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
4
LAQV REQUIMTE—Laboratório Associado para a Química Verde da Rede de Química e Tecnologia, Universidade de Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
*
Author to whom correspondence should be addressed.
Algorithms 2025, 18(3), 173; https://doi.org/10.3390/a18030173
Submission received: 1 March 2025 / Revised: 12 March 2025 / Accepted: 17 March 2025 / Published: 19 March 2025
(This article belongs to the Section Algorithms for Multidisciplinary Applications)

Abstract

The transformation of healthcare organizations is essential to address their inherent complexity and dynamic nature. This study emphasizes the role of Data Science, with the incorporation of Artificial Intelligence tools, in enabling data-driven and interconnected management strategies. To achieve this, a thermodynamic approach to Knowledge Representation and Reasoning was employed, capturing healthcare workers’ perceptions of their work environment through structured questionnaires. Over several months, the entropic efficiency in healthcare workers’ responses was analyzed, offering insights into the intricate relationships between leadership, teamwork, work engagement, and their influence on organizational performance and worker satisfaction. This approach demonstrates Data Science’s potential to enhance organizational effectiveness and adaptability while empowering healthcare workers. By bridging technological innovation with human-centric management, it provides actionable insights for sustainable improvements in healthcare systems. The study underscores that involving healthcare workers in decision-making processes not only could enhance satisfaction but also facilitate meaningful organizational transformation, creating more responsive and resilient healthcare organizations capable of navigating the complexities of modern healthcare.
Keywords: healthcare organizations; data science; healthcare workers; entropy; logical programming; knowledge representation and reasoning healthcare organizations; data science; healthcare workers; entropy; logical programming; knowledge representation and reasoning

Share and Cite

MDPI and ACS Style

Faria, P.; Alves, V.; Neves, J.; Vicente, H. Data Science in the Management of Healthcare Organizations. Algorithms 2025, 18, 173. https://doi.org/10.3390/a18030173

AMA Style

Faria P, Alves V, Neves J, Vicente H. Data Science in the Management of Healthcare Organizations. Algorithms. 2025; 18(3):173. https://doi.org/10.3390/a18030173

Chicago/Turabian Style

Faria, Pedro, Victor Alves, José Neves, and Henrique Vicente. 2025. "Data Science in the Management of Healthcare Organizations" Algorithms 18, no. 3: 173. https://doi.org/10.3390/a18030173

APA Style

Faria, P., Alves, V., Neves, J., & Vicente, H. (2025). Data Science in the Management of Healthcare Organizations. Algorithms, 18(3), 173. https://doi.org/10.3390/a18030173

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop