Data Science in the Management of Healthcare Organizations
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 t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/18/3/173 |
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| author | Pedro Faria Victor Alves José Neves Henrique Vicente |
| author_facet | Pedro Faria Victor Alves José Neves Henrique Vicente |
| author_sort | Pedro Faria |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ffd41045204f4d7a851b78136dc534f0 |
| institution | OA Journals |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-ffd41045204f4d7a851b78136dc534f02025-08-20T02:11:11ZengMDPI AGAlgorithms1999-48932025-03-0118317310.3390/a18030173Data Science in the Management of Healthcare OrganizationsPedro Faria0Victor Alves1José Neves2Henrique Vicente3LASI—Laboratório Associado de Sistemas Inteligentes, Centro Algoritmi, Universidade do Minho, Campus de Gualtar, Rua da Universidade, 4710-057 Braga, PortugalLASI—Laboratório Associado de Sistemas Inteligentes, Centro Algoritmi, Universidade do Minho, Campus de Gualtar, Rua da Universidade, 4710-057 Braga, PortugalLASI—Laboratório Associado de Sistemas Inteligentes, Centro Algoritmi, Universidade do Minho, Campus de Gualtar, Rua da Universidade, 4710-057 Braga, PortugalLASI—Laboratório Associado de Sistemas Inteligentes, Centro Algoritmi, Universidade do Minho, Campus de Gualtar, Rua da Universidade, 4710-057 Braga, PortugalThe 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.https://www.mdpi.com/1999-4893/18/3/173healthcare organizationsdata sciencehealthcare workersentropylogical programmingknowledge representation and reasoning |
| spellingShingle | Pedro Faria Victor Alves José Neves Henrique Vicente Data Science in the Management of Healthcare Organizations Algorithms healthcare organizations data science healthcare workers entropy logical programming knowledge representation and reasoning |
| title | Data Science in the Management of Healthcare Organizations |
| title_full | Data Science in the Management of Healthcare Organizations |
| title_fullStr | Data Science in the Management of Healthcare Organizations |
| title_full_unstemmed | Data Science in the Management of Healthcare Organizations |
| title_short | Data Science in the Management of Healthcare Organizations |
| title_sort | data science in the management of healthcare organizations |
| topic | healthcare organizations data science healthcare workers entropy logical programming knowledge representation and reasoning |
| url | https://www.mdpi.com/1999-4893/18/3/173 |
| work_keys_str_mv | AT pedrofaria datascienceinthemanagementofhealthcareorganizations AT victoralves datascienceinthemanagementofhealthcareorganizations AT joseneves datascienceinthemanagementofhealthcareorganizations AT henriquevicente datascienceinthemanagementofhealthcareorganizations |