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Opinions Related to the Potential Application of Artificial Intelligence (AI) by the Responsible in Charge of the Administrative Management Related to the Logistics and Supply Chain of Medical Stock in Health Centers in North of Chile
The research evaluated the opinion of those in charge of the administrative management of the logistics and supply chain of medical and pharmaceutical stocks of health care centers in the north of Chile and a potential improvement of their operations through the use of artificial intelligence (AI)....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048829/ https://www.ncbi.nlm.nih.gov/pubmed/36981748 http://dx.doi.org/10.3390/ijerph20064839 |
Sumario: | The research evaluated the opinion of those in charge of the administrative management of the logistics and supply chain of medical and pharmaceutical stocks of health care centers in the north of Chile and a potential improvement of their operations through the use of artificial intelligence (AI). The identification of the problem arose from the empirical analysis, where serious deficiencies in the manual handling and management of the stock of medicines and hospital supplies were evidenced. This deficiency does not allow a timely response to the demand of the logistics and supply chain, causing stock ruptures in health centers. Based on this finding, we asked ourselves how AI was observed as the most efficient tool to solve this difficulty. The results were obtained through surveys of personnel in charge of hospital and pharmacy supplies. The questions focused on the level of training, seniority in positions related to the problem, knowledge of regulations, degree of innovation in the procedures used in logistics and supply chain and procurement. However, a very striking fact was related to the importance of the use of AI, where, very surprisingly, 64.7% considered that it would not help to reduce human errors generated in the areas analyzed. |
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