Determinación de las limitaciones para la implementación de modelos de Inteligencia Artificial en Cuidado Intensivo en un Hospital Universitario de Bogotá, Colombia
Thesis
Artificial Intelligence has an exponential growth in Health. Within the multiple medical specialties, Critical Care Medicine has been highlighted for its rapid growth and dynamic behavior. In the future, medical centers will not only be more specialized, but also more technological. Therefore, the implementation of Artificial Intelligence models is important, however, for this it is key to determine the possible limitations to propose implementation strategies that allow not only the optimization of processes, but also of resources. For the development of this document, a cross-sectional, quantitative analytical study was carried out by applying an online survey to professionals related to intensive care in one of the university hospitals in Bogotá, Colombia. 119 health professionals who work in the intensive care area participated in this survey. Of the total number of participants, 31% were nurses, 18.4% medical specialists, and 15.9% medical graduates in specialized training. 8.4% of the participants were biomedical engineers. 72.3% of those surveyed responded that they felt grateful to the concept of artificial intelligence, 52.9% considered themselves with an affinity towards engineering and 58.8% stated that they were aware of the application of artificial intelligence in the ICU. 70% of the respondents agreed that the future of health care will be characterized by a combination of humans and AI and of the total 80% of the participants agreed with the possible benefit of the implementation of intelligence artificial in all areas of clinical practice. It is clear that health professionals within the ICU are the most sought after for knowledge in the technological area. Therefore, it is necessary to work on educating in concepts of artificial intelligence and possible uses in biomedical engineering in the ICU setting, emphasizing that it is a tool and does not replace the worker. Additionally, for health institutions it will be key to have teams of professionals and technicians with training in biomedical engineering or to seek advice from a specialized external team.
