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Modelação e Simulação do modelo da gestão de consultas nos cuidados de saúde primários
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As atuais abordagens relativas à gestão de informação do utente são inadequadas para utentes com multimorbilidade, o que constitui uma barreira ao acesso à saúde. Além disso, considerando o aumento da população envelhecida, resulta num maior número de pessoas com problemas de saúde mais complexos, e, portanto, maior procura de serviços. É essencial que que os serviços de saúde consigam dar resposta às necessidades da população.
A presente dissertação consiste em usar a ciência da modelação e simulação (modelo de unidade de saúde) para compreender o impacto dos processos de gestão numa unidade de saúde e a importância da informação na tomada de decisão, com base em serviços digitais que usam grandes quantidades de dados, e refletir sobre o potencial do uso da Inteligência Artifi-cial (IA) para ajudar à otimização da gestão.
Como primeira abordagem do modelo e simulação, não foram consideradas algumas variáveis, e por isso, o modelo não foi suficientemente complexo, desta forma, não foi possível aplicar ferramentas de IA. Foi feita a análise dos dados obtidos e estes permitem concluir que, à medida que são aplicados níveis de variação superiores os tempos de espera aumentam, principalmente quando é aplicado o nível de variação A (alto) à chegada de utentes e à duração das consultas. A aplicação destes níveis teve um impacto significativo nos tempos de espera estudados. Estes realçam a importância de os utentes chegarem 15 minutos antes da hora mar-cada. Refletiu-se sobre os demais resultados e sobre a sua importância para apoiar os processos de decisão nos cuidados de doentes crónicos num contexto de transformação digital.
Seria interessante desenvolver, ainda mais, o modelo de modo que se inclua possíveis faltas de utentes e profissionais e atrasos aplicados aos próprios profissionais, no sentido de ser criada uma base de dados mais sólida incluindo mais variáveis. A integração da tecnologia da informação é particularmente importante e urgente na melhoria do tratamento médico nos cuidados de saúde primários. No entanto, ainda existem diversos obstáculos a serem supera-dos.
The current approaches to the management of patient information are inadequate for patients with multimorbidity, which constitutes a barrier in accessing healthcare. Further-more, with the increase of the aging population, it results in a greater number of people with more complex health problems, and therefore greater demand for services. It is essential that health services are able to respond to the needs of the population. This dissertation makes use of the science of modelling and simulation (model of healthcare center) to understand the impact of management processes in a healthcare center and the importance of information in decision making, based on digital services that use large amounts of data, and reflects on the potential use of Artificial Intelligence (AI) to help optimize management. As a first approach to the model and simulation, some variables were not considered, and therefore, the model was not complex enough, therefore, it was not possible to apply AI tools. The data obtained was analyzed and was concluded that, as higher levels of variation are applied, the waiting times increase, especially when the variation level A (high) is applied to the arrival of users and the duration of consultations. The application of these levels had a significant impact on the waiting times studied. These emphasize the importance of patients arriving 15 minutes before the scheduled time. Reflections were made on the other results and on their importance to support decision-making processes in the care of chronically ill patients in a context of digital transformation. It would be interesting to develop the model even further to include possible absences of users and professionals and delays applied to professionals themselves, in order to create a more solid database with the inclusion of more variables. The integration of information tech-nology is particularly important and urgent in the improvement of medical care in primary healthcare. However, there are still several obstacles to be overcome.
The current approaches to the management of patient information are inadequate for patients with multimorbidity, which constitutes a barrier in accessing healthcare. Further-more, with the increase of the aging population, it results in a greater number of people with more complex health problems, and therefore greater demand for services. It is essential that health services are able to respond to the needs of the population. This dissertation makes use of the science of modelling and simulation (model of healthcare center) to understand the impact of management processes in a healthcare center and the importance of information in decision making, based on digital services that use large amounts of data, and reflects on the potential use of Artificial Intelligence (AI) to help optimize management. As a first approach to the model and simulation, some variables were not considered, and therefore, the model was not complex enough, therefore, it was not possible to apply AI tools. The data obtained was analyzed and was concluded that, as higher levels of variation are applied, the waiting times increase, especially when the variation level A (high) is applied to the arrival of users and the duration of consultations. The application of these levels had a significant impact on the waiting times studied. These emphasize the importance of patients arriving 15 minutes before the scheduled time. Reflections were made on the other results and on their importance to support decision-making processes in the care of chronically ill patients in a context of digital transformation. It would be interesting to develop the model even further to include possible absences of users and professionals and delays applied to professionals themselves, in order to create a more solid database with the inclusion of more variables. The integration of information tech-nology is particularly important and urgent in the improvement of medical care in primary healthcare. However, there are still several obstacles to be overcome.
Descrição
Palavras-chave
Cuidados de Saúde Primários Doenças Crónicas Gestão de Informação Gestão de Serviços Modelação e Simulação