Spatial distribution of patients served in the emergency of a tertiary hospital

• Autor(a) principal: Damasceno Brito, Odézio
• Data de Publicação: 2020
• Outros Autores: Albuquerque Brandão, Maria Girlane Sousa, Brioso Bastos, Ismael, Galindo Neto, Nelson Miguel, Áfio Caetano, Joselany, Moreira Barros, Lívia
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: HU Revista (Online)
• Texto Completo: https://periodicos.ufjf.br/index.php/hurevista/article/view/30138
• topic: Spatial Analysis; Emergencies; Emergency Hospital Service; Emergency Identification; Health Service Needs and Demands; Análise Espacial; Emergências; Serviço Hospitalar de Emergência; Identificação da Emergência; Necessidades e Demandas de Serviços de Saúde

Introduction: In practice and research, the use of technologies that assist the work of professionals, such as geoprocessing, is increasingly present, useful for investigating spatial variables of a given phenomenon, when searching for data, using geostatistical tools. Objective: To analyze the spatial distribution of patients seen in the emergency department of a tertiary hospital. Material and Methods: Cross-sectional study, carried out from July to September 2017, in the emergency of a tertiary hospital, with 783 care records/medical records. The spatial analysis was performed with the Quantum GIS 2.18.10 software. Results: Most of the consultations were male (63,9%), with an average age of 52 years. Those from the surrounding cities (75,6%) had a risk classification, predominantly, in yellow and red, while the classification in green and yellow prevailed among patients in the same municipality where the hospital was located. The visits were made to patients from the northern region of the state of Ceará, with greater density in the municipalities of the Sobral macro-region, however, there were visits to patients from Fortaleza and the state's backlands. Conclusion: The spatial distribution points out that the emergency department visits covered patients from the north of the state of Ceará, the hinterland and the metropolitan region of the state capital. The attendance density and risk classification in blue and green colors were directly proportional to the geographical proximity to the hospital, while the yellow and red colors had an inversely proportional relationship with such distance.