Demand forecast in the emergency department in Minas Gerais, Brazil

• Autor(a) principal: de Brito, Franciele Guimarães
• Data de Publicação: 2019
• Outros Autores: Resende, Elmiro Santos, Rodrigues, Aurélia Aparecida de Araújo, Junqueira, Marcelle Aparecida Barros, Barreto, Vívian Ribeiro, Destro Filho, João Batista
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Bioscience journal (Online)
• Texto Completo: https://seer.ufu.br/index.php/biosciencejournal/article/view/46115
• topic: Triage.; Health service needs and demands.; Public health.; Health Sciences

This study presents a mathematical model to carry out the demand forecasts in relation to patientes classified as green in the emergency department of a municipality in Minas Gerais, Brazil. In addition, another approach will investigate whether the green patients demand remains the same over the weekend, as compared to the weekdays, since there is no support from Primary Health Care units over the weekend. A retrospective study of the emergency service in the municipality of Monte Carmelo was carried out from January 2014 to December 2017.The time series of the patients classified as green during the host by the nurse, according to the Manchester Triage Scale, was analyzed in the temporal domain for the construction of a parametric model with the purpose of realizing the demand forecast. The Manchester Triage Scale has been adopted in most emergency department as a guiding instrument for risk classification, prioritizing the most serious cases. The data processing was fulfilled using Software R Version 3.4. The ARIMA model (1,1,1) presented a better fit for this forecast. The predictions of this model are values close to those observed for the number of patients seen that ranges from 1780.4 to 1796.6 patients per month. In relation to the demand of patients classified as green at the weekend, it has shown that it is slightly lower than the weekend, but it is still an expressive demand. The application of the models must be seen by the managers as a tool to aid decisions, thus it must support processes of planning, management and evaluation of public policies. In this context, mathematical models for demand forecasting are an instrument for management care and services.