Prediction of house calls in primary care
a time series approach using the ARIMA model
DOI:
https://doi.org/10.5712/rbmfc17(44)3012Keywords:
Needs Assessment, Primary Health Care, House Calls, Forecasting.Abstract
Introduction: A new profile of demand for Brazil's public healthcare – Sistema Único de Saúde (SUS), is expected in the coming years, due to population-aging and increased prevalence of chronic diseases. Thus, it is necessary to use tools for planning the responsiveness of health services. Models for time series analysis such as the AutoRegressive Integrated Moving Average (ARIMA), can be useful. Objective: The aim of the study is to estimate the demand for home visits in Primary Health Care (PHC) of SUS, in Florianópolis (SC). Methods: Ecological study of time series using ARIMA for projections. Home visits carried out by the PHC, recorded in the electronic medical record of the Municipal Health Department, from January 2015 to February 2019 were used. Results: The forecast points to a maximum of 702 visits in August 2019, followed by a drop to 573 visits in December 2019, and subsequent recovery, with an estimate of 632 for October 2020. The forecast for each Health Center indicated variations in demand between units with the same number of Family Health Teams, between 11.3 to 1.3 visits/FHT, in the 20th month. Conclusions: ARIMA made it possible to carry out projections of home visits in the municipality, indicating a drop in the demand for home visits. The method can be of great value for the projection of other demands in the same municipality or in other municipalities that have historical series data. Future studies can expand the analysis in this regard, as well as compare ARIMA with models such as exponential smoothing.
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