alexa Abstract | The modelling of time-series and the evaluation of forecasts for the future: the case of the number of persons per physician in turkey between 1928 and 2010

Biomedical Research
Open Access

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Objectives: Health professionals are very important for improving the health status of the society and maintaining a healthy life. The aim of the present study is to model the number of persons per physician via Box-Jenkins and exponential smoothing methods and trend models, to compare these models, and to make estimations for the future. ARIMA or Box-Jenkins models are the combinations of AR and MA models administered to the series differenced at degree d.

Methods: The research material consists of data regarding the number of persons per physician between 1928 and 2010. The data were obtained from STATISTICAL INDICATORS Journal published by the Turkish Statistical Institute. 1928-2010 the number of persons per physician data ARIMA, exponential smoothing, and then modeled by Moving Average methods for future studies (2020) model performance is evaluated.

Results: The goodness of fit criteria of the relevant models. It is seen that the ARIMA (0,1,0) model has the best values except for Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE), but it is the Holt model which has lower mean error.

Conclusion: All administrative works and functions such as planning, organization, management, and rearrangement of healthcare services should be based on the data/evidence to be provided by this institution. Likewise, the problems and effects of healthcare services should be evaluated based on the data of this institution.

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Author(s): Mustafa Agah Tekindal zlem Gll Ayse Canan Yazici Yasemin Yavuz


Time series, Forecasting consistency, ARIMA models, Exponential smoothing methods, Estimation trend., #

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