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Forecasting health expenditures in Iran using the ARIMA model (2016-2020)
Background: Accurate economic forecast has important effects on governmental policy and economic planning, and it can help policymakers to make decisions for future and create new infrastructures for the development of new forecasting methods. This study calculated total health expenditure, public h...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Iran University of Medical Sciences
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662543/ https://www.ncbi.nlm.nih.gov/pubmed/31380315 http://dx.doi.org/10.34171/mjiri.33.25 |
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author | Ramezanian, Maryam Haghdoost, Ali Akbar Mehrolhassani, Mohammad Hossein Abolhallaje, Masoud Dehnavieh, Reza Najafi, Behzad Fazaeli, Ali Akbar |
author_facet | Ramezanian, Maryam Haghdoost, Ali Akbar Mehrolhassani, Mohammad Hossein Abolhallaje, Masoud Dehnavieh, Reza Najafi, Behzad Fazaeli, Ali Akbar |
author_sort | Ramezanian, Maryam |
collection | PubMed |
description | Background: Accurate economic forecast has important effects on governmental policy and economic planning, and it can help policymakers to make decisions for future and create new infrastructures for the development of new forecasting methods. This study calculated total health expenditure, public health expenditure and out of pocket (OOP) payment for 2016-2020. Methods: Autoregressive Integrated Moving Average Process (ARIMA) is one of the most important forecasting models. In this study, five-year values were forecasted using EViews8 software according to health expenditures in Iran from 1971 to 2015. Results: Applying annual data for total health expenditure, resulted in the ARIMA (1,1,1) model being the most appropriate to predict these costs. The results of this study indicate that total health expenditures will reach from about 1228338 billion IRR in 2016 to 2698346 billion IRR in 2020 and the amount of out of pocket (OOP) will become more than 41% of total health expenditure in 2020. Conclusion: Total health expenditures in 2020 will become more than two halves in 2016. These expenditures indicated there is a need for continued governmental support of this sector during the upcoming years. |
format | Online Article Text |
id | pubmed-6662543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Iran University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-66625432019-08-02 Forecasting health expenditures in Iran using the ARIMA model (2016-2020) Ramezanian, Maryam Haghdoost, Ali Akbar Mehrolhassani, Mohammad Hossein Abolhallaje, Masoud Dehnavieh, Reza Najafi, Behzad Fazaeli, Ali Akbar Med J Islam Repub Iran Original Article Background: Accurate economic forecast has important effects on governmental policy and economic planning, and it can help policymakers to make decisions for future and create new infrastructures for the development of new forecasting methods. This study calculated total health expenditure, public health expenditure and out of pocket (OOP) payment for 2016-2020. Methods: Autoregressive Integrated Moving Average Process (ARIMA) is one of the most important forecasting models. In this study, five-year values were forecasted using EViews8 software according to health expenditures in Iran from 1971 to 2015. Results: Applying annual data for total health expenditure, resulted in the ARIMA (1,1,1) model being the most appropriate to predict these costs. The results of this study indicate that total health expenditures will reach from about 1228338 billion IRR in 2016 to 2698346 billion IRR in 2020 and the amount of out of pocket (OOP) will become more than 41% of total health expenditure in 2020. Conclusion: Total health expenditures in 2020 will become more than two halves in 2016. These expenditures indicated there is a need for continued governmental support of this sector during the upcoming years. Iran University of Medical Sciences 2019-04-01 /pmc/articles/PMC6662543/ /pubmed/31380315 http://dx.doi.org/10.34171/mjiri.33.25 Text en © 2019 Iran University of Medical Sciences http://creativecommons.org/licenses/by-nc-sa/1.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial-ShareAlike 1.0 License (CC BY-NC-SA 1.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly. |
spellingShingle | Original Article Ramezanian, Maryam Haghdoost, Ali Akbar Mehrolhassani, Mohammad Hossein Abolhallaje, Masoud Dehnavieh, Reza Najafi, Behzad Fazaeli, Ali Akbar Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title | Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title_full | Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title_fullStr | Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title_full_unstemmed | Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title_short | Forecasting health expenditures in Iran using the ARIMA model (2016-2020) |
title_sort | forecasting health expenditures in iran using the arima model (2016-2020) |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662543/ https://www.ncbi.nlm.nih.gov/pubmed/31380315 http://dx.doi.org/10.34171/mjiri.33.25 |
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