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Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries
OBJECTIVE: To (1) develop a framework for forecasting future dental expenditures, using currently available information, and (2) identify relevant research and data gaps such that dental expenditure predictions can continuously be improved in the future. METHODS: Our analyses focused on 32 OECD coun...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247018/ https://www.ncbi.nlm.nih.gov/pubmed/33252147 http://dx.doi.org/10.1111/cdoe.12597 |
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author | Jevdjevic, Milica Listl, Stefan Beeson, Morgan Rovers, Maroeska Matsuyama, Yusuke |
author_facet | Jevdjevic, Milica Listl, Stefan Beeson, Morgan Rovers, Maroeska Matsuyama, Yusuke |
author_sort | Jevdjevic, Milica |
collection | PubMed |
description | OBJECTIVE: To (1) develop a framework for forecasting future dental expenditures, using currently available information, and (2) identify relevant research and data gaps such that dental expenditure predictions can continuously be improved in the future. METHODS: Our analyses focused on 32 OECD countries. Dependent on the number of predictors, we employed dynamic univariate and multivariate modelling approaches with various model specifications. For univariate modelling, an auto‐regressive (AR) dynamic model was employed to incorporate historical trends in dental expenditures. Multivariate modelling took account of historical trends, as well as of relationships between dental expenditures, dental morbidity, economic growth in terms of gross domestic product and demographic changes. RESULTS: Estimates of dental expenditures varied substantially across different model specifications. Models relying on dental morbidity as one of the predictors performed worst regardless of their specification. Using the best‐fitted model specification, that is the univariate second‐order autoregression [AR(2)], the forecasted dental expenditures across 32 OECD countries amounted to US$316bn (95% forecasted interval, FI: 258‐387) in 2020, US$434bn (95%FI: 354‐532) in 2030 and US$594bn (95%FI: 485‐728) in 2040. Per capita spending in 2040 was forecasted to be highest in Germany (US$889, 95%FI: 726‐1090) and lowest in Mexico (US$52, 95%FI: 42‐64). CONCLUSIONS: The present study demonstrates the feasibility and challenges in predicting dental expenditures and can serve as a basis for improvement towards more sustainable and resilient health policy and resource planning. Within the limitations of available data sources, our findings suggest that dental expenditures in OECD countries could increase substantially over the next two decades and vary considerably across countries. For more accurate estimation and a better understanding of determinants of dental expenditures, more comprehensive data on dental spending and dental morbidity are urgently needed. |
format | Online Article Text |
id | pubmed-8247018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82470182021-07-02 Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries Jevdjevic, Milica Listl, Stefan Beeson, Morgan Rovers, Maroeska Matsuyama, Yusuke Community Dent Oral Epidemiol Original Articles OBJECTIVE: To (1) develop a framework for forecasting future dental expenditures, using currently available information, and (2) identify relevant research and data gaps such that dental expenditure predictions can continuously be improved in the future. METHODS: Our analyses focused on 32 OECD countries. Dependent on the number of predictors, we employed dynamic univariate and multivariate modelling approaches with various model specifications. For univariate modelling, an auto‐regressive (AR) dynamic model was employed to incorporate historical trends in dental expenditures. Multivariate modelling took account of historical trends, as well as of relationships between dental expenditures, dental morbidity, economic growth in terms of gross domestic product and demographic changes. RESULTS: Estimates of dental expenditures varied substantially across different model specifications. Models relying on dental morbidity as one of the predictors performed worst regardless of their specification. Using the best‐fitted model specification, that is the univariate second‐order autoregression [AR(2)], the forecasted dental expenditures across 32 OECD countries amounted to US$316bn (95% forecasted interval, FI: 258‐387) in 2020, US$434bn (95%FI: 354‐532) in 2030 and US$594bn (95%FI: 485‐728) in 2040. Per capita spending in 2040 was forecasted to be highest in Germany (US$889, 95%FI: 726‐1090) and lowest in Mexico (US$52, 95%FI: 42‐64). CONCLUSIONS: The present study demonstrates the feasibility and challenges in predicting dental expenditures and can serve as a basis for improvement towards more sustainable and resilient health policy and resource planning. Within the limitations of available data sources, our findings suggest that dental expenditures in OECD countries could increase substantially over the next two decades and vary considerably across countries. For more accurate estimation and a better understanding of determinants of dental expenditures, more comprehensive data on dental spending and dental morbidity are urgently needed. John Wiley and Sons Inc. 2020-11-30 2021-06 /pmc/articles/PMC8247018/ /pubmed/33252147 http://dx.doi.org/10.1111/cdoe.12597 Text en © 2020 The Authors. Community Dentistry and Oral Epidemiology Published by John Wiley & Sons Ltd https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Jevdjevic, Milica Listl, Stefan Beeson, Morgan Rovers, Maroeska Matsuyama, Yusuke Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title | Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title_full | Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title_fullStr | Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title_full_unstemmed | Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title_short | Forecasting future dental health expenditures: Development of a framework using data from 32 OECD countries |
title_sort | forecasting future dental health expenditures: development of a framework using data from 32 oecd countries |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247018/ https://www.ncbi.nlm.nih.gov/pubmed/33252147 http://dx.doi.org/10.1111/cdoe.12597 |
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