Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Jevdjevic, Milica, Listl, Stefan, Beeson, Morgan, Rovers, Maroeska, Matsuyama, Yusuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
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
_version_ 1783716435439124480
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
work_keys_str_mv AT jevdjevicmilica forecastingfuturedentalhealthexpendituresdevelopmentofaframeworkusingdatafrom32oecdcountries
AT listlstefan forecastingfuturedentalhealthexpendituresdevelopmentofaframeworkusingdatafrom32oecdcountries
AT beesonmorgan forecastingfuturedentalhealthexpendituresdevelopmentofaframeworkusingdatafrom32oecdcountries
AT roversmaroeska forecastingfuturedentalhealthexpendituresdevelopmentofaframeworkusingdatafrom32oecdcountries
AT matsuyamayusuke forecastingfuturedentalhealthexpendituresdevelopmentofaframeworkusingdatafrom32oecdcountries