Jevdjevic Milica, Listl Stefan, Beeson Morgan, Rovers Maroeska, Matsuyama Yusuke
Department of Dentistry - Quality and Safety of Oral Healthcare, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands.
Department of Conservative Dentistry, Translational Health Economics Group, Heidelberg University, Heidelberg, Germany.
Community Dent Oral Epidemiol. 2021 Jun;49(3):256-266. doi: 10.1111/cdoe.12597. Epub 2020 Nov 30.
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.
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.
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).
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.
（1）利用现有信息建立一个预测未来牙科支出的框架；（2）识别相关研究和数据缺口，以便未来能够不断改进牙科支出预测。
我们的分析聚焦于32个经合组织国家。根据预测变量的数量，我们采用了具有不同模型规格的动态单变量和多变量建模方法。对于单变量建模，采用自回归（AR）动态模型纳入牙科支出的历史趋势。多变量建模考虑了历史趋势，以及牙科支出、牙科发病率、国内生产总值（GDP）方面的经济增长和人口变化之间的关系。
不同模型规格下牙科支出的估计差异很大。无论规格如何，将牙科发病率作为预测变量之一的模型表现最差。使用最佳拟合模型规格，即单变量二阶自回归[AR(2)]，2020年32个经合组织国家的预测牙科支出为3160亿美元（95%预测区间，FI：258 - 387），2030年为4340亿美元（95%FI：354 - 532），2040年为5940亿美元（95%FI：485 - 728）。预计2040年人均支出在德国最高（889美元，95%FI：726 - 1090），在墨西哥最低（52美元，95%FI：42 - 64）。
本研究证明了预测牙科支出的可行性和挑战，并可为改进更具可持续性和弹性的卫生政策及资源规划提供基础。在现有数据源的限制范围内，我们的研究结果表明，经合组织国家的牙科支出在未来二十年可能大幅增加，且各国之间差异很大。为了进行更准确的估计并更好地理解牙科支出的决定因素，迫切需要关于牙科支出和牙科发病率的更全面数据。
