Smit Filip, Cuijpers Pim, Oostenbrink Jan, Batelaan Neeltje, de Graaf Ron, Beekman Aartjan
Trimbos Institute (Netherlands Institute of Mental Health and Addiction), P.O. Box 725, 2500 AS Utrecht, The Netherlands.
J Ment Health Policy Econ. 2006 Dec;9(4):193-200.
Mental disorders are highly prevalent and are associated with substantial disease burden, but their economic costs have been relatively less well researched. Moreover, few cost-of-illness studies used population-based psychiatric surveys for estimating direct medical, direct non-medical and indirect costs, and were able to do so for several well diagnosed mental disorders.
To calculate the cost of nine common mental disorders. The costs were calculated at individual level (per capita costs), and at population level per one million population for both prevalence (current cases) and incidence (new cases).
Data were derived from the Netherlands Mental Health Survey and Incidence Study (Nemesis), a population-based psychiatric cohort study among 5,504 adults in the age bracket of 18-65 years. DSM-III-R disorders were assessed with help of the Composite International Diagnostic Interview (CIDI). The costs of health service uptake, patients' out-of-pocket costs, and production losses were calculated for the reference year 2003. Robust regression methods, with 1,000 bootstrap replications, were used to estimate the excess costs of the distinct mental disorders and their 95% confidence intervals, while adjusting for physical illnesses and concurrent mental disorders in the regression equation.
The annual per capita excess costs of the mood disorders (5,009 euros) were higher than those of the anxiety disorders (3,587 euros) and alcohol-related disorders (1,431 euros). Being more prevalent, the excess costs of anxiety disorders are higher than those of mood disorders at population level. The annual influx of new cases (incidence) accounts for 39.2% of the costs at population level. It appeared that in the general population, in the productive age of 18-65 years, the bulk of the costs (85%) were related to production losses.
The study has some strengths and limitations. The data were derived from a large and representative population-based sample. Disorders were assessed with a reliable instrument. The costs were comprehensive in that they included direct medical, direct non-medical and indirect costs. The costs attributable to mental disorders were obtained with robust regression models while adjusting for the presence of somatic illnesses. For several reasons the costs figures must be seen as conservative lower bounds of the true costs. (i) People who were hospitalised were likely to be underrepresented in the sample, and it is well known that hospitalisation is one of the major cost drivers. (ii) Resource use was based on self-report, and this is likely to have resulted in underreporting. (iii) Work loss days were included in the analysis, but work cutback data were unavailable, while it is known that the costs due to work cutback can be substantial.
(i) The costs of mental disorders are comparable to those of physical illnesses. This throws some light on the allocation of budgets for research and development in mental versus physical illnesses. (ii) At population level a substantial part of the costs are caused by new cases, and this is a strong argument for strengthening the role of preventive psychiatry in public health with the aim to reduce incidence and avoid the future costs. (iii) In particular, reducing the incidence of major depression, panic disorder, agoraphobia and dysthymia should be considered as public health priorities, because these disorders are associated with substantial disability, and have, in addition, important economic ramifications. (iv) The bulk of the costs are due to production losses; this makes employers pertinent stakeholders in mental health promotion, and thoughts should be given to the question how to involve them more actively in health promotion. (v) It is well to emphasise that adoption of the above mentioned policies will require that first more prevention trials and cost-effectiveness studies are conducted in the selected disorders.
精神障碍极为普遍，且与巨大的疾病负担相关，但对其经济成本的研究相对较少。此外，很少有疾病成本研究使用基于人群的精神病学调查来估计直接医疗、直接非医疗和间接成本，并且能够针对几种诊断明确的精神障碍做到这一点。
计算九种常见精神障碍的成本。成本按个体水平（人均成本）计算，并按每百万人口的人群水平计算患病率（现患病例）和发病率（新发病例）。
数据来自荷兰精神健康调查与发病率研究（Nemesis），这是一项针对5504名18 - 65岁成年人的基于人群的精神病学队列研究。借助综合国际诊断访谈（CIDI）评估DSM - III - R障碍。计算了2003年参考年度的医疗服务使用成本、患者自付费用和生产损失。使用稳健回归方法，进行1000次自助重复抽样，来估计不同精神障碍的额外成本及其95%置信区间，同时在回归方程中对躯体疾病和并发精神障碍进行调整。
心境障碍的年度人均额外成本（5009欧元）高于焦虑障碍（3587欧元）和酒精相关障碍（1431欧元）。由于焦虑障碍更为普遍，在人群水平上其额外成本高于心境障碍。新发病例（发病率）的年度流入量占人群水平成本的39.2%。在18 - 65岁的劳动年龄普通人群中，大部分成本（85%）似乎与生产损失有关。
该研究有一些优点和局限性。数据来自一个大型且具有代表性的基于人群的样本。使用可靠的工具评估障碍。成本具有全面性，因为它们包括直接医疗、直接非医疗和间接成本。在对躯体疾病的存在进行调整的同时，通过稳健回归模型获得了归因于精神障碍的成本。由于几个原因，成本数字必须被视为真实成本的保守下限。（i）住院患者在样本中可能代表性不足，而且众所周知住院是主要成本驱动因素之一。（ii）资源使用基于自我报告，这可能导致报告不足。（iii）分析中包括了工作损失天数，但工作减少数据不可用，而众所周知因工作减少产生的成本可能很大。
（i）精神障碍的成本与躯体疾病的成本相当。这为精神疾病与躯体疾病研发预算的分配提供了一些启示。（ii）在人群水平上，很大一部分成本是由新发病例引起的，这有力地支持了加强预防性精神病学在公共卫生中的作用，以降低发病率并避免未来成本。（iii）特别是，将降低重度抑郁症、惊恐障碍、广场恐惧症和心境恶劣障碍的发病率视为公共卫生优先事项，因为这些障碍与严重残疾相关，此外还有重要的经济影响。（iv）大部分成本是由于生产损失；这使得雇主成为促进精神健康的相关利益者，应该思考如何让他们更积极地参与健康促进。（v）需要强调的是，要实施上述政策首先需要在选定的障碍中进行更多的预防试验和成本效益研究。
