Welte Robert, Feenstra Talitha, Jager Hans, Leidl Reiner
Institute of Health Economics and Health Care Management (IGM), GSF National Research Center for Environment and Health, Neuherberg, Germany.
Pharmacoeconomics. 2004;22(13):857-76. doi: 10.2165/00019053-200422130-00004.
To develop a user-friendly tool for managing the transfer of economic evaluation results.
Factors that may influence the transfer of health economic study results were systematically identified and the way they impact on transferability was investigated. A transferability decision chart was developed that includes: knock-out criteria; a checklist based on the transferability factors; and methods for improving transferability and for assessing the uncertainty of transferred results. This approach was tested on various international cost-effectiveness studies in the areas of interventional cardiology, vaccination and screening.
The transfer of study results is possible pending the outcomes of the transferability check and necessary adjustments. Transferability factors can be grouped into areas of methodological, healthcare system and population characteristics. Different levels of effort are required for analysis of factors, ranging from very low (e.g. discount rate) to very high (e.g. practice variation). The impact of differences of most transferability factors can be estimated via the key health economic determinants: capacity utilisation, effectiveness, productivity loss and returns to scale. Depending on the outcomes of the transferability check a correction of the study results for inflation and for differences related to currencies or purchasing power might be sufficient. Otherwise, modelling-based adjustments might be necessary, requiring the (re-)building and sometimes structural modification of the study model. For determination of the most essential adjustments, a univariate sensitivity analysis seems appropriate. If not all relevant study parameters can be substituted with country-specific ones, multivariate or probabilistic sensitivity analysis seems to be a promising way to quantify the uncertainty associated with a transfer. If study results cannot be transferred, the transfer of study models or designs should be investigated as this can significantly save time when conducting a new study.
Our transferability decision chart is a transparent and user-friendly tool for assessing and improving the transferability of economic evaluation results. A state of the art description of the methodology in a study, providing detailed components for calculation, is not only essential for determining its transferability but also for improving it via modelling adjustments.
开发一种便于用户使用的工具,用于管理经济评估结果的转化。
系统识别可能影响卫生经济研究结果转化的因素,并研究其对可转化性的影响方式。制定了一份可转化性决策图,其中包括:淘汰标准;基于可转化性因素的清单;以及提高可转化性和评估转化结果不确定性的方法。该方法在介入心脏病学、疫苗接种和筛查等领域的各种国际成本效益研究中进行了测试。
在可转化性检查结果及必要调整完成之前,研究结果的转化是可行的。可转化性因素可分为方法学、医疗保健系统和人群特征等领域。分析这些因素所需的工作量各不相同,从非常低(如贴现率)到非常高(如实践差异)。大多数可转化性因素差异的影响可通过关键卫生经济决定因素进行估计:产能利用、有效性、生产率损失和规模收益。根据可转化性检查结果,对研究结果进行通货膨胀以及与货币或购买力相关差异的校正可能就足够了。否则,可能需要基于模型的调整,这需要(重新)构建研究模型,有时还需要进行结构修改。为了确定最必要的调整,单变量敏感性分析似乎是合适的。如果并非所有相关研究参数都可以用特定国家的参数替代,多变量或概率敏感性分析似乎是量化与转化相关不确定性的一种有前景的方法。如果研究结果无法转化,应研究研究模型或设计的转化,因为这在开展新研究时可显著节省时间。
我们的可转化性决策图是一种用于评估和提高经济评估结果可转化性的透明且便于用户使用的工具。研究中对方法学的最新描述,提供详细的计算组成部分,不仅对于确定其可转化性至关重要,而且对于通过模型调整来改进它也至关重要。