Dooley Mary, Simpson Annie N, Nietert Paul J, Williams Dunc, Simpson Kit N
Departments of Health Science and Research and Healthcare Leadership and Management, College of Health Professions, Medical University of South Carolina, Charleston, USA.
Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, USA.
Health Serv Outcomes Res Methodol. 2021;21(1):131-144. doi: 10.1007/s10742-020-00233-5. Epub 2021 Jan 7.
As healthcare costs continue to increase, studies assessing costs are becoming increasingly common, but researchers planning for studies that measure costs differences (savings) encounter a lack of literature or consensus among researchers on what constitutes "small" or "large" cost savings for common measures of resource use. Other fields of research have developed approaches to solve this type of problem. Researchers measuring improvement in quality of life or clinical assessments have defined minimally important differences (MID) which are then used to define magnitudes when planning studies. Also, studies that measure cost effectiveness use benchmarks, such as cost/QALY, but do not provide benchmarks for cost differences. In a review of the literature, we found no publications identifying indicators of magnitude for costs. However, the literature describes three approaches used to identify minimally important outcome differences: (1) anchor-based, (2) distribution-based, and (3) a consensus-based Delphi methods. In this exploratory study, we used these three approaches to derive MID for two types of resource measures common in costing studies for: (1) hospital admissions (high cost); and (2) clinic visits (low cost). We used data from two (unpublished) studies to implement the MID estimation. Because the distributional characteristics of cost measures may require substantial samples, we performed power analyses on all our estimates to illustrate the effect that the definitions of "small" and "large" costs may be expected to have on power and sample size requirements for studies. The anchor-based method, while logical and simple to implement, may be of limited value in cases where it is difficult to identify appropriate anchors. We observed some commonalities and differences for the distribution and consensus-based approaches, which require further examination. We recommend that in cases where acceptable anchors are not available, both the Delphi and the distribution-method of MID for costs be explored for convergence.
随着医疗成本持续上升，评估成本的研究越来越普遍，但计划开展衡量成本差异（节省情况）研究的人员发现，在研究人员中，对于常见资源使用衡量指标而言，什么构成“小”或“大”的成本节省，缺乏相关文献或共识。其他研究领域已开发出解决这类问题的方法。衡量生活质量改善情况或临床评估的研究人员定义了最小重要差异（MID），然后在规划研究时用其来界定差异程度。此外，衡量成本效益的研究使用成本效益比等基准，但未提供成本差异的基准。在文献综述中，我们未发现确定成本差异程度指标的出版物。然而，文献描述了三种用于确定最小重要结果差异的方法：（1）基于锚定的方法；（2）基于分布的方法；（3）基于共识的德尔菲法。在这项探索性研究中，我们使用这三种方法得出了成本核算研究中常见的两种资源衡量指标的MID：（1）住院（高成本）；（2）门诊就诊（低成本）。我们使用两项（未发表）研究的数据来进行MID估计。由于成本衡量指标的分布特征可能需要大量样本，我们对所有估计值进行了功效分析，以说明“小”和“大”成本定义可能对研究的功效和样本量要求产生的影响。基于锚定的方法虽然逻辑清晰且易于实施，但在难以确定合适锚定的情况下可能价值有限。我们观察到基于分布和基于共识的方法存在一些共性和差异，需要进一步研究。我们建议，在无法获得可接受的锚定的情况下，探索德尔菲法和基于分布的成本MID方法以实现趋同。
