Department Orthopaedics, University Medical Center Utrecht, Utrecht, Netherlands.
BMC Health Serv Res. 2010 Mar 23;10:75. doi: 10.1186/1472-6963-10-75.
Implementation of medical interventions may vary with organization and available capacity. The influence of this source of variability on the cost-effectiveness can be evaluated by computer simulation following a carefully designed experimental design. We used this approach as part of a national implementation study of ultrasonographic infant screening for developmental dysplasia of the hip (DDH).
First, workflow and performance of the current screening program (physical examination) was analyzed. Then, experimental variables, i.e., relevant entities in the workflow of screening, were defined with varying levels to describe alternative implementation models. To determine the relevant levels literature and interviews among professional stakeholders are used. Finally, cost-effectiveness ratios (inclusive of sensitivity analyses) for the range of implementation scenarios were calculated.
The four experimental variables for implementation were: 1) location of the consultation, 2) integrated with regular consultation or not, 3) number of ultrasound machines and 4) discipline of the screener. With respective numbers of levels of 3,2,3,4 in total 72 possible scenarios were identified. In our model experimental variables related to the number of available ultrasound machines and the necessity of an extra consultation influenced the cost-effectiveness most.
Better information comes available for choosing optimised implementation strategies where organizational and capacity variables are important using the combination of simulation models and an experimental design. Information to determine the levels of experimental variables can be extracted from the literature or directly from experts.
医疗干预措施的实施可能因组织和可用能力而异。通过精心设计的实验设计进行计算机模拟，可以评估这种变异性来源对成本效益的影响。我们在一项全国性的超声婴儿髋关节发育不良（DDH）筛查实施研究中使用了这种方法。
首先，分析了当前筛查计划（体格检查）的工作流程和性能。然后，定义了实验变量，即筛查工作流程中的相关实体，并设置了不同的水平，以描述替代实施模型。为了确定相关水平，我们使用了文献和专业利益相关者的访谈。最后，计算了实施范围内的成本效益比（包括敏感性分析）。
实施的四个实验变量为：1）咨询地点，2）是否与常规咨询相结合，3）超声机数量和 4）筛查人员的专业。总共有 72 种可能的方案，各自的水平数分别为 3、2、3、4。在我们的模型中，与可用超声机数量和额外咨询必要性相关的实验变量对成本效益的影响最大。
通过模拟模型和实验设计的结合，可以更好地了解组织和能力变量重要的优化实施策略选择，从而获得更好的信息。可以从文献或直接从专家那里提取确定实验变量水平的信息。
