Röder Christoph, Staub L, Dietrich D, Zweig T, Melloh M, Aebi M
MEM Research Center for Orthopaedic Surgery, Institute for Evaluative Research in Orthopaedic Surgery, University of Bern, Stauffacherstrasse 78, 3014 Bern, Switzerland.
Eur Spine J. 2009 Aug;18 Suppl 3(Suppl 3):305-11. doi: 10.1007/s00586-009-0943-7. Epub 2009 Apr 1.
The newly released online statistics function of Spine Tango allows comparison of own data against the aggregated results of the data pool that all other participants generate. This comparison can be considered a very simple way of benchmarking, which means that the quality of what one organization does is compared with other similar organizations. The goal is to make changes towards better practice if benchmarking shows inferior results compared with the pool. There are, however, pitfalls in this simplified way of comparing data that can result in confounding. This means that important influential factors can make results appear better or worse than they are in reality and these factors can only be identified and neutralized in a multiple regression analysis performed by a statistical expert. Comparing input variables, confounding is less of a problem than comparing outcome variables. Therefore, the potentials and limitations of automated online comparisons need to be considered when interpreting the results of the benchmarking procedure.
Spine Tango新发布的在线统计功能允许将自身数据与所有其他参与者生成的数据池汇总结果进行比较。这种比较可被视为一种非常简单的基准测试方式,即一个组织的工作质量与其他类似组织进行比较。目标是如果基准测试显示与数据池相比结果较差,就朝着更好的实践进行改进。然而,这种简化的数据比较方式存在一些可能导致混淆的陷阱。这意味着重要的影响因素可能使结果看起来比实际情况更好或更差,而这些因素只能在统计专家进行的多元回归分析中被识别和消除。与比较结果变量相比,比较输入变量时,混淆问题较小。因此,在解释基准测试程序的结果时,需要考虑自动在线比较的潜力和局限性。