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利用漏斗图和混合效应模型检测和可视化提供者概况中的异常值——来自处方索赔数据的一个示例。

Detecting and Visualizing Outliers in Provider Profiling Using Funnel Plots and Mixed Effects Models-An Example from Prescription Claims Data.

机构信息

Department of General Practice/Family Medicine, Philipps University Marburg, Karl-von-Frisch-Str.4, 35043 Marburg, Germany.

Central Research Institute of Ambulatory Health Care in Germany (ZI), Salzufer 8, 10587 Berlin, Germany.

出版信息

Int J Environ Res Public Health. 2018 Sep 15;15(9):2015. doi: 10.3390/ijerph15092015.

Abstract

When prescribing a drug for a patient, a physician also has to consider economic aspects. We were interested in the feasibility and validity of profiling based on funnel plots and mixed effect models for the surveillance of German ambulatory care physicians' prescribing. We analyzed prescriptions issued to patients with a health insurance card attending neurologists' and psychiatrists' ambulatory practices in the German federal state of Saarland. The German National Association of Statutory Health Insurance Physicians developed a prescribing assessment scheme (PAS) which contains a systematic appraisal of the benefit of drugs for so far 12 different indications. The drugs have been classified on the basis of their clinical evidence as "standard", "reserve" or "third level" medication. We had 152.583 prescriptions in 56 practices available for analysis. A total of 38.796 patients received these prescriptions. The funnel plot approach with additive correction for overdispersion was almost equivalent to a mixed effects model which directly took the multilevel structure of the data into account. In the first case three practices were labeled as outliers, the mixed effects model resulted in two outliers. We suggest that both techniques should be routinely applied within a surveillance system of prescription claims data.

摘要

当为患者开处方时,医生还必须考虑经济方面。我们对基于漏斗图和混合效应模型进行分析以监测德国门诊医生处方的可行性和有效性很感兴趣。我们分析了在德国萨尔州的神经科医生和精神科医生的门诊实践中,持有健康保险卡的患者的处方。德国法定健康保险公司协会制定了一种处方评估方案(PAS),该方案对 12 种不同适应症的药物的疗效进行了系统评估。这些药物根据其临床证据被分类为“标准”、“储备”或“第三级”药物。我们有 56 家诊所的 152,583 张处方可供分析。共有 38,796 名患者收到了这些处方。添加了过度分散的校正的漏斗图方法几乎等同于直接考虑数据多层次结构的混合效应模型。在前一种情况下,有三个实践被标记为异常值,而混合效应模型则产生了两个异常值。我们建议在处方索赔数据的监测系统中应常规应用这两种技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6e/6163340/2746c0040ba3/ijerph-15-02015-g001.jpg

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