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首页> 外文期刊>BMC Medical Informatics and Decision Making >Visualizing nationwide variation in medicare Part D prescribing patterns
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Visualizing nationwide variation in medicare Part D prescribing patterns

机译：可视化全国医疗保险D部分处方模式的差异

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To characterize the regional and national variation in prescribing patterns in the Medicare Part D program using dimensional reduction visualization methods. Using publicly available Medicare Part D claims data, we identified and visualized regional and national provider prescribing profile variation with unsupervised clustering and t-distributed stochastic neighbor embedding (t-SNE) dimensional reduction techniques. Additionally, we examined differences between regionally representative prescribing patterns for major metropolitan areas. Distributions of prescribing volume and medication diversity were highly skewed among over 800,000 Medicare Part D providers. Medical specialties had characteristic prescribing patterns. Although the number of Medicare providers in each state was highly correlated with the number of Medicare Part D enrollees, some states were enriched for providers with ?10,000 prescription claims annually. Dimension-reduction, hierarchical clustering and t-SNE visualization of drug- or drug-class prescribing patterns revealed that providers cluster strongly based on specialty and sub-specialty, with large regional variations in prescribing patterns. Major metropolitan areas had distinct prescribing patterns that tended to group by major geographical divisions. This work demonstrates that unsupervised clustering, dimension-reduction and t-SNE visualization can be used to analyze and visualize variation in provider prescribing patterns on a national level across thousands of medications, revealing substantial prescribing variation both between and within specialties, regionally, and between major metropolitan areas. These methods offer an alternative system-wide and pattern-centric view of such data for hypothesis generation, visualization, and pattern identification.
机译：使用降维可视化方法来表征Medicare Part D程序中处方模式的地区和国家差异。使用可公开获得的Medicare D部分索赔数据，我们通过无监督聚类和t分布随机邻居嵌入（t-SNE）降维技术，识别并可视化了区域和国家提供方规定的配置文件变化。此外，我们研究了主要都会区的区域代表性处方模式之间的差异。在超过80万的Medicare D部分提供者中，处方量和药物种类的分布高度偏斜。医学专业具有独特的处方方式。尽管每个州的Medicare提供者数量与Medicare Part D参保者的数量高度相关，但某些州的富裕者每年增加了10,000处方药索赔。药品或药品类别处方模式的降维，层次聚类和t-SNE可视化显示，提供者基于专业和亚专业强烈地聚类，处方模式在区域上存在较大差异。大都市区有不同的处方模式，往往按主要地理区域分组。这项工作表明，无监督的聚类，降维和t-SNE可视化可用于分析和可视化全国范围内数千种药物在医疗服务提供者处方模式中的变化，从而揭示出专业之间，区域内以及地区之间的实质性处方差异。主要都会区。这些方法为此类数据提供了另一种全系统的，以模式为中心的视图，用于假设生成，可视化和模式识别。

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