BACKGROUND Drug safety in children is a major concern; however, there is still a lack of methods for quantitatively measuring, let alone to improving, drug safety in children under different clinical conditions. To assess pediatric drug safety under different clinical conditions, a computational method based on Electronic Medical Record (EMR) datasets was proposed. METHODS In this study, a computational method was designed to extract the significant drug-diagnosis associations (based on a Bonferroni-adjusted hypergeometric P-value < 0.05) among drug and diagnosis co-occurrence in EMR datasets. This allows for differences between pediatric and adult drug use to be compared based on different EMR datasets. The drug-diagnosis associations were further used to generate drug clusters under specific clinical conditions using unsupervised clustering. A 5-layer quantitative pediatric drug safety level was proposed based on the drug safety statement of the pediatric labeling of each drug. Therefore, the drug safety levels under different pediatric clinical conditions were calculated. Two EMR datasets from a 1900-bed children's hospital and a 2000-bed general hospital were used to test this method. RESULTS The comparison between the children's hospital and the general hospital showed unique features of pediatric drug use and identified the drug treatment gap between children and adults. In total, 591 drugs were used in the children's hospital; 18 drug clusters that were associated with certain clinical conditions were generated based on our method; and the quantitative drug safety levels of each drug cluster (under different clinical conditions) were calculated, analyzed, and visualized. CONCLUSION With this method, quantitative drug safety levels under certain clinical conditions in pediatric patients can be evaluated and compared. If there are longitudinal data, improvements can also be measured. This method has the potential to be used in many population-level, health data-based drug safety studies.

中文翻译：

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一种使用电子病历定量测量儿科药物安全性的计算方法。

背景技术儿童的药物安全性是主要关注的问题。然而，仍然缺乏定量测量不同临床条件下儿童药物安全性的方法，更不用说改善药物安全性了。为了评估不同临床条件下的儿科药物安全性，提出了一种基于电子病历（EMR）数据集的计算方法。方法在本研究中，设计了一种计算方法以提取EMR数据集中药物与诊断共现之间的重要药物诊断关联（基于Bonferroni调整的超几何P值<0.05）。这允许根据不同的EMR数据集比较儿科和成人用药之间的差异。药物诊断协会还使用无监督聚类进一步用于在特定临床条件下产生药物聚类。基于每种药物的儿科标签的药物安全性说明，提出了5层定量儿科药物安全性级别。因此，计算了不同儿科临床条件下的药物安全性水平。该方法使用了来自1900张病床的儿童医院和2000张病床的综合医院的两个EMR数据集。结果儿童医院与综合医院之间的比较显示了儿科药物使用的独特特征，并确定了儿童与成人之间的药物治疗差距。儿童医院总共使用了591种药物；根据我们的方法，产生了18种与某些临床状况相关的药物群；并计算，分析每个药物簇（在不同的临床条件下）的定量药物安全性水平，和可视化。结论采用这种方法，可以评估和比较儿童在特定临床条件下的定量药物安全性水平。如果有纵向数据，也可以测量改进。这种方法有可能用于许多基于人口数据，基于健康数据的药物安全性研究中。