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首页> 外文期刊>BMC Medical Informatics and Decision Making >Evaluation of rational nonsteroidal anti-inflammatory drugs and gastro-protective agents use; association rule data mining using outpatient prescription patterns
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Evaluation of rational nonsteroidal anti-inflammatory drugs and gastro-protective agents use; association rule data mining using outpatient prescription patterns

机译：评价合理的非甾体抗炎药和胃保护剂的使用;门诊处方模式的关联规则数据挖掘

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Background Nonsteroidal anti-inflammatory drugs (NSAIDs) and gastro-protective agents should be co-prescribed following a standard clinical practice guideline; however, adherence to this guideline in routine practice is unknown. This study applied an association rule model (ARM) to estimate rational NSAIDs and gastro-protective agents use in an outpatient prescriptions dataset. Methods A database of hospital outpatients from October 1st, 2013 to September 30th, 2015 was searched for any of following drugs: oral antacids (A02A), peptic ulcer and gastro-oesophageal reflux disease drugs (GORD, A02B), and anti-inflammatory and anti-rheumatic products, non-steroids or NSAIDs (M01A). Data including patient demographics, diagnoses, and drug utilization were also retrieved. An association rule model was used to analyze co-prescription of the same drug class (i.e., prescriptions within A02A-A02B, M01A) and between drug classes (A02A-A02B & M01A) using the Apriori algorithm in R. The lift value, was calculated by a ratio of confidence to expected confidence, which gave information about the association between drugs in the prescription. Results We identified a total of 404,273 patients with 2,575,331 outpatient visits in 2 fiscal years. Mean age was 48?years and 34% were male. Among A02A, A02B and M01A drug classes, 12 rules of associations were discovered with support and confidence thresholds of 1% and 50%. The highest lift was between Omeprazole and Ranitidine (340 visits); about one-third of these visits (118) were prescriptions to non-GORD patients, contrary to guidelines. Another finding was the concomitant use of COX-2 inhibitors (Etoricoxib or Celecoxib) and PPIs. 35.6% of these were for patients aged less than 60?years with no GI complication and no Aspirin, inconsistent with guidelines. Conclusions Around one-third of occasions where these medications were co-prescribed were inconsistent with guidelines. With the rapid growth of health datasets, data mining methods may help assess quality of care and concordance with guidelines and best evidence.
机译：背景非甾体抗炎药（NSAIDs）和胃保护剂应按照标准的临床实践指南共同处方;但是，在日常实践中是否遵守该准则尚不清楚。这项研究应用关联规则模型（ARM）来估计门诊处方数据集中合理使用的NSAID和胃保护剂。方法对2013年10月1日至2015年9月30日住院的门诊患者数据库中的以下药物进行检索：口服抗酸药（A02A），消化性溃疡和胃食管反流病药物（GORD，A02B），抗炎药和抗风湿产品，非类固醇或非甾体抗炎药（M01A）。还检索了包括患者人口统计信息，诊断和药物利用情况的数据。使用关联规则模型使用R中的Apriori算法分析相同药物类别（即A02A-A02B，M01A内的处方）以及药物类别之间（A02A-A02B和M01A）的共同处方。提升值是由置信度与预期置信度之比计算得出，可提供有关处方中药物之间关联的信息。结果我们在两个财政年度内共鉴定了404,273名患者，门诊为2,575,331名。平均年龄为48岁，男性为34％。在A02A，A02B和M01A药物类别中，发现了12个关联规则，支持和置信度阈值为1％和50％。最高升程在奥美拉唑和雷尼替丁之间（340次）。与指南相反，这些访视中约有三分之一（118）是针对非GORD患者的处方。另一个发现是同时使用COX-2抑制剂（Etoricoxib或Celecoxib）和PPI。其中35.6％用于年龄小于60岁且没有胃肠道并发症和阿司匹林的患者，与指南不一致。结论共同处方这些药物的大约三分之一的情况与指南不一致。随着健康数据集的快速增长，数据挖掘方法可能有助于评估护理质量并与指南和最佳证据保持一致。

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