在澳大利亚个人级别的药物发行数据中进行的药物利用研究:一个盲目的多中心复制分析
Malcolm B Gillies1,2, Chrianna Bharat2,3, Ximena Camacho1,2
1Medicines Intelligence Research Program, School of Population Health, UNSW Sydney, Kensington, Australia.
数据准备决策显著影响研究可重复性. 一个协调的协议 (HARPER) 提高了分析糖尿病治疗事件的药物发行数据的一致性.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 药学流行病学 药学流行病学
- 数据科学数据科学数据科学
背景情况:
- 药物发行数据需要进行广泛的研究准备.
- 数据准备期间的分析决策可能会导致无法复制的结果.
- 标准化这些决策对于可靠的研究成果至关重要.
研究的目的:
- 检查分析决策对研究结果的影响.
- 在分析药物发行数据的研究中评估可重复性.
- 评估一个协调的协议,以提高药物流行病学中的可复制性.
主要方法:
- 四个澳大利亚站点独立地应用了Harmonized Protocol模板来提高可重复性 (HARPER).
- 对澳大利亚制药福利计划10%样本数据集进行了分析.
- 关键结果包括队列大小,人口统计,治疗中止,切换和强化,在各站点评估一致性.
主要成果:
- 对于队列大小,性别和年龄组,观察到良好的一致性.
- 然而,由于估计日供应和操作定义的不同方法,治疗中止,转换和强化率达成不一致.
- 时间到事件的估计和危险比率也显示出不良协议.
结论:
- 在处理分发数据时,分析决策的变化显著影响了研究可复制性.
- 详细的分析协议,如哈珀,对于确保操作定义和解释的透明度至关重要.
- 标准化协议对于提高使用药物发行数据的研究的可靠性和可重复性至关重要.
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