在电子医疗记录数据中确定处方:开发标准化,可重复的药物代码列表的方法
Emily L Graul1, Philip W Stone1,2, Georgie M Massen2
1School of Public Health, Imperial College London, London W12 0BZ, United Kingdom.
JAMIA open
|August 31, 2023
概括
制定全面的药物代码列表需要在所有变量上制定完整的搜索策略,以便在研究中准确识别患者. 这种方法确保了跨研究的可复制性和适应性.
科学领域:
- 药物监督和药物流行病学
- 医疗信息学 医疗信息学
- 临床研究方法论 临床研究方法论
背景情况:
- 准确识别患者的药物使用对于流行病学研究至关重要.
- 现有的生成药物代码列表的方法可能缺乏全面性或适应性.
- 为了在各种数据库中创建药物代码列表,需要标准化和可重复的方法.
研究的目的:
- 开发一种标准化,可复制和适应的方法,用于创建包含临床专业知识的药物代码列表.
- 为了比较不同的药物代码列表生成策略的准确性和全面性.
- 应用开发的方法来识别心血管疾病和COPD疗法在大型患者队列中.
主要方法:
- 开发并测试了使用临床实践研究数据链接 (CPRD) Aurum数据库生成药物代码列表的方法.
- 为心血管疾病和呼吸慢性阻塞性肺病 (COPD) 疗法生成了代码列表.
- 对比了三个搜索策略:所有药物词典变量 (A),仅化学变量 (B) 和仅存在学变量 (C).
主要成果:
- 完整的搜索策略 (A) 与策略C相比,对于心血管药物和COPD吸入器,发现了显著更多的处方.
- 策略C错过了许多必要的处方,包括血管扩张抗高血压药和SAMA吸入器.
- 战略A在335,931名COPD患者的队列中确定了165,150名心血管药物患者和317,963名COPD吸入器患者.
结论:
- 建议综合搜索策略 (A) 用于生成可适应和可通用的药物代码列表.
- 强调临床输入,标准化,可重复性和跨数据背景的理解的重要性.
- 强调了诸如药物状态波动,队列特定指示和代码列表开发中的等级本体学等考虑因素.
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