在现实世界的数据中检测日期移动
Laura Evans1, Jack W London1,2, Matvey B Palchuk1
1TriNetX, LLC., Boston, Massachusetts, United States.
Applied clinical informatics
|July 17, 2023
概括
研究人员可以通过分析例行医疗检查的模式来检测医疗保健现实世界数据 (RWD) 中的日期转移. 该方法可靠地识别数据完整性问题,确保更准确的患者健康事件分析.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 流行病学 流行病学
背景情况:
- 现实世界数据 (RWD) 提供了对患者护理的宝贵见解,但也有局限性.
- 在RWD中改变日期可能会损害研究结果的有效性.
- 准确的时间数据对于可靠的健康研究至关重要.
研究的目的:
- 开发和验证一种方法来检测医疗保健RWD中的日期转移.
- 评估日期转移对患者诊断和治疗事件分析完整性的影响.
- 提高RWD在临床研究和决策方面的可靠性.
主要方法:
- 开发了一种新的方法,通过分析诊断和程序中的时间模式来检测日期转移.
- 分析了TrinetX网络中的71个美国医疗保健组织 (HCO) 的数据.
- 为了与实际的HCO数据进行比较,生成了不同程度的日期转移的合成数据.
主要成果:
- 该方法成功预测了71个HCO中的28个日期转移,数据提供商证实了这一点.
- 39个HCO被准确地预测为没有日期转移.
- 只有在工作日进行例行医疗检查的发生率与日期转移的存在或不存在有很高的相关性 (0.92).
结论:
- 美国医疗保健中的日期转移RWD可以通过检查例行医疗检查的模式来可靠地检测.
- 评估常规考试是否只在工作日进行,是数据完整性的关键指标.
- 这种方法提高了RWD在健康研究中的可信度.
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