通过结合丹麦国家患者登记册中的临床人员联系人来形成医院护理情节的算法:一种方法论共识驱动的研究
Rasmus Gregersen1,2,3, Cathrine Fox Maule2, Camilla Bjørn Jensen2
1Department of Emergency Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Scandinavian journal of public health
|October 23, 2024
概括
这项研究开发了一种算法,将丹麦国家患者登记册 (DNPR) 中的顺序患者联系联系成完整的医院护理情节. 经过验证的算法改进了对停留时间和再接收研究的健康数据分析.
科学领域:
- 医疗信息学 医疗信息学
- 数据链接方法论数据链接方法论
- 公共卫生研究 公共卫生研究
背景情况:
- 使用注册数据评估完整的医院护理事件存在方法上的挑战,因为缺乏唯一的联系链接标识符.
- 现有的方法难以准确地定义综合住院时间,影响住院时间,出院和再入院的分析.
研究的目的:
- 开发和验证一个算法,将丹麦国家患者登记册 (DNPR) 中的连续出勤联系结合成完整的医院护理情节.
- 创建一个强大的方法,覆盖整个持续时间,包括从医院到达到出发的所有接触.
主要方法:
- 丹麦研究机构合作开发了一种算法,处理DNPR数据 (版本2和3).
- 该方法涉及数据清理,门诊接触者的重复删除,接触类型的修改和在定义的时间值内连接连续接触 (建议4小时).
- 该算法在丹麦 (2013-2021) 的成年人数据集上进行了测试,并比较了各种小时截止值.
主要成果:
- 该算法处理了570万个人的12020万个联系人,形成了1.059亿次医院护理事件.
- 建议将联系人切断4小时,与较长的间隔 (12-h, 24-h) 相比,对事件数的影响最小.
- 在3小时,5小时和6小时的截止时间之间观察到微小的变化 (<0.4%),而12小时 (<1.7%) 和24小时 (<43.1%) 显示出更大的差异.
结论:
- 开发的算法自动化了连接连续的出席联系到全面的医院护理情节.
- 该工具提高了健康数据分析的准确性,特别是对于像停留时间和再接收率这样的指标.
- 该算法以SAS宏的形式提供,以促进其在研究中的采用.
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