接近全国性的注册:分析心力衰竭患者的大数据
Tuğçe Çöllüoğlu1, Anıl Şahin2, Ahmet Çelik3
1Department of Cardiology, Faculty of Medicine, Karabük University, Karabük, Turkiye.
Turkish journal of medical sciences
|December 30, 2024
概括
这项研究强调了使用医疗保健大数据用于心力衰竭 (HF) 研究的挑战. 准确的患者鉴定和专家分析对于高频的可靠现实世界证据至关重要.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 大数据分析大数据分析
背景情况:
- 随机对照试验往往缺乏现实世界的概括性.
- 大数据分析将试验结果与临床实践联系起来,但也面临着数据质量挑战.
- 这项研究考察了在土耳其为心力衰竭 (HF) 研究访问和使用医疗保健大数据的情况.
研究的目的:
- 探索获得和利用医疗保健大数据用于心力衰竭 (HF) 研究的挑战.
- 详细介绍在土耳其创建全国HF注册的经验.
- 在高频研究中确定大数据分析的最佳实践.
主要方法:
- 组建了一个多学科团队 (心脏病学家,生物统计学家,数据分析师).
- 与HF流行病学,结果和治疗相关的关键词被用于数据检索.
- 大数据来自国家医疗保健数据系统,选了超过8500万份医疗记录.
主要成果:
- 通过使用ICD-10代码和药物数据,确定了超过270万HF患者的队列.
- 分析了并发症,药物 (ATC代码) 和程序 (SUT代码).
- 基于SPSS,MedCalc,E-PICOS和Python的代码被用于统计分析,并采用倾向得分匹配.
结论:
- 从大数据中使用ICD-10代码准确识别心力衰竭患者需要特定的标准.
- 利用多种统计程序和专家分析对于正确的大数据解释在高频研究中至关重要.
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