识别和表征慢性病电子表型使用电子健康记录衍生数据:对策略和应用的叙述性审查
Christopher Sparks1,2, Adam G Steinberg1,2,3, Nigel D Toussaint1,2
1Department of Nephrology, The Royal Melbourne Hospital, Melbourne, Victoria, Australia.
Nephrology (Carlton, Vic.)
|September 13, 2025
概括
使用电子健康记录 (EHR) 开发慢性病 (CKD) 的电子表型是可行的. 结合估计的淋巴膜过率 (eGFR) 和蛋白尿标准,为CKD识别提供了一种实用和可靠的方法.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
背景情况:
- 慢性病 (CKD) 构成了全球健康面临的重大和日益严重的挑战.
- 慢性瘤的分期依赖于实验室值,使电子健康记录 (EHR) 成为识别和表征的有价值数据来源.
- 为CKD开发一个准确和实用的电子表型 (e-表型) 对研究和临床护理至关重要.
研究的目的:
- 审查和评估各种策略,以从EHR数据中创建CKD电子表型.
- 评估不同表型化方法的准确性,准确性和实用性.
- 概述可靠的CKD电子表型的当前和未来应用.
主要方法:
- 对CKD电子表型化策略的文献综述.
- 分析方法包括ICD代码,eGFR和蛋白尿标准,NLP和机器学习.
- 对算法性能,复杂性和可靠性的评估.
主要成果:
- 不同CKD电子表型算法的性能和复杂性存在显著的变化.
- 使用估计的膜过率 (eGFR) 和蛋白尿标准是CKDe-表型发展的最实用和可靠的方法.
- CKD e-表型在描述疾病负担和指导优质护理方面具有潜在的应用.
结论:
- 使用EHR数据可以有效地开发CKD电子表现型.
- eGFR和蛋白尿症标准为CKDe-表型提供了坚实的基础.
- 未来的应用包括风险分层,临床决策支持,公共卫生和临床试验招聘.
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