在电子健康记录中找到埋藏的基因测试结果是低效的,并且在各机构之间有所变化
Olivia J Veatch1, Jomol Mathew2, Shira Rockowitz3
1University of Kansas Medical Center, 3901 Rainbow Blvd, Mail Stop 4015, Kansas City, KS 66160-8500, USA.
Therapeutic advances in rare disease
|July 14, 2025
概括
从电子健康记录 (EHR) 中检索遗传测试结果的标准化对于识别罕见遗传变异患者至关重要. 这改善了研究参与和基因组驱动的护理,减少了诊断旅程.
科学领域:
- 基因组学和生物信息学
- 医疗信息学 医疗信息学
- 罕见疾病研究研究 罕见疾病研究
背景情况:
- 在电子健康记录 (EHR) 和罕见疾病诊断代码中缺乏标准化的基因测试结果处理,这阻碍了患者的识别.
- 这种差距阻碍了获得研究机会和基因组驱动的护理,延长了罕见遗传变异患者的诊断旅程.
研究的目的:
- 评估资源需求,产量和不同方法的偏差来识别和检索遗传测试结果.
- 将11个智力和发育障碍研究中心 (IDDRC) 的方法进行比较,以优化遗传数据检索.
主要方法:
- 一项调查收集了用于识别含有遗传检测结果和特定变异的EHR的方法的数据.
- 评估了四种方法的优点和局限性:手动搜索,NLP辅助手动审查,定制数据库和EHR供应商基因组学模块.
- 评估了存储格式,患者识别策略,时间/成本估计,访问的数据和确定变种类型的偏差.
主要成果:
- 存储,搜索和提取遗传测试结果的方法有很大的不同,特别是对于较旧的数据.
- 手动搜索的基础设施较低,但错过了变体;NLP软件减少了工作量,但需要信息支持.
- 定制数据库和EHR供应商模块提供了高效的检索,但需要大量的计算资源.
结论:
- 基因检测结果管理在IDDRC之间存在显著差异,影响数据的可访问性和实用性.
- 制定实践指南以标准化存储和检索对于有效识别研究参与者至关重要.
- 标准化将促进基因组信息的患者护理,并加速对罕见遗传疾病的研究.
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