逻辑观察标识符名称和代码术语的资源,这些术语可能与识别信息相关联
Mehdi Nourelahi1, Eugene M Sadhu1, Malarkodi J Samayamuthu1
1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, United States.
概括
创建了1309个逻辑观察标识符名称和代码 (LOINC) 术语的新列表,这些术语可能与患者,提供者和设施数据相关. 这个资源有助于去识别LOINC编码的健康记录,以符合隐私要求.
科学领域:
- 医疗信息学 医疗信息学
- 医学术语 医学术语 医学术语
- 数据 隐私 数据 隐私 数据
背景情况:
- 电子健康记录 (EHR) 使用标准化术语进行数据编码.
- 准确地消除电子病历数据的识别对于研究和患者隐私至关重要.
- 逻辑观察标识符名称和代码 (LOINC) 是广泛采用的临床观察标准.
研究的目的:
- 创建与患者,医疗保健提供者和设施标识符相关的LOINC术语的全面目录.
- 开发一个资源,以促进LOINC编码数据的非识别.
- 为了支持遵守HIPAA等隐私法规.
主要方法:
- 为了确定相关的LOINC术语,采用了两步过程.
- 该程序涉及LOINC长常见名称的关键字搜索和按属性值进行过.
- 专家医生进行了审查,以确认和分类识别的术语.
主要成果:
- 编制了1309个可能与识别信息相关的LOINC术语的最终清单.
- 这些术语与患者,医疗保健提供者和医疗保健设施有关.
- 完整的列表可以通过GitHub公开访问.
结论:
- 与其他术语相比,LOINC编码的数据在去识别方面存在明显的挑战.
- 开发的资源对于去识别LOINC数据非常有价值,确保HIPAA合规.
- 这项工作增强了医疗数据中患者,提供者和设施隐私的保护.
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