健康数据中心:对现有的研究数据治理特征进行分析
Celia Alvarez-Romero1, Alicia Martínez-García2, Máximo Bernabeu-Wittel3
1Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Avenue Manuel Siurot S/N, 41013, Seville, Spain. celia.alvarez@juntadeandalucia.es.
Health research policy and systems
|July 10, 2023
概括
这项研究调查了欧洲的健康数据中心,以确定管理敏感健康数据的最佳做法. 主要建议包括集中操作,明确的数据处理协议,以及强大的匿名化,以确保在研究中安全的数据共享.
科学领域:
- 医疗信息学 医疗信息学
- 数据治理数据治理
- 生物医学研究生物医学研究
背景情况:
- 医疗保健的数字化转型产生了大量敏感的健康数据.
- 医疗记录用于研究的二次使用面临着伦理和法律挑战.
- 了解数据中心的健康数据管理对于数据共享和重复使用至关重要.
研究的目的:
- 分析欧洲健康数据中心的数据治理模型.
- 确定管理敏感健康数据的模式和最佳实践.
- 评估链接个人健康数据的可行性.
主要方法:
- 一项调查在2022年1月份分发给99个国家,欧洲和全球健康数据中心.
- 分析重点是数据治理,数据链接可行性和模式生成.
- 分析了到2022年6月收到的41个健康数据中心的响应.
主要成果:
- 建立了健康数据中心的一般数据治理模式.
- 根据组织结构 (集中/分散) 和受访者角色 (数据控制者/处理者) 定义了特定的治理配置文件.
- 确定了数据管理和治理的常见方面.
结论:
- 卫生数据中心应以集中方式运作,实施数据处理协议.
- 确定数据提供者的正式程序是必不可少的.
- 强大的数据质量控制,完整性和匿名化方法被推用于敏感数据处理.
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