在纵向研究中开发数字健康管理系统:马来西亚队列经验
Noraidatulakma Abdullah1, Nurul Faeizah Husin1, Ying-Xian Goh1
1UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Digital health
|September 16, 2024
概括
马来西亚队列项目为广泛的纵向健康数据开发了创新的数据管理策略. 这些方法确保了数据的完整性和安全性,为资源有限的队列研究提供了一个模型.
科学领域:
- 医疗信息学 医疗信息学
- 纵向数据管理 纵向数据管理
- 公共卫生研究 公共卫生研究
背景情况:
- 在队列研究中管理广泛的纵向数据存在挑战,特别是在资源有限的中等收入国家.
- 确保长期健康数据的数据完整性,安全性和可扩展存储是至关重要的.
- 在像马来西亚这样的环境中,技术资源的局限性加剧了这些数据管理困难.
研究的目的:
- 概述马来西亚队列项目用于管理大规模纵向数据库的创新方法.
- 确保强大的数据隐私和安全在整个项目生命周期,从开始到后续.
- 提出可扩展的数据管理框架,适用于资源有限的环境中类似的队列研究.
主要方法:
- 开发和实施用于处理大量数据的先进信息管理系统.
- 遵守严格的数据安全协议,以保持数据隐私和完整性.
- 建立一个可扩展的数据库架构,以适应动态的研究需求.
主要成果:
- 成功建立了可扩展的数据库架构和有效的数据隐私框架.
- 展示适用于纵向医疗保健研究的可靠数据管理实践.
- 为在资源有限的环境中面临类似数据管理挑战的队列研究创建模型.
结论:
- 实施的数据管理解决方案为资源有限的队列研究提供了有价值的模型.
- 这些方法为管理公共卫生和个性化医疗的医疗保健大数据提供了洞察力.
- 分享这些实践有助于改善纵向健康研究的全球数据管理.
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