在选计划中管理数据:挑战和解决方案
Hugo Monteiro1, Mariana Oliveira1, Ricardo Martinho2
1Faculdade de Medicina. Universidade do Porto. Porto. Portugal.
Acta medica portuguesa
|December 16, 2025
概括
大数据分析可以通过改进数据管理,从存档到实时处理和预测建模来简化人口健康查计划. 这一框架提高了公共卫生倡议的效率,资源优化和患者护理.
科学领域:
- 公共卫生信息学 公共卫生信息学
- 健康 数据科学 数据科学
- 医疗保健管理的管理
背景情况:
- 基于人口的查计划对于早期发现疾病和降低成本至关重要.
- 扩展程序产生大量的数据,需要结构化的数字解决方案.
- 有效的数据管理对于优化查工作流程和患者结果至关重要.
研究的目的:
- 为医疗保健查中的大数据分析提供一个务实的框架.
- 引导医疗保健专业人员和管理人员将数据分析集成到常规工作流程中.
- 用现实世界的例子来说明大数据概念的应用.
主要方法:
- 系统存档使用基于云的存储来进行安全的数据维护.
- 实时处理用于快速决策和患者管理.
- 数据转换和集成到集中式分析平台.
- 先进的分析,包括过程挖掘和预测建模.
- 实时可视化工具用于运营洞察力.
主要成果:
- 结构化数据管理显著提高了运营效率和医疗保健的可访问性.
- 灵活的数字基础设施对于适应公共卫生危机至关重要.
- 大数据分析可以揭示效率低下,并优化选计划中的资源配置.
- 预测模型有助于早期识别有风险的个体.
结论:
- 采用大数据分析需要对数字基础设施,专业培训和数据治理进行投资.
- 对数据管理的结构化方法提高了预防性医疗保健计划的有效性.
- 通过数据驱动的洞察力,可以实现选工作流程的持续改进.
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