使用易于获得的数据集构建护理价值模型:把拼图的部分放在一起
Seo Yoon Lee1, Chang Gi Park2, Andrew D Boyd3
1Center for Research and Scholarly Development, School of Nursing, Vanderbilt University, Nashville, TN.
Nursing administration quarterly
|December 10, 2025
概括
本研究详细说明了使用医疗保健数据构建护理价值模型 (NVM) 的方法. 它强调了数据整合的挑战,以准确地测量患者级护理价值.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 护理研究 护理研究
- 数据科学数据科学数据科学
背景情况:
- 护理价值模型 (NVM) 是衡量患者级护理价值的框架.
- 关于使用真实数据进行NVM构建和可行性的研究有限.
- 电子健康记录 (EHR) 和行政数据是医疗分析的关键来源.
研究的目的:
- 引入一种使用可用的医疗保健数据构建NVM的方法.
- 通过识别洞察力和挑战,讨论NVM开发的可行性.
- 通过数据综合,探索患者层面的护理成本估计.
主要方法:
- 从四个不同的数据源收集并合并了六个数据集.
- 描述了数据采集,纠,构建和整合性过程.
- 分析了用于NVM开发的单个数据集的优缺点.
主要成果:
- 从多个来源成功构建了一个用于NVM探索的数据集.
- 鉴定了数据集合并的重大挑战,原因是患者和护士的非统一的唯一代码.
- 强调了数据整合过程中遇到的复杂性和困难.
结论:
- 开发NVM需要强大的数据系统,能够轻松收集,组织和合成数据.
- 解决数据统一性问题对于准确的患者级护理价值计算至关重要.
- 未来的努力应专注于改进数据基础设施,以支持全面的护理价值评估.
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