捕捉与脆弱相关的因素,使用常规收集的电子病历数据在加拿大不列颠哥伦比亚省,初级保健机构设置
Manpreet Thandi1, Morgan Price2, Jennifer Baumbusch1
1School of Nursing, University of British Columbia, Vancouver, BC, Canada.
Primary health care research & development
|May 8, 2025
概括
捕捉加拿大初级保健中的脆弱性需要标准化代码和自由文本术语. 这项研究开发了电子医疗记录的脆弱性选算法,以改善患者的治疗结果.
科学领域:
- 老年学是一门学科.
- 医疗信息学 医疗信息学
- 主要护理医学 医疗保健
背景情况:
- 虚弱是老年人的一个重要的健康问题.
- 电子医疗记录 (EMR) 系统为解决脆弱性提供了机会.
- 在英国使用阅读代码开发了一个36个因素的电子脆弱性指数 (eFI).
研究的目的:
- 将英国36个因素的电子脆弱性指数 (eFI) 转化为加拿大背景.
- 使用加拿大术语开发一个反映36个eFI因子的编码集.
- 为加拿大初级保健创建一个脆弱选算法.
主要方法:
- 将术语手动和自动映射到36个eFI因子.
- 使用加拿大EMR数据的标准化术语和自由文本.
- 从不列颠哥伦比亚省加拿大初级保健哨兵监测网络审查了超过50万个EMR数据条目.
主要成果:
- 识别了3768个术语,包括3021个代码和747个自由文本术语.
- 在36个脆弱性因素中,24个主要是通过代码捕捉,7个通过自由文本,以及4个同样.
- 标准化术语本身是不够的;代码和自由文本的组合更好地捕捉了脆弱的复杂性.
结论:
- 使用标准化代码和自由文本术语的混合方法对于加拿大初级保健中准确的脆弱性评估是必要的.
- 可以优化EMR系统以更好地检测脆弱性.
- 这项研究的成果使得能够为初级保健机构开发一个实用的脆弱性选算法.
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