使用电子医疗记录检测痴呆症的养老院居民的激动行为
Hyunkyung Yun1, Vincent Mor2, Christopher Santostefano3
1Department of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA.
Journal of the American Medical Directors Association
|September 30, 2024
概括
增加最小数据集 (MDS) 数据与电子医疗记录 (EMR) 显著增加了在阿尔茨海默病和相关痴呆症 (ADRD) 的养老院居民中检测激动行为. 这种全面的方法可以更好地识别更好的护理.
科学领域:
- 老年学和老年医学是老年学和老年医学.
- 行为健康和精神病学
- 医疗信息学 医疗信息学
背景情况:
- 在阿尔茨海默氏症和相关痴呆症 (ADRD) 的养老院 (NH) 居民中,兴奋的行为很普遍.
- 仅仅依靠最小数据集 (MDS) 数据来进行NH的行为管理试验会导致报告不足.
- 电子病历 (EMR) 提供了一个潜在的来源,以增强MDS数据,以便更准确的行为评估.
研究的目的:
- 描述一种方法来增强基于MDS的行为测量方法,使用NH EMR的结构化和非结构化数据.
- 评估纳入EMR数据对ADRD患者激动行为识别的影响.
主要方法:
- 来自多州NH公司的EMR数据的重复横截面分析 (2020年1月 - 2022年8月).
- 包括长期停留的NH居民 (≥90天) 患有ADRD.
- 从MDS,INTERACT表单 (结构化EMR) 和自由文本订单 (非结构化EMR) 中提取的行为数据.
主要成果:
- 分析包括对19,705名居民进行的77,936次MDS评估.
- 补充MDS与EMR数据增加了3.8个百分点的行为识别 (25.7%的相对增加).
- 仅MDS就发现了14.8%的居民每月有行为;MDS + INTERACT发现了16.2%;MDS + INTERACT +订单发现了18.6%.
结论:
- 将EMR数据 (结构化和非结构化) 与MDS整合起来,可以显著提高在NH居民患有ADRD时兴奋行为的检测.
- 这三个数据源 (MDS,INTERACT,订单) 捕获了不同的行为信息,这表明综合方法可以提供更全面的识别.
- 改进的识别策略对于有针对性的干预和资源分配至关重要,以提高与ADRD相关行为的NH居民的生活质量.
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