确定心力衰竭患者有资格接受指导方针导向的医学治疗
Samantha Subramaniam1, Shahzad Hassan1,2,3, Ozan Unlu1,2,3
1Accelerator for Clinical Transformation, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Population health management
|December 4, 2024
概括
一个基于规则的系统 (RBS) 自动识别心力衰竭 (HF) 患者进行指南导向治疗,减少手动EHR审查. 虽然提高了效率,但准确率为32.1%,表明需要进一步优化.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人口健康管理 人口健康管理
背景情况:
- 许多心力衰竭患者没有接受指南推的治疗.
- 临床工作人员手动审查电子健康记录 (EHR) 是旨在改善药物服药的人口健康管理 (PHM) 计划的重大障碍.
- 需要自动化工具来简化对符合指导方针指导护理的患者的识别.
研究的目的:
- 开发和评估一个基于规则的系统 (RBS) 来自动识别心力衰竭 (HF) 符合准则导向治疗的患者.
- 评估绩效并确定需要改进的领域,用于支持PHM计划的自动化系统.
主要方法:
- 开发了一个基于规则的系统 (RBS) 来分析电子健康记录并识别潜在的符合条件的HF患者.
- 在PHM计划中部署了RBS,每隔一个月运行一次,以标记患者进行手动查.
- 评估了系统性能,包括对假阳性病例的错误分析.
主要成果:
- 在RBS中,从161,000名患有心声图的患者中,每次执行大约确定了4200名患者.
- 在5460名患者的手动查中,确定了1754名真正符合条件的患者,导致准确率为32.1%.
- 超过38%的错误阳性被归因于在确定症状性HF和患者药物史上的不准确性.
结论:
- RBS提供了一种系统的方法,以丰富患者群体的指导方针导向治疗资格.
- 整合临床笔记处理可以显著提高系统的准确性和性能.
- 实施指南导向护理的自动化工具提出了需要进一步解决方案的实际挑战.
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