一个框架来定义通过电子算法识别的诊断上具有挑战性的条件
Andrew P J Olson1, Jennifer Sloane2,3, Andrew Zimolzak2,3
1Division of Hospital Medicine, Department of Medicine; Division of Pediatric Hospital Medicine, Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA.
Diagnosis (Berlin, Germany)
|October 25, 2025
概括
早期识别患有难以诊断疾病 (DCC) 的患者至关重要. 一个新的框架使用电子健康记录数据主动找到这些患者,旨在减少诊断延迟和改善结果.
科学领域:
- 医疗信息学 医疗信息学
- 临床决策支持 临床决策支持
- 医学诊断 医学诊断 医学诊断
背景情况:
- 诊断错误每年影响5%的美国成年人,导致长期的诊断旅程.
- 患有难以诊断的疾病 (DCC) 的患者在接受准确诊断时面临显著的延迟.
- 纵向电子健康记录 (EHR) 数据为积极的患者识别提供了潜力.
研究的目的:
- 提出一个新的框架,利用电子数据主动识别患有DCC的患者.
- 为了能够更早地检测DCC并减轻诊断延迟.
- 通过及时诊断和干预,改善患者的治疗结果.
主要方法:
- 开发了一个利用纵向EHR数据的框架来识别患有DCC的患者.
- 针对检测特定的DCC的拟议标准,可用于基于EHR的算法检测.
- 将框架应用于纤维化间歇性肺病的案例研究.
主要成果:
- 拟议的框架可以识别患有诊断延迟风险的患者.
- 可以开发基于EHR的算法来检测特定的DCC.
- 早期识别有助于及时跟进,并减少错过诊断.
结论:
- 一个主动的基于EHR的框架可以显著减少DCC的诊断延迟.
- 这种方法可以通过确保及时诊断,从而改善患者的治疗结果.
- 未来的研究可以专注于实时实施,以防止因延迟护理而造成的伤害.
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