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Venous Thromboembolism (VTE) Harm Measurement and Risk Assessment in Real-Time Using Electronic Health Records(EHR)

机译:使用电子病历(EHR)实时进行静脉血栓栓塞(VTE)危害测量和风险评估

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摘要

Venous Thromboembolism (VTE) is a deadly disease and is considered as one of the top reasons for avoidable hospital deaths in the United States and around the world. Patients who survive this disease often must face life-long complications such as Post-thrombotic syndrome (PTS), Chronic thromboembolic pulmonary hypertension (CTPH), etc. Therefore, it is important to monitor and reduce the number of VTE instances in hospitals. This study shows how Electronic Health Records (EHRs) can be utilized to achieve this goal.;First, a new near real-time VTE harm measurement model was developed. Not only the developed model can deliver near real-time results, but also it can outperform the existing PSI12 measurement model that uses administrative data (sensitivity 84% vs. 38% and NPV 99% vs. 95%).;In the next step, Padua VTE risk assessment model was developed inside the EHR to deliver real-time VTE risk assessment. Retrospective data analysis was also performed to show how another risk assessment model (IMPROVE) can be developed inside EHR. Analysis were completed to show and compare the effectiveness of each model.;Finally, the results of utilizing the developed models are presented in terms of contributions to savings for the health system as well as the number of lives saved.
机译:静脉血栓栓塞症(VTE)是一种致命疾病,被认为是美国和世界各地可避免的医院死亡的主要原因之一。在这种疾病中幸存的患者通常必须面对终生并发症,例如血栓形成后综合症(PTS),慢性血栓栓塞性肺动脉高压(CTPH)等。因此,监测和减少医院中的VTE病例数非常重要。这项研究表明了如何利用电子健康记录(EHR)来实现这一目标。首先,开发了一种新的近实时VTE危害测量模型。开发的模型不仅可以提供近乎实时的结果,而且还可以超越使用管理数据的现有PSI12测量模型(灵敏度分别为84%与38%和NPV 99%与95%)。 ,帕多瓦VTE风险评估模型是在EHR内部开发的,用于提供实时VTE风险评估。还进行了回顾性数据分析,以显示如何在EHR中开发另一个风险评估模型(IMPROVE)。完成分析以显示和比较每个模型的有效性。最后,使用开发的模型的结果从对卫生系统节省的费用以及挽救的生命数方面进行了介绍。

著录项

  • 作者

    Marashi, Seyed Mani.;

  • 作者单位

    Wayne State University.;

  • 授予单位 Wayne State University.;
  • 学科 Industrial engineering.;Medicine.;Information technology.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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