Implementation of a Novel Multi-Platform Evidence-Based Clinical Decision Support System

新型多平台循证临床决策支持系统的实施

基本信息

项目摘要

Project Abstract Venous thromboembolism (VTE), consisting of deep venous thrombosis (DVT) and pulmonary embolism (PE), is a deadly disease with 30-day and one-year case fatality in the general population of 14% and 29%, respectively. This concern has increased with the recent pandemic as complications due to VTE have been associated with 40% of deaths of patients with Coronavirus Disease 2019 (COVID-19). The overarching aim of this proposal is: 1) to refine and validate two clinical prediction rules (CPRs) for assessment of VTE in patients presenting to or admitted from the emergency department (ED) with COVID-19 and 2) to design, perform usability testing, and implement two clinical decision support (CDS) tools based on these CPRs within our novel, innovative service-oriented architecture (SOA)-based complex CDS system (CDSS). Wells’ criteria in combination with D-Dimer is a CPR that helps healthcare providers exclude PE and the need for unnecessary computed tomography pulmonary angiography (CTPA). In addition, acutely-ill hospitalized medical patients are at moderate-to-high risk for developing VTE events during the hospital stay. Hospitalized COVID-19 patients are at especially high risk of VTE, with recent reports suggest a prevalence of DVT as high as 46% in medical wards and PE as high as 42% in ICU settings. These data are consistent with VTE risk associated with previous viral pneumonias such as H1N1 which have shown a 23-fold increased risk for VTE. Thrombo-prophylaxis shows significant benefits for in-hospital period, but must be used appropriately as it carries risk for morbidity and mortality related to bleeding. VTE risk in admitted patients is difficult to assess and physicians rely on CPRs such as IMPROVE-D-Dimer (DD) for patient care. Our parent grant (1R18HS026196-01A1) proposed the use of two validated CPRs (Wells’ criteria and the IMPROVE model) within the context of a novel CDSS, building on a SOA that will function across multiple electronic health record (EHR) platforms. We will build upon our original idea by refining and validating the Wells’ criteria in the ED and IMPROVE-DD risk model in hospitalized COVID-19 patients and then implementing the CDS by utilizing the groundwork set forth within the platform we are currently developing for the parent grant. This work is significant because CPRs for VTE assessment are essential but have not been established or validated in COVID-19 patients. We are uniquely suited to perform this work at Northwell Health as we are at the forefront of fighting the pandemic, having treated over 150,000 COVID-19 patients with subsequent performance of high-level big data analysis on this cohort and are well positioned for appropriate validation and subsequent implementation of VTE risk assessment. The long-term goal of this project is implementation of evidence-based CDS tools on a widely disseminated platform to meaningfully inform universal VTE management of COVID-19 patients.
项目摘要 由深静脉血栓形成(DVT)和肺部组成 栓塞(PE)是一种致命疾病 和29%。由于VTE引起的并发症,这种关注随着最近的大流行而增加 与2019年冠状病毒病患者的40%死亡有关(COVID-19)。这 该提案的总体目的是:1)改进和验证两个临床预测规则(CPR)进行评估 在与Covid-19和2的紧急部门(ED)出现或接纳的患者中的VTE 根据这些设计,执行可用性测试并实施两个临床决策支持(CD)工具 我们的小说,创新的面向服务的建筑(SOA)的复杂CDS系统(CDSS)中的CPR。 Wells的标准与D-Dimer结合使用是CPR,可帮助医疗保健提供者排除PE和 需要不必要的计算机断层扫描肺血管造影(CTPA)。另外,急性ill 住院的医疗患者在住院期间患VTE事件的中等风险。 住院的Covid-19患者的VTE风险特别高,最近的报告表明患病率是 在ICU设置中,医疗病房的DVT高达46%,PE高达42%。这些数据与 VTE风险与以前的病毒性肺炎相关的风险,例如H1N1,这些风险已显示出23倍的风险 对于VTE。 Thrombo-Prophylaxis在院内显示出明显的好处,但必须适当使用 因为它具有与出血有关的发病率和死亡率的风险。入院患者的VTE风险很难 评估和医生依靠CPRS,例如改善D-Dimer(DD)进行患者护理。 我们的父母赠款(1R18HS026196-01A1)建议使用两个经过验证的CPR(Wells的标准和 改进模型)在新颖的CDS的背景下,建立在SOA上,该SOA将在多个跨多个 电子健康记录(EHR)平台。我们将通过完善和验证来建立我们的原始想法 在住院的Covid-19患者中,Wells的ED和Revor Revor-DD风险模型的标准,然后 通过使用我们目前正在开发的平台内列出的基础工作来实施CD 父母赠款。这项工作很重要,因为用于VTE评估的CPR是必不可少的,但尚未 在Covid-19患者中建立或验证。我们非常适合在Northwell Health进行这项工作 由于我们处于与大流行作斗争的最前沿,因此已经治疗了150,000多名Covid-19患者 随后在此队列上进行高级大数据分析的性能,并且可以很好地定位 验证和随后实施VTE风险评估。 该项目的长期目标是在广泛地实施基于证据的CDS工具 传播平台可有意义地为COVID-19患者提供通用的VTE管理。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

THOMAS G MCGINN其他文献

THOMAS G MCGINN的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('THOMAS G MCGINN', 18)}}的其他基金

Spread the Word: Integrating Clinical Prediction Rules at the Point of Care
传播信息:在护理点整合临床预测规则
  • 批准号:
    8473499
  • 财政年份:
    2013
  • 资助金额:
    $ 40万
  • 项目类别:
Spread the Word: Integrating Clinical Prediction Rules at the Point of Care
传播信息:在护理点整合临床预测规则
  • 批准号:
    8628071
  • 财政年份:
    2013
  • 资助金额:
    $ 40万
  • 项目类别:
Spread the Word: Integrating Clinical Prediction Rules at the Point of Care
传播信息:在护理点整合临床预测规则
  • 批准号:
    8811447
  • 财政年份:
    2013
  • 资助金额:
    $ 40万
  • 项目类别:
Evidence Based Decision Making: Integrating Clinical Prediction Rules into Electr
基于证据的决策:将临床预测规则集成到 Electr 中
  • 批准号:
    8080374
  • 财政年份:
    2009
  • 资助金额:
    $ 40万
  • 项目类别:
Evidence Based Decision Making: Integrating Clinical Prediction Rules into Electr
基于证据的决策:将临床预测规则集成到 Electr 中
  • 批准号:
    7938103
  • 财政年份:
    2009
  • 资助金额:
    $ 40万
  • 项目类别:
Evidence Based Decision Making: Integrating Clinical Prediction Rules into Electr
基于证据的决策:将临床预测规则集成到 Electr 中
  • 批准号:
    8262455
  • 财政年份:
    2009
  • 资助金额:
    $ 40万
  • 项目类别:
Prevention of Depression in HIV/HCV co-infected Substance Abuse Patients
预防 HIV/HCV 合并感染药物滥用患者的抑郁症
  • 批准号:
    7119895
  • 财政年份:
    2006
  • 资助金额:
    $ 40万
  • 项目类别:
Prevention of Depression in HIV/HCV co-infected Substance Abuse Patients
预防 HIV/HCV 合并感染药物滥用患者的抑郁症
  • 批准号:
    7296140
  • 财政年份:
    2006
  • 资助金额:
    $ 40万
  • 项目类别:
Primary Care Practice-Based Research Network
初级保健实践研究网络
  • 批准号:
    6447256
  • 财政年份:
    2000
  • 资助金额:
    $ 40万
  • 项目类别:
RESIDENCY TRAINING IN GIM AND/OR GIP
GIM 和/或 GIP 的住院医师培训
  • 批准号:
    2432349
  • 财政年份:
    1993
  • 资助金额:
    $ 40万
  • 项目类别:

相似国自然基金

novel-miR75靶向OPR2,CA2和STK基因调控人参真菌胁迫响应的分子机制研究
  • 批准号:
    82304677
  • 批准年份:
    2023
  • 资助金额:
    30.00 万元
  • 项目类别:
    青年科学基金项目
海南广藿香Novel17-GSO1响应p-HBA调控连作障碍的分子机制
  • 批准号:
    82304658
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
白术多糖通过novel-mir2双靶向TRADD/MLKL缓解免疫抑制雏鹅的胸腺程序性坏死
  • 批准号:
  • 批准年份:
    2021
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
novel-miR-59靶向HMGAs介导儿童早衰症细胞衰老的作用及机制研究
  • 批准号:
    32171163
  • 批准年份:
    2021
  • 资助金额:
    58.00 万元
  • 项目类别:
    面上项目

相似海外基金

Maternal Fetal Medicine Units Network: University of California, San Francisco
母胎医学单位网络:加州大学旧金山分校
  • 批准号:
    10682872
  • 财政年份:
    2023
  • 资助金额:
    $ 40万
  • 项目类别:
P-KIDs CARE: An Intervention to Address Health Systems Delays to Care for Injured Children in Tanzania
P-KIDs CARE:解决坦桑尼亚卫生系统延误照顾受伤儿童的干预措施
  • 批准号:
    10722628
  • 财政年份:
    2023
  • 资助金额:
    $ 40万
  • 项目类别:
Personalized End of Life Care in Safety-Net hospitals: Implementation of the 3 Wishes Project
安全网医院的个性化临终关怀:实施“三个愿望”项目
  • 批准号:
    10736466
  • 财政年份:
    2023
  • 资助金额:
    $ 40万
  • 项目类别:
A randomized clinical trial of client-centered care coordination to improve pre-exposure prophylaxis use for Black men who have sex with men
一项以客户为中心的护理协调的随机临床试验,以改善男男性行为黑人的暴露前预防使用
  • 批准号:
    10762186
  • 财政年份:
    2023
  • 资助金额:
    $ 40万
  • 项目类别:
Optimizing Care for Older Adults through Thyroid Hormone Deprescribing
通过减少甲状腺激素处方来优化老年人的护理
  • 批准号:
    10733478
  • 财政年份:
    2023
  • 资助金额:
    $ 40万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了