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Significant high order drug interactions in the emergency department setting among older patient population

Significant high order drug interactions in the emergency department setting among older patient population
急诊科老年患者群体中存在显着的高阶药物相互作用
批准号:
10559571
负责人:
Macarius M. Donneyong
金额:
$52.69万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-02-01 至 2026-11-30

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中文摘要
翻译
老年人(≥65岁)约占美国人口的17%,但约占人口的57% 使用≥3种药物(多种药物)。目前,约有3000万美国成年人使用≥3种药物,这增加了他们的暴露 高阶药物相互作用(HDDI),即涉及≥3种药物的药物相互作用。HDDI是主要风险 导致急诊(艾德)就诊或住院的严重药物不良事件(ADE)因素。 与年轻人相比,老年人住院的可能性是年轻人的7倍, 去艾德急诊室检查然而,关于如何识别HDDI-ADE关联的知识, 不同3种药物组合的安全性比较以及HDDI的临床和药代动力学机制- ADE协会都非常有限。目前的项目旨在通过以下方式解决这些主要差距: 具体地说:(1)应用我们最先进的数据挖掘技术来发现与 较高的ADE风险以及与较低ADE风险相关的ADE风险;(2)进行比较安全性 评估涉及抗凝剂、抗糖尿病剂和阿片类药物的3种药物组合;以及(3)验证 并评价HDDI-ADE相关性的临床有效性和药理学机制。 这些目标将通过关注根据真实世界进行艾德访视的老年患者来实现 健康保险索赔数据(MarketScan和Medicare)和电子健康记录(EHR)数据。我们 将重点关注胃肠道(GI)出血、低血糖和阿片类药物诱导的ADE,作为 对这三个目标都感兴趣。这三种ADE占所有ADE诱导的艾德就诊的60%,是治疗目标 美国卫生与公众服务部的预防和监测优先事项。我们的初步数据来自 MarketScan声称,仅2012-2018年的数据就证实,老年人发生ADE的风险更高, 这些ADE的风险随着患者使用的伴随药物的数量而增加。我们将把我们的混合物 药物计数反应(MDCR)和图形模型,以确定特定的3-或4-药物组合, 老年人中艾德环境中ADE风险最高和风险最低的人群(目标1)。对于目标2, 将应用药物流行病学研究设计和因果推理方法来评估比较 特定高风险和低风险3种药物组合的安全性。我们将控制以下因素的潜在混杂效应: 多个患者水平(人口统计学、临床、慢性合并症、药物特征、医疗保健利用等) 和提供者/医疗保健系统水平的因素,以评估高风险与低风险之间的因果关系, 风险3-药物组合。最后,我们将使用临床专家团队来评估HDDI-ADE对, 从目标1和2中确定的临床有效性和实用性相关性。 识别高风险和低风险的3种药物组合是指导治疗的重要知识。 制定新的多药处方建议,以帮助解决重大的公共卫生问题 挑战来自于AD。
英文摘要
Older adults (≥65 years old) constitute about 17% of the US population but account for ~57% of the population who use ≥3 drugs (polypharmacy). Currently, ~30million US adults use ≥3 drugs which increase their exposure to high-order drug-drug interactions (HDDIs), i.e. drug-drug interactions involving ≥3 drugs. HDDI is a major risk factor of serious adverse drug events (ADEs) that result in emergency department (ED) visits or hospitalization. Older adults, compared to younger adults, are 7-times more likely to be hospitalized and 2 to 3-times more likely to visit the ED for ADEs. However, knowledge on how to identify HDDI-ADE associations, data on the comparative safety of different 3-drug combinations and clinical and pharmacokinetic mechanisms for HDDI- ADE associations are all critically limited. The current project is designed to address these major gaps by specifically: (1) applying our state-of-art data mining techniques to discover HDDIs that are associated with higher risk of ADEs as well as those associated with lower ADE risk; (2) performing a comparative safety assessment of 3-drug combinations involving anticoagulants, antidiabetic agents and opioids; and (3) validating and evaluating the clinical validity and pharmacologic mechanisms of HDDI-ADE associations. These aims will be implemented by focusing on older patients who had an ED visit based on real-world data from health insurance claims (MarketScan and Medicare) and Electronic Health Records (EHR) data. We will focus on gastrointestinal (GI) bleeding, hypoglycemia and opioid-induced ADEs as the primary ADEs of interest for all three aims. These three ADEs account for 60% of all ADE-induced ED visits and are a target priority for prevention and surveillance by the US Health and Human Services. Our preliminary data from the MarketScan claims data (2012-2018) alone has confirmed that older adults are at higher risk of ADEs and that the risk of these ADEs increase with the counts of concomitant drugs used by patients. We will apply our mixture drug-count response (MDCR) and graphical models to identify the specific 3- or 4-drug combinations that have the highest risk and those with the lowest risk of ADEs in ED settings among older adults (Aim 1). For Aim 2, we will apply pharmacoepidemiologic study designs and casual inference approaches to assess the comparative safety of specific high and low-risk 3-drug combinations. We will control for the potential confounding effects of several patient-level (demographic, clinical, chronic comorbidities, drug characteristics, healthcare utilization, etc) and provider/healthcare system-level factors to assess the causal associations between high-risk versus low- risk 3-drug combinations. Finally, we will use a clinician expert team to evaluate the HDDI-ADE pairs and associations identified from Aims 1 and 2 for clinical validity and utility. The identification of high- and low-risk 3-drug combinations is vital knowledge that could guide the development of new polypharmacy prescribing recommendations to help address the significant public health challenge created by ADEs.
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Significant high order drug interactions in the emergency department setting among older patient population
  • 批准号:
    10367528
  • 项目类别:
  • 资助金额:
    $37.93万
  • 财政年份:
    2022
  • 负责人:
    Macarius M. Donneyong
  • 依托单位:
海外基金