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: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10559571
• 关键词: Accident and Emergency department; Address; Adult; Adverse drug event; Adverse event; Anticoagulants; Antidiabetic Drugs; Biological; Caring; Cause of Death; Characteristics; Chronic; Clinical; Clonidine; Data; Databases; Development; Diagnosis; Drug Combinations; Drug Interactions; Drug Kinetics; Drug usage; Elderly; Electronic Health Record; Emergency department visit; Exposure to; Fluconazole; Future; Gastrointestinal Hemorrhage; Goals; Health; Healthcare Systems; High Prevalence; Hospitalization; Hospitals; Human; Hypoglycemia; Impaired cognition; Indiana; Individual; Knowledge; Literature; Measures; Medicare; Methods; Modeling; Myopathy; Ohio; Omeprazole; Opioid; Patients; Pharmaceutical Preparations; Pharmacoepidemiology; Pharmacy facility; Polypharmacy; Population; Prevention; Procedures; Provider; Public Health; Publishing; Recommendation; Research; Research Design; Review Committee; Risk; Risk Factors; Safety; Services; Techniques; Therapeutic; Training; Treatment outcome; Visit; adjudication; comorbidity; comparative; comparative safety; data mining; design; drug misuse; frailty; health care service utilization; health data; high risk; human old age (65+); insurance claims; interest; older patient; patient population; patient safety; pharmacokinetic model; pharmacologic; physiologically based pharmacokinetics; population based; prevent; response; safety assessment; synergism; tool; young adult

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.

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（当前的多个药物）。 高阶药物相互作用（HDDIS），即药物相互作用≥3种药物。 严重不良药物事件（ADE）导致急诊科（ED）访问或住院的因素。 与年轻人相比，老年人要多7倍，要多7倍，可能会增加2至3倍的可能性 但是，要访问ED，以了解如何识别HDDI-ADE关联 HDDI-的不同3药物组合以及临床和药代动力学机制的比较安全性 ADE协会都是至关重要的。 具体来说：（1）应用我们的最先进的数据挖掘技术来发现与与之相关的HDDI。 ADE的风险较高，ADE风险较低； 评估3条抗凝剂，抗糖尿病药物和阿片类药物的组合； 并评估HDDI-ADE关联的临床有效性和药物学机制。 这些目标将通过聚焦于基于现实世界的ANED访问的老年患者来实现 来自健康保险索赔的数据（MarketScan和Medicare）和电子健康记录（EHR）数据 将专注于胃肠道（GI）出血，低血糖症和阿片类药物作为主要ADE 这三个目标的兴趣。 美国卫生和人类服务的预防和监视优先级。 MarketScan索赔数据（2012-2018）仅确认老年人的ADE风险很高，并且 这些地址的风险随患者使用的伴随药物的数量而增加。 药物计数响应（MDCR）和图形模型，以识别具有特定的3或4药物组合 最高的风险和在老年人中具有ED环境中ADS的风险的最高风险（AIM 1），我们是AIM 2。 将采用药物ePIDEMIologic研究设计和随意的Infhone Incasual推断来评估比较 特定的高和3级药物组合的安全性。 几个患者级（人口统计学利用等），医疗保健利用，医疗保健利用，健康特征，药物特征，药物特征，药物特征，药物特征 提供者/医疗保健系统级别的因素要评估以评估高风险与低点低点之间的因果关系 风险3级药物组合。 从目标1和2中确定的临床有效性和效用的关联。 高风险和低风险3级药物的识别是重要的知识，可以指导您 开发新的多药处方招聘建议，以帮助解决重大的公共卫生 ADE创造的挑战。