Medications and the Risk of Motor Vehicle Crashes in Older Adults

老年人的药物和车祸风险

• 批准号: 10425421
• 负责人: Andrew Reis Zullo
• 金额: $ 44.14万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10425421
• 关键词: Accident and Emergency department; Accounting; Acetylcholinesterase Inhibitors; Address; Adherence; Adult; Affect; Age; Aging; Alzheimer' s disease related dementia; Antidepressive Agents; Antipsychotic Agents; Automobile Driving; Belief; Biological; Central Nervous System Stimulants; Cessation of life; Characteristics; Cholinesterase Inhibitors; Counseling; Data; Data Set; Databases; Dose; Drowsiness; Drug Prescriptions; Drug usage; Elderly; Ensure; Equilibrium; Frequencies; Future; Goals; Health; Health Insurance; Impairment; Individual; Intervention; Lead; Licensing; Link; Medical; Medicare; Medication Management; Mental Depression; Mental disorders; Methods; Morbidity - disease rate; Motor Vehicles; Musculoskeletal Diseases; National Institute on Aging; Neuraxis; Non-Steroidal Anti-Inflammatory Agents; Observational Study; Opioid; Opioid Analgesics; Outcome; Patients; Personal Satisfaction; Pharmaceutical Preparations; Physical Function; Physiological; Play; Policy Making; Polypharmacy; Population; Prevalence; Psychomotor Impairments; Psychotropic Drugs; Randomized Controlled Trials; Recording of previous events; Research; Risk; Role; Safety; Schizophrenia; Sensory; Sleep; Sleep Disorders; Social isolation; Source; Stimulant; Subgroup; Testing; Time; Vehicle crash; Work; age related; aging in place; cognitive function; data resource; driving safety; epidemiologic data; evidence base; experience; human old age (65+); hypnotic; improved; innovation; longitudinal database; medication compliance; mortality; multiple chronic conditions; nervous system disorder; novel; older driver; preservation; primary outcome; response; sedative; therapy development; time use; transportation access; unsafe driving

PROJECT SUMMARY Despite the common belief that prescription drug use is a leading cause of motor vehicle crashes, data are scarce and controversy remains about the effects of medications on crashes in older adults aged ≥65 years. Unlike other determinants of crashes (e.g., medical conditions), medications are one of few modifiable potential determinants of the 6,800 crash-related deaths and 191,000 crash-related non-fatal injuries that occur annually among older adults. In particular, psychoactive drugs are commonly used among older drivers, but may interfere with safe driving. As more adults continue to drive into older age, there is an urgent need to understand the effects of medications and distinguish them from the effects of contemporaneous age-related medical conditions, impairments, and physiological changes. The overall objective of this proposal is to examine the causal effects of medications on crashes in older drivers, and the extent to which these medications disproportionately affect crash risk across subgroups [e.g., Alzheimer's disease and related dementias (ADRD), polypharmacy] and by medication adherence status. The central hypothesis is that sedating psychoactive medications (opioids, nonbenzodiazepine hypnotics, antidepressants, and antipsychotics) will increase crash risk while central nervous system (CNS)-activating drugs (cholinesterase inhibitors, CNS simulants) and others (non-steroidal anti- inflammatory drugs) will decrease the risk, and that these effects will be greatest among individuals with ADRD and those who are adherent to their medications. This hypothesis will be tested by pursuing three specific aims: 1) Estimate the effect of initiating sedating psychoactive, CNS-activating, and other medications, including dose, on crashes in older adults; 2) Quantify the effect of initiating sedating psychoactive, CNS-activating, and other medications on crashes across important subgroups of older adults, including those with ADRD; polypharmacy; multimorbidity; and sleep, psychiatric, neurological, and musculoskeletal disorders; and 3) Evaluate the effect of non-adherence to sedating psychoactive, CNS-activating, and other medications, each separately compared to adherence, on crash risk. To accomplish the three aims, our team will develop a unique database that combines data on older drivers' licensing and crash histories; Medicare health insurance and drug claims; and data on important determinants of medication use and crashes (e.g., access to transportation alternatives). This approach is innovative because it is the first to compile high-quality U.S. data on all three domains necessary to study the effect of medications on crashes—1) medical conditions (covariates); 2) medication use (exposure); and 3) crashes (outcome)—in a dataset that is large enough to precisely estimate effects using causal inference methods while accounting for differential driving frequency between drivers. The proposed research is significant because: 1) it will provide empirical evidence to help guide the management of medications to maximize older adults' ability to maintain safe mobility; and 2) it will establish a unique large data resource that can be used to conduct important future medication-related studies of older drivers. This proposal is responsive to PA-17-088.

项目概要 尽管人们普遍认为处方药的使用是机动车事故的主要原因，但数据显示 关于药物对 65 岁以上老年人车祸的影响，这一点还很稀缺且存在争议。 与车祸的其他决定因素（例如医疗状况）不同，药物是少数可以改变的因素之一 每年发生 6,800 起事故相关死亡和 191,000 起事故相关非致命伤害的决定因素 在老年人中。特别是，老年驾驶员普遍使用精神活性药物，但可能会干扰 安全驾驶。随着越来越多的成年人继续步入老年，迫切需要了解 药物的影响并将其与同时期与年龄相关的医疗状况的影响区分开来， 损伤和生理变化。该提案的总体目标是检查因果影响 药物对老年驾驶员车祸的影响，以及这些药物对车祸的影响程度 跨亚组的崩溃风险[例如阿尔茨海默氏病和相关痴呆症 (ADRD)、多药治疗] 药物依从性状态。中心假设是镇静精神活性药物（阿片类药物、 非苯二氮卓类安眠药、抗抑郁药和抗精神病药）会增加撞车风险，而中枢性 神经系统 (CNS) 激活药物（胆碱酯酶抑制剂、CNS 模拟剂）和其他药物（非甾体类抗 炎症药物）会降低风险，并且这些影响在 ADRD 患者中最为明显 以及那些坚持服药的人。这一假设将通过追求三个具体目标来检验： 1) 估计开始镇静精神活性药物、中枢神经系统激活药物和其他药物的效果，包括剂量、 关于老年人的碰撞事故； 2) 量化启动镇静、精神活性、中枢神经系统激活和其他药物的效果 针对老年人重要亚群（包括 ADRD 患者）的崩溃药物；多药治疗； 多重病态；以及睡眠、精神、神经和肌肉骨骼疾病； 3) 评估效果 不坚持使用镇静精神药物、中枢神经系统激活药物和其他药物，分别与 遵守，关于崩溃风险。为了实现这三个目标，我们的团队将开发一个独特的数据库，该数据库结合了 有关老年驾驶执照和碰撞历史的数据；医疗保险健康保险和药物索赔；和数据 药物使用和事故的重要决定因素（例如，获得替代交通方式）。这 该方法具有创新性，因为它是第一个汇编美国所有三个领域所需的高质量数据的方法。 研究药物对车祸的影响——1) 医疗状况（协变量）； 2) 药物使用（暴露）； 3) 崩溃（结果）——在足够大的数据集中，可以使用因果推理精确估计影响 方法，同时考虑驾驶员之间的驾驶频率差异。拟议的研究意义重大 因为：1）它将提供经验证据来帮助指导药物管理，以最大限度地提高老年人的寿命 成年人保持安全行动的能力； 2）它将建立一个独特的大数据资源，可用于 对老年驾驶员进行重要的未来药物相关研究。该提案是对 PA-17-088 的回应。