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: 10624520
• 负责人: Andrew Reis Zullo
• 金额: $ 36.85万
• 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/10624520
• 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.

项目摘要 尽管人们普遍认为处方药的使用是导致机动车撞车的主要原因，但数据显示， 关于药物对≥65岁老年人撞车的影响，目前还缺乏相关研究，且存在争议。 不像其他崩溃的决定因素（例如，医疗条件），药物是为数不多的可改变的潜力之一 每年发生的6，800起与碰撞有关的死亡和191，000起与碰撞有关的非致命伤害的决定因素 在老年人中。特别是，精神药物通常用于老年驾驶员，但可能会干扰 安全驾驶。随着越来越多的成年人继续进入老年，迫切需要了解 药物的影响，并将其与同期年龄相关的医疗条件的影响区分开来， 损伤和生理变化。本建议的总体目标是研究因果效应 药物对老年驾驶员撞车的影响，以及这些药物对老年驾驶员撞车的影响程度 跨子组的碰撞风险[例如，阿尔茨海默氏病和相关痴呆症（ADRD），多种药物]和 药物依从性状态。中心假设是，镇静精神药物（阿片类药物， 非苯二氮卓类催眠药、抗抑郁药和抗精神病药）会增加撞车风险，而中枢神经系统 神经系统（CNS）激活药物（胆碱酯酶抑制剂，CNS模拟物）和其他（非甾体抗 炎性药物）将降低风险，并且这些作用在ADRD患者中最大 和那些坚持服药的人将通过追求三个具体目标来检验这一假设： 1)估计开始使用镇静精神活性药物、CNS激活药物和其他药物的效果，包括剂量， 2）量化开始使用镇静精神活性药物、CNS激活药物和其他药物的效果。 在老年人的重要亚组中，包括ADRD患者的药物治疗;多种药物治疗; 多发性硬化症;和睡眠，精神，神经和肌肉骨骼疾病;和3）评估的影响， 不依从镇静精神活性药物、CNS激活药物和其他药物，分别与 坚持，在崩溃的风险。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， 关于老年驾驶员执照和撞车历史的数据;医疗保险健康保险和药物索赔;以及 药物使用和崩溃的重要决定因素（例如，获得交通替代方案）。这 这种方法是创新的，因为它是第一个在所有三个领域汇编高质量的美国数据， 研究药物对车祸的影响-1）医疗条件（协变量）; 2）药物使用（暴露）; 和3）崩溃（结果）-在一个足够大的数据集中，使用因果推理精确估计效果 方法，同时考虑驱动器之间的差分驱动频率。所提出的研究是有意义的 因为：1）它将提供经验证据，帮助指导药物管理，以最大限度地提高老年人的健康水平。 成年人保持安全移动的能力; 2）它将建立一个独特的大型数据资源，可用于 对老年驾驶员进行重要的未来药物相关研究。本提案响应PA-17-088。