An Innovative Approach for Understanding Trajectories of Medication Adherence in Patients with Heart Failure

了解心力衰竭患者药物依从性轨迹的创新方法

• 批准号: 10054987
• 负责人: Hanzhang Xu
• 金额: $ 8.05万
• 依托单位: DUKE 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 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10054987
• 关键词: Address; Adherence; Adrenergic beta-Antagonists; American; Angiotensin II Receptor; Angiotensin-Converting Enzyme Inhibitors; Characteristics; Chronic Disease; Clinical; Data; Data Set; Data Sources; Diagnosis; Elderly; Exhibits; Foundations; Future; Goals; Guidelines; Health; Health and Retirement Study; Healthcare Systems; Heart failure; Hospitalization; Intervention; Knowledge; Link; Medicare claim; Methods; Mission; Modeling; National Institute on Aging; Organizational Models; Outcome; Patients; Pattern; Pharmaceutical Preparations; Physical Function; Recurrence; Regimen; Risk; Sampling; Science; Self Care; Self Management; Series; Socioeconomic Status; Time; Translational Research; Typology; United States; Vulnerable Populations; Work; World Health Organization; base; cost; demographics; effective intervention; improved; improved outcome; innovation; medication compliance; multidisciplinary; novel; symptom management; symptomatic improvement

PROJECT SUMMARY Heart failure (HF) is among the most common and costly chronic illnesses in older adults in the United States. Medication adherence is a critical component of long-term self-management in HF and is associated with improved symptom management, physical functioning, and the recurrence of complications. Despite the well- established evidence that medication adherence improves outcomes in HF, only half of patients with HF achieve adequate medication adherence. Although clinical guidelines emphasize the long-term benefits of medication adherence for HF outcomes, we lack critical knowledge of actionable time point(s) to effectively promote medication adherence during the course of illness. To date, current studies of adherence in HF patients have largely ignored heterogeneous patterns of adherence over time and are agnostic to the classes of medication. Indeed, there is evidence to suggest that differences in short- and long-term patterns of adherence of certain medications may be associated with important patient characteristics. Therefore, there are urgent needs to accurately classify longitudinal patterns of adherence based on medication class and to understand the factors associated with distinct patterns of adherence in patients with HF. This information is crucial for developing and implementing tailored interventions to improve adherence in this vulnerable population. To address this gap in knowledge, we propose to carry out a series of analyses that use a novel method—group-based trajectory models—and leverage the strengths of two national datasets: (a) Medicare claims data, and (b) the Health and Retirement Study (HRS). In doing so, our overall objectives for the current proposal are twofold. First, linking Medicare claims to the HRS data, we will first classify the medication adherence trajectories of the guideline- recommended classes of medications (angiotensin-converting enzyme inhibitors [ACEI] /angiotensin II receptor blockers [ARB], and Beta blockers) separately in patients with HF. We will then simultaneously examine the longitudinal patterns of adherence across the classes of medications (i.e. group-based multi trajectories). Second, guided by the World Health Organization model of adherence, we will first examine how patients’ demographics, socioeconomic status, patient-, condition-, therapy-, and healthcare system-related characteristics at the time of HF diagnosis are associated with trajectory typologies of medication adherence that we identified in Aim 1. We will then assess how changes in these factors are related to the assignment of a patient to certain trajectories of medication adherence. We will examine factors that are associated with trajectories for each class of medication as well as factors that are contributing to a patient’s multi-class trajectories. Results from this study will provide an important scientific foundation for a future large-scale proposal to develop tailored strategies to improve adherence according to identified, predictable time points in the illness trajectory.

项目摘要 心力衰竭（HF）是美国老年人中最常见，最昂贵的慢性疾病之一。 药物依从性是HF长期自我管理的关键组成部分，与 改善症状管理，身体功能和并发症的复发。尽管有很好的 确定的证据表明，药物依从性改善了HF的预后，只有一半的HF成就患者 尽管临床准则强调了药物的长期益处 遵守HF结果，我们缺乏对可行的时间点的批判性知识，无法有效地促进 疾病过程中的药物依从性。迄今为止，HF患者依从性的当前研究 随着时间的流逝，在很大程度上忽略了依从性的异质模式，对药物类别不可知。 确实，有证据表明，依从性的短期和长期模式的差异 药物可能与重要的患者特征有关。因此，迫切需要 根据药物类别准确对依从性的纵向模式进行分类，并了解因素 与HF患者的不同依从性模式有关。此信息对于开发和 实施量身定制的干预措施以提高这种脆弱人群的依从性。解决这个差距 知识，我们建议进行一系列使用新方法的分析 - 基于组的轨迹 模型 - 并利用两个国家数据集的优势：（a）Medicare索赔数据，以及（b）健康和健康 退休研究（HRS）。这样一来，我们目前提案的总体目标是双重的。首先，链接 Medicare索赔人力资源数据，我们将首先对指南的药物依从性轨迹进行分类 - 推荐的药物类（血管紧张素转换酶抑制剂[ACEI] /血管紧张素II接收器 HF患者分别是阻滞剂[ARB]和Beta阻滞剂）。然后，我们将简单地检查 在各种药物类别（即基于群体的多轨迹）之间依从性的纵向模式。第二， 在世界卫生组织依从性模型的指导下，我们将首先研究患者的人口统计学方法， 社会经济状况，患者，状况，治疗和与医疗系统相关的特征 HF诊断与我们在AIM 1中确定的药物依从性的轨迹类型有关。 然后将评估这些因素的变化如何与患者分配到某些轨迹 药物依从性。我们将检查与每种药物轨迹相关的因素 以及导致患者多级轨迹的因素。这项研究的结果将提供 未来大规模提议的重要科学基础，以制定量身定制的策略以改善 根据疾病轨迹中可预测的时间点的依从性。