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

项目摘要 心力衰竭（HF）是美国老年人中最常见和最昂贵的慢性疾病之一。 药物依从性是HF患者长期自我管理的关键组成部分， 改善症状管理、身体功能和并发症复发。尽管如此- 已有证据表明，药物依从性改善了HF的结局，但只有一半的HF患者达到了 适当的药物依从性。尽管临床指南强调药物治疗的长期益处 对于HF结局的依从性，我们缺乏可操作时间点的关键知识，以有效促进 在患病期间坚持服药。迄今为止，目前关于HF患者依从性的研究 在很大程度上忽略了随时间推移的异质性坚持模式，并且对药物类别不可知。 事实上，有证据表明，短期和长期的模式的差异，坚持某些 药物可能与重要的患者特征相关。因此，迫切需要 根据药物类别对依从性的纵向模式进行准确分类， 与HF患者不同的依从性模式相关。这些信息对于开发和 实施有针对性的干预措施，以提高这一弱势群体的依从性。为了弥补这一差距， 知识，我们建议进行一系列的分析，使用一种新的方法-基于组的轨迹 模型，并利用两个国家数据集的优势：（a）医疗保险索赔数据，（B）健康和 退休研究（HRS）。在这样做时，我们目前提案的总体目标是双重的。第一，链接 医疗保险声称HRS数据，我们将首先对指南的药物依从性轨迹进行分类- 推荐的药物类别（血管紧张素转换酶抑制剂[ACEI] /血管紧张素II受体 受体阻滞剂[ARB]和β受体阻滞剂）。然后我们将同时检查 跨药物类别的纵向依从性模式（即基于组的多轨迹）。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， 社会经济状况、患者、病情、治疗和医疗保健系统相关特征 HF诊断与我们在目标1中确定的药物依从性的轨迹类型学相关。我们 然后将评估这些因素的变化如何与患者的某些轨迹分配相关， 药物依从性。我们将检查与每类药物的轨迹相关的因素 以及导致患者多类轨迹的因素。这项研究的结果将提供 这是未来制定量身定制的战略以改善 根据疾病轨迹中确定的、可预测的时间点进行依从性。

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.