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

项目总结 心力衰竭(HF)是美国老年人中最常见、最昂贵的慢性病之一。 服药依从性是心力衰竭患者长期自我管理的关键组成部分，并与 改善症状管理、身体功能和并发症的复发。尽管井很好- 已有证据表明，坚持用药可以改善心力衰竭的预后，只有一半的心力衰竭患者实现了 有足够的服药依从性。尽管临床指南强调用药的长期益处 对于HF结果的坚持，我们缺乏可操作时间点的关键知识(S)来有效地推动 在病程中坚持用药。到目前为止，目前关于心力衰竭患者依从性的研究有 很大程度上忽略了随着时间的推移依从性的异质性模式，并且与药物类别无关。 事实上，有证据表明，短期和长期坚持模式的差异 用药可能与患者的重要特征有关。因此，迫切需要 根据用药类别对依从性的纵向模式进行准确分类，并了解其影响因素 与心力衰竭患者不同的依从性有关。这些信息对于开发和开发 实施量身定制的干预措施，以提高这一弱势群体的遵从性。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-基于群的轨迹 模型-并利用两个国家数据集的优势：(A)医疗保险索赔数据，和(B)健康和 退休研究(HRS)。在这样做时，我们对当前提案的总体目标有两个。第一，链接 根据医疗保险声称的HRS数据，我们将首先对指南的用药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)分别用于心力衰竭患者。然后我们将同时检查 跨药物类别的依从性的纵向模式(即基于组的多轨迹)。第二, 在世界卫生组织坚持模式的指导下，我们将首先检查患者的人口统计数据， 当时的社会经济状况、患者、病情、治疗和医疗保健系统的相关特征 心力衰竭的诊断与我们在目标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与将患者分配到特定轨迹的关系 药物依从性。我们将检查与每一类药物的轨迹相关的因素 以及影响患者多类轨迹的因素。这项研究的结果将提供 未来大规模提案的重要科学基础，以制定量身定制的战略以改善 依从性根据确定的、可预测的疾病轨迹时间点。

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.