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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要心力衰竭 (HF) 是美国老年人最常见且费用最高的慢性疾病之一。药物依从性是心力衰竭长期自我管理的关键组成部分，并且与尽管病情良好，但症状管理、身体机能和并发症的复发得到了改善。已有证据表明药物依从性可改善心力衰竭的预后，只有一半的心力衰竭患者达到尽管临床指南强调药物治疗的长期益处。坚持心衰结果，我们缺乏有效促进可采取行动的时间点的关键知识迄今为止，目前对心力衰竭患者依从性的研究已取得进展。在很大程度上忽略了随着时间的推移依从性的异质模式，并且与药物类别无关。事实上，有证据表明，短期和长期的某些坚持模式存在差异。药物可能与重要的患者特征相关，因此迫切需要进行药物治疗。根据药物类别准确分类纵向依从模式并了解因素与心力衰竭患者的不同依从性模式相关，这一信息对于开发和治疗至关重要。实施量身定制的干预措施，以提高这一弱势群体的依从性，以解决这一差距。知识，我们建议使用一种新方法——基于群体的轨迹——进行一系列分析模型——并利用两个国家数据集的优势：(a) 医疗保险索赔数据，以及 (b) 健康和退休研究 (HRS) 在此过程中，我们当前提案的总体目标有两个：首先，联系起来。 Medicare 对 HRS 数据的索赔，我们首先将指南的用药依从轨迹进行分类—— 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 受体然后，我们将同时检查心力衰竭患者的情况。跨类别药物的纵向依从模式（即基于群体的多轨迹）。在世界卫生组织的依从性模型的指导下，我们将首先研究患者的人口统计数据，失业状况、患者、病情、治疗和医疗保健系统相关特征心力衰竭诊断与我们在目标 1 中确定的药物依从性轨迹类型相关。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我们将检查与每类药物的轨迹相关的因素。以及影响患者多类别轨迹的因素本研究将提供结果。为未来制定量身定制的战略以改进的大规模提案奠定了重要的科学基础根据疾病轨迹中已识别的、可预测的时间点进行坚持。