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

> **NIH NIH R03** · DUKE UNIVERSITY · 2020 · $80,500

## Abstract

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
adher...

## Key facts

- **NIH application ID:** 10054987
- **Project number:** 1R03AG064303-01A1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Hanzhang Xu
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $80,500
- **Award type:** 1
- **Project period:** 2020-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10054987

## Citation

> US National Institutes of Health, RePORTER application 10054987, An Innovative Approach for Understanding Trajectories of Medication Adherence in Patients with Heart Failure (1R03AG064303-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10054987. Licensed CC0.

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