# Personalized Patient data and behavioral nudges to improve adherence to chronic cardiovascular medications

> **NIH NIH UH3** · UNIVERSITY OF COLORADO DENVER · 2021 · $1,417,404

## Abstract

Abstract
Our objective in this project is to employ population level pharmacy data and delivery of nudges via cell phone
text messaging and artificially intelligent (AI) interactive chat bot to improve medication adherence and patient
outcomes in 3 integrated healthcare delivery systems (HCS): University of Colorado Health System
(UCHealth), VA Eastern Colorado Health Care System (VA), and Denver Health Medical Center (DH). We will
identify patients with chronic cardiovascular (CV) conditions taking medications to treat hypertension, atrial
fibrillation, coronary artery disease, diabetes and/or hyperlipidemia. We will leverage pharmacy refill data to
identify episodes of non-adherence through gaps in medication refills and randomize individuals to 1 of 4 study
arms when they have a first refill gap: 1) usual care; 2) generic text message reminder; 3) tailored and
engaging text messages optimized to facilitate behavior change; or 4) optimized text messages plus a pre-
programmed AI interactive chat bot designed to support identification and resolution of barriers to medication
refill and adherence. In the UG3 phase (year 1), we will develop and program a theoretically informed
technology-based (a) text message library and (b) chat bot content library using multiple and iterative N of 1
within subject studies to optimize content for a range of diverse patients. These outcomes will inform a pilot
intervention to demonstrate feasibility of delivering the intervention and preliminary effects in all 3 HCS. We will
also engage patient, provider and health systems stakeholders in designing, refining, and implementing the
pilot intervention. In the UH3 phase (years 2-5), we will conduct a pragmatic patient-level randomized
intervention across 3 HCS to improve adherence to chronic CV medications. We will evaluate the intervention
using a mixed methods approach and apply the RE-AIM (reach, effectiveness, adoption, implementation, and
maintenance) framework. In addition, we will assess the context and implementation processes to inform local
tailoring, adaptations and modifications, and eventual expansion of the intervention.

## Key facts

- **NIH application ID:** 10200136
- **Project number:** 5UH3HL144163-04
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** SHEANA S BULL
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,417,404
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10200136

## Citation

> US National Institutes of Health, RePORTER application 10200136, Personalized Patient data and behavioral nudges to improve adherence to chronic cardiovascular medications (5UH3HL144163-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10200136. Licensed CC0.

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