# Implementing a digitally-enabled community health worker intervention for patients with heart failure > **NIH NIH K23** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $197,243 ## Abstract Project Summary/Abstract Heart failure (HF) 30-day readmissions generate over a third of HF healthcare costs in the US and are the leading cause of US 30-day readmissions. Drivers of HF readmissions include increasing complexity associated with clinical, social, and behavioral factors. Despite numerous interventions, readmission rates remain elevated and a quarter of these could be prevented by a multidisciplinary approach promoting better connections to and communication with clinical care teams while addressing social and behavioral barriers to HF care. Community health workers (CHWs) are members of medical teams who address social, behavioral, and basic clinical factors influencing health outcomes while fostering patient connections to and communication with care teams. CHW care is one of a few interventions shown to reduce readmissions in patients with chronic disease. However, CHW care relies on intensive 1:1 patient care models that do not leverage technology which limits efficiency and scalability. There has been limited attention on developing technology-based interventions in CHW care to reduce HF 30-day readmissions. A HF mobile phone application-based digital platform that utilizes artificial intelligence driven biometric data to minimize false alarms, promotes early identification of true decline, and encourages communication with providers was developed in 2016 to reduce HF 30-day readmissions. Preliminary clinical trial data for the digital platform has been promising. A prototype designed for patients with HF and the CHWs caring for them has recently been created. The current proposal will assess the acceptability, feasibility, and preliminary effectiveness of a digitally-enabled CHW intervention to reduce HF 30-day readmissions. Aim 1: Identify behavioral (e.g., diet, activity) and social (e.g., socioeconomic status, social supports, living situation) factors that influence HF outcomes relevant to a digitally-enabled CHW intervention by performing semi-structured interviews with 30 patients with HF and 20 CHWs. Aim 2: Test usability of a digitally- enabled CHW intervention (focused on CHW workflow integration) in 10 patients with HF in an open pilot trial. Aim 3: Assess the acceptability, feasibility, and preliminary effectiveness of implementing a digitally-enabled CHW intervention compared to CHW care to reduce HF 30-day readmissions within a pilot RCT (n=50). The candidate’s overall career goals are: to identify social and behavioral drivers of HF/cardiovascular clinical outcomes; to develop expertise in qualitative methods, behavioral science, and RCTs; and ultimately, to develop interventions that improve care and reduce costs in HF/cardiovascular disease and other NHLBI diseases seen by generalists. This training plan includes strong mentorship, formal coursework, and scientific meetings with cohesive training in behavioral and social sciences, qualitative research, and the conduction of RCTs. This proposal investigates a po... ## Key facts - **NIH application ID:** 9871771 - **Project number:** 1K23HL150287-01 - **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL - **Principal Investigator:** Jocelyn Alexandria Carter - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $197,243 - **Award type:** 1 - **Project period:** 2020-01-15 → 2024-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9871771 ## Citation > US National Institutes of Health, RePORTER application 9871771, Implementing a digitally-enabled community health worker intervention for patients with heart failure (1K23HL150287-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9871771. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*