AI-written messages to help doctors treat heart failure with guideline medicines
Tests AI-written messages to cardiologists about heart failure medicine for adults.
Plain-language title generated from the registry record
Registry title: Targeted Artificial Intelligence Language mOdel Recommendations for Heart Failure (TAILOR-HF)
Key facts
- Where
- Boston, United StatesSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 18 and 85 years old?
Source: NCT07337577, who can take part
Where in United States
- Mass General BrighamBoston, United StatesTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Brigham and Women's Hospital
- Trial code
- NCT07337577
- Record updated
- 31 August 2026
- Original description
This study is an investigator-initiated, cluster-randomized implementation trial evaluating a large language model (LLM)-based clinical decision support (CDS) tool designed to improve guideline-directed medical therapy (GDMT) for adult patients with heart failure seen in outpatient cardiology clinics at Mass General Brigham.Read full original descriptionShow less
Large Language Model-Generated Messages to Improve Guideline-Directed Medical Therapy in Heart Failure
This study is an investigator-initiated, cluster-randomized implementation trial evaluating a large language model (LLM)-based clinical decision support (CDS) tool designed to improve guideline-directed medical therapy (GDMT) for adult patients with heart failure seen in outpatient cardiology clinics at Mass General Brigham.
For eligible heart failure encounters, the CDS tool reviews existing electronic health record (EHR) data, including diagnoses, medications, vital signs, laboratory results, and recent notes, and generates brief, clinician-facing messages suggesting opportunities to initiate or optimize GDMT and highlighting relevant safety considerations. Messages are delivered to cardiology providers via Epic InBasket and/or institutional email prior to scheduled visits. The tool is advisory only and cannot place orders or change medications automatically; all treatment decisions remain at the discretion of the treating clinician and patient.
Cardiology providers are assigned at the provider/clinic level to early implementation of the CDS tool versus usual care (no messages) during the initial phase. The primary outcome is GDMT optimization within 30 days of an index visit. Secondary outcomes include feasibility of CDS generation and delivery and a 30-day safety composite (e.g., heart failure hospitalization, acute kidney injury, hyperkalemia, hypotension or bradyarrhythmia plausibly related to GDMT).
Inclusion: Age ≥18 years; Scheduled outpatient visit with a participating cardiology provider in an MGB outpatient cardiology clinic; At least one prior cardiology clinic visit in the MGB system within the past 2 years; Diagnosis of heart failure by ICD code within the past 2 years; Heart failure diagnosis supported by at least one of the following:; Current or recent use of a loop diuretic; Left ventricular ejection fraction ≤40% on the most recent echocardiogram; Explicit documentation of heart failure diagnosis or heart failure signs/symptoms in a prior cardiology note.
Exclusion: Heart rate <50 beats per minute on the most recent recorded measurement; Known cardiac amyloidosis or hypertrophic cardiomyopathy; History of heart transplant or presence of a left ventricular assist device; Severe aortic stenosis, severe aortic insufficiency, or severe mitral stenosis on the most recent echocardiogram; Encounter occurs in an adult congenital heart disease clinic; eGFR <20 mL/min/1.73 m² on the most recent laboratory assessment; Systolic blood pressure <90 mmHg on the most recent recorded measurement.