A Pragmatic Trial Evaluating the Impact of the Anumana Clinical Decision Support Tool for Guideline-Directed Management of Heart Failure (ACT-HF): Clinical trial design and methods

一项评估Anumana临床决策支持工具在心力衰竭指南指导管理中作用的实用性试验(ACT-HF):临床试验设计和方法

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Abstract

BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) is progressive and pervasive. Guidelines provide evidence-based recommendations to manage HFrEF, yet adherence to Guideline Directed Medical Therapy (GDMT) is low. An opportunity exists to improve adherence by delivering actionable data, reducing clinician information overload, and enhancing patient care. A Pragmatic Trial Evaluating the Impact of the Anumana Clinical Decision Support Tool for Guideline-Directed Management of Heart Failure (ACT-HF) will evaluate a clinical decision support software (CDSS) that integrates in electronic health records (EHR), automates chart review, and identifies care gaps. METHODS: Anumana's Guideline Navigator is an innovative, multi-module AI-enabled CDSS with automated chart review to rapidly analyze EHR data, detect care gaps, and provide alerts for eligible patients not receiving optimal GDMT. ACT-HF, a multi-center cluster pragmatic trial, will recruit and randomize clinician participants (≤250) from 2 health systems to receive intervention software or provide usual care. The trial will evaluate outpatient care for adults with documented HFrEF and not on optimal GDMT (>2148). Outcomes will be evaluated at 90 days. Clinician participants may discuss results with patients, but patients will not have access to the CDSS. RESULTS: Primary outcome is change in GDMT medications; exploratory endpoints include clinical outcomes, resource utilization, and usability. Subgroup analyses include health system, clinician, and patient-level characteristics associated with outcomes. CONCLUSION: Building on efforts to improve GDMT adherence, ACT-HF will test Anumana's Guideline Navigator in a multicenter study to evaluate outcomes and further refine the CDSS EHR integration EHR for improved clinical utility, workflow integration, and patient outcomes.

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