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Risk EValuation And its Impact on ClinicAL Decision Making and Outcomes in Heart Failure: The REVeAL-HF Trial

Acute heart failure is the most common cause of hospitalizations in the United States with an associated mortality that exceeds most cancers. Readmission rates are remarkably high, with nearly 50% patients hospitalized within 6 months of discharge. Despite this, most studies examining strategies to improve clinical outcomes have failed. A key reason for our inability to meaningfully improve patient outcomes is the lack of personalizing interventions to the individual patient. Due to their heterogeneous nature, commonly used clinical descriptors such as New York Association (NYHA) Class or Left Ventricular Ejection Fraction (LVEF) are imprecise predictors of disease progression. Several risk scores have been developed, but their impact on clinical decision making has never been evaluated. This gap between accurate prognostication and clinical decision-making results in misutilization of therapies. We hypothesize that giving providers accurate information about their heart failure patient's prognosis will improve use of appropriate interventions and result in better clinical outcomes.

Despite the availability of several risk scores in heart failure, no prior study has examined the impact of prognostic information on clinical decision making on patient outcomes. In order to address this gap in knowledge, we are undertaking the Risk EValuation and its Impact on ClinicAL Decision Making and Outcomes in Heart Failure: REVeAL-HF Clinical Trial (NCT03845660) across the 5 hospitals that comprise the Yale New Haven Health System. REVeAL-HF is a pragmatic randomized controlled trial testing an electronic alert system that informs practitioners about their acute heart failure patient's inpatient and 1-year predicted mortality using validated data from the electronic health record along with a best practice alert with guidelines for heart failure management. We are examining the impact of this information on rates of post discharge hospitalization, all-cause mortality, length of stay, use of pharmacotherapies, referral to electrophysiology, palliative care referral, and use of advanced therapies like heart transplantation or mechanical circulatory support.

Leadership

Collaborators

Yu Yamamoto
Statistician, Yale University

Publications