Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure (REVeAL-HF)

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

Heart failure is a complex and heterogenous disease with mortality and morbidity that equals more cancers. Numerous studies have examined the ability to improve prognostication from heart failure, ranging from basic statistical methodologies to machine learning, with impressive improvements in both predictive indices. However, no study to date has examined, in a randomized fashion, the impact of providing prognostic information on provider behavior and downstream clinical outcomes. It is for this reason that the investigators plan to perform the Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure (REVeAL-HF) Trial within the Yale New Haven Health System. REVeAL-HF is a randomized, single-blind intervention trial that is testing the clinical impact of providing prognostic information to the provider on heart failure outcomes in the inpatient settings. The study hypothesis is that electronic alerting about prognostic information on heart failure patients along with links to guidelines will lead to reductions in all-cause mortality and 30-day HF hospitalizations via improved use of guideline directed medical therapy and more adequate decongestion.

Heart failure is the major cause of mortality and morbidity in the United States and Western Europe and prognosis in individual patients is highly variable. Quantifying a patient's survival prospects based on their overall risk profile has the potential to help identify those patients in need of more intensive monitoring and help target appropriate populations for therapies. In fact, several comprehensive risk scores in patients with heart failure are currently available for both reduced and preserved ejection fraction but their applicability to contemporary heart failure populations is unknown. Additionally, the impact of knowing a patient's prognostic information on treatment decisions in heart failure has never been studied. Therefore, guidelines do not recommend using risk assessments to decide on therapeutic decision making in heart failure due to a lack of data for this strategy. The investigators have proposed a randomized controlled trial be conducted of an electronic alert system that informs practitioners about their patients risk of inpatient mortality and 1-year predicted mortality using data from the electronic health record (EHR). The primary outcome for the trial will be a composite of all-cause mortality and 30-day risk of heart failure rehospitalization. The secondary outcomes will be length of stay, discharge doses of heart failure therapies, palliative care referral, referral for advanced therapies like transplant or mechanical circulatory support, referral to electrophysiology, and change in weight during hospitalization (aggressiveness of diuresis). The investigators will enroll into the trial across the hospitals that comprise the Yale New Haven Health System.

Subjects will be recruited when electronically identified. The inclusion criteria will be all adults ≥18 years who have an NTproBNP levels of >500 pg/mL and received intravenous diuretics within 24 hours of admission within the YNHS. Patients randomized to the intervention will have an alert of their prognosis based on the best available prognostic models for inpatient and 1-year mortality generated with information from their electronic health record, which will consist of a "pop-up" when providers accesses a patient record to enter a progress note.

Providers taking care of patients randomized to this arm will have no alert related to the patients prognosis.

Patients randomized to the intervention will have an alert of their prognosis based on the best available prognostic models for inpatient and 1-year mortality generated with information from their electronic health record, which will consist of a "pop-up" when the provider accesses a patient record to enter a progress note after the definitions for inclusions into the study have been registered.

Patients randomized to the intervention will have an alert of their prognosis based on the best available prognostic models for inpatient and 1-year mortality generated with information from their electronic health record, which will consist of a "pop-up" when the provider accesses a patient record to enter a progress note after the definitions for inclusions into the study have been registered.

Referrals for advanced therapies like transplant or mechanical circulatory support will be collected and counted (number)

Inclusion Criteria: Age >18 NTproBNP levels of >500pg/mL within 24 hours of admission Intravenous diuretics within 24 hours of admission Exclusion Criteria: • None

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