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

• ClinicalTrials.gov Identifier: NCT03845660
• Recruitment Status: Active, not recruiting
• First Posted: February 19, 2019
• Last Update Posted: February 25, 2021
• Sponsor: Yale University
• Information provided by (Responsible Party): Yale University

Study Description

Brief Summary:

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.

Condition or disease	Intervention/treatment	Phase
Heart Failure	Behavioral: Electronic Alert	Not Applicable

Detailed Description:

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.

Study Design

• Study Type: Interventional (Clinical Trial)
• Estimated Enrollment: 4000 participants
• Allocation: Randomized
• Intervention Model: Sequential Assignment
• Intervention Model Description: 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.
• Masking: Triple (Participant, Investigator, Outcomes Assessor)
• Primary Purpose: Other
• Official Title: The REVeAL-HF Trial: Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure
• Actual Study Start Date: January 1, 2020
• Estimated Primary Completion Date: December 30, 2022
• Estimated Study Completion Date: December 30, 2024

Arms and Interventions

Arm	Intervention/treatment
No Intervention: Usual Care; Providers taking care of patients randomized to this arm will have no alert related to the patients prognosis.
Experimental: Electronic Alert; 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.	Behavioral: Electronic Alert; 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.

Outcome Measures

Primary Outcome Measures :

1. All-Cause Mortality [ Time Frame: 1 Year ]
   All cause mortality will be monitored and reported.
2. Heart failure Re-hospitalization [ Time Frame: 30 Days Post Discharge ]
   30-day risk of heart failure re-hospitalization will be assessed and reported.

Secondary Outcome Measures :

1. Length of stay [ Time Frame: 1 Year ]
   Average length of stay will be collected in Days
2. Discharge doses of heart failure therapies [ Time Frame: 1 Year ]
   Discharge doses of guideline recommended heart failure therapies in milligrams (mg)
3. Palliative care referral [ Time Frame: 1 Year ]
   Palliative care referrals will be collected and counted (Number)
4. Advanced therapies referral [ Time Frame: 1 Year ]
   Referrals for advanced therapies like transplant or mechanical circulatory support will be collected and counted (number)
5. Electrophysiology referral [ Time Frame: 1 Year ]
   Referrals to electrophysiology will be collected and counted (number)
6. Weight Change [ Time Frame: 1 Year ]
   Weight change is defined as the change in weight during hospitalization (kg)

Eligibility Criteria

• Ages Eligible for Study: 18 Years and older (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Criteria

Inclusion Criteria:

• Age >18
• NTproBNP levels of >500pg/mL within 24 hours of admission
• Intravenous diuretics within 24 hours of admission

Exclusion Criteria:

• None

Contacts and Locations

Locations

United States, Connecticut

Yale New Haven Hospital

New Haven, Connecticut, United States, 06510

Sponsors and Collaborators

Yale University

Investigators

• Principal Investigator: Tariq Ahmad, MD MPH; Yale University
• Principal Investigator: Nihar R Desai, MD MPH; Yale University
• Principal Investigator: Francis P Wilson, MD MS; Yale University

More Information

Publications of Results:

Wilson FP, Greenberg JH. Acute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support. Nephron. 2018;140(2):116-119. doi: 10.1159/000492064. Epub 2018 Aug 2. Review.

Martin M, Wilson FP. Utility of Electronic Medical Record Alerts to Prevent Drug Nephrotoxicity. Clin J Am Soc Nephrol. 2019 Jan 7;14(1):115-123. doi: 10.2215/CJN.13841217. Epub 2018 Apr 5. Review.

Ahmad T, Freeman JV, Asselbergs FW. Can advanced analytics fix modern medicine's problem of uncertainty, imprecision, and inaccuracy? Eur J Heart Fail. 2019 Jan;21(1):86-89. doi: 10.1002/ejhf.1370. Epub 2018 Dec 10.

Ahmad T, Wilson FP, Desai NR. The Trifecta of Precision Care in Heart Failure: Biology, Biomarkers, and Big Data. J Am Coll Cardiol. 2018 Sep 4;72(10):1091-1094. doi: 10.1016/j.jacc.2018.07.009.

Ahmad T, O'Brien EC, Schulte PJ, Stevens SR, Fiuzat M, Kitzman DW, Adams KF, Kraus WE, Piña IL, Donahue MP, Zannad F, Whellan DJ, O'Connor CM, Felker GM. Evaluation of the Incremental Prognostic Utility of Increasingly Complex Testing in Chronic Heart Failure. Circ Heart Fail. 2015 Jul;8(4):709-16. doi: 10.1161/CIRCHEARTFAILURE.114.001996. Epub 2015 Jun 1.

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):

Ahmad T, Yamamoto Y, Biswas A, Ghazi L, Martin M, Simonov M, Hsiao A, Kashyap N, Velazquez EJ, Desai NR, Wilson FP. REVeAL-HF: Design and Rationale of a Pragmatic Randomized Controlled Trial Embedded Within Routine Clinical Practice. JACC Heart Fail. 2021 Jun;9(6):409-419. doi: 10.1016/j.jchf.2021.03.006. Epub 2021 May 12. Review.

• Responsible Party: Yale University
• ClinicalTrials.gov Identifier: NCT03845660
• Other Study ID Numbers: 2000025000
• First Posted: February 19, 2019
• Last Update Posted: February 25, 2021
• Last Verified: February 2021

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No
• Plan Description: Data will be housed at Yale University.

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Yale University:

Heart Failure; Prognosis; Electronic Alerts

Additional relevant MeSH terms:

Heart Failure; Heart Diseases; Cardiovascular Diseases