HeakHeart Phase 1 Proof of Concept Study
HeakHeart Phase 1 Proof of Concept Study
This pilot study will test the feasibility of a novel digital health technology-enabled platform, HekaHeart, developed to facilitate comprehensive medical management, including medication initiation, titration, e-prescription eligibility, remote patient monitoring, and communication of care coordination activities, for patients with Heart Failure with Reduced Ejection Fraction (HFrEF) not currently on all four pillars of guideline-directed medical therapy (GDMT).
Heart Failure (HF) is a major cause of morbidity, mortality, and healthcare expenditure in the United States (US). The 2022 AHA/ACC/HFSA Guideline for the management of HF strongly recommends quadruple therapy for all patients with HFrEF, which includes: beta-blockers (BB); renin-angiotensin-aldosterone-system (RAAS) inhibitors such as angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB) and angiotensin receptor-neprilysin inhibitors (ARNi); mineralocorticoid receptor antagonists (MRA); and sodium-glucose cotransporter-2 inhibitors (SGLT2i). Unfortunately, suboptimal adoption of GDMT persists despite mounting, unambiguous evidence of its substantial benefit on patient outcomes (including mortality) across numerous large-scale studies.
Further, following initial prescription of quadruple therapy, augmentation of each pillar to target or highest tolerated dosing is critical to achieve maximum benefit, as shown in a recent multinational randomized controlled trial (STRONG-HF) where rapid uptitration to optimal doses of GDMT reduced the risk of death and hospitalization just 180 days after an acute HF episode. Yet, multiple contemporary registry studies continue to reflect suboptimal uptake and dose escalation of GDMT for patients with HFrEF in real-world clinical practice due to both clinical and patient-based barriers.
The HekaHeart platform is a comprehensive remote care and monitoring-based method for GDMT titration and management. The platform uses a virtual team of clinicians with expertise in HF to manage GDMT prescription, dose escalation, and symptom monitoring for patients with HFrEF as a means to both provide personalized patient care and support while alleviating clinician burden. Once a patient is fully optimized with respect to GDMT, they are transitioned back to routine clinical care.
The present study will evaluate the usability of the HekaHeart platform to initiate, monitor, and manage GDMT for patients with HFrEF. The study will prospectively recruit eligible patients from ambulatory HF clinics affiliated with Yale New Haven Health System (YNHHS). Consented patients will be onboarded to the HekaHeart platform for GDMT management by HF disease management clinicians, which will include medication adjustment and remote patient monitoring to assess laboratory results, changes in body weight, blood pressure, and heart rate. Throughout the study, patients will engage in short message service (SMS), video and phone check-ins with clinicians, who will leverage standardized titration protocols to guide medication optimization, monitor patient progress and symptoms, and collect, analyze and respond to remote monitoring data. After 45 days, patients will be transitioned back to usual care.
The primary outcome is the Net Promoter Score (NPS), collected at study offboarding by each participant, and used to assess patient satisfaction with the HekaHeart platform and experience. The secondary outcome is the increase in proportion of HFrEF patients prescribed four pillars of GDMT. Other secondary endpoints include percent of patients successfully onboarded to the HekaHeart platform, proportion of patients whose GDMT is titrated toward target or maximally tolerated dosing, number scheduled visits attended, and percent of platform GDMT recommendations implemented.
Inclusion Criteria:
Documentation of HFrEF as evidenced by the presence of LVEF ≤40% reading at any time within the last 12 months,
Currently receiving care at YNHHS
Currently not on all 4 recommended classes of GDMT (BB, ACEi/ARB/ARNi, MRA, and SGLT2i)
Exclusion Criteria: