Product Details
HeartInsight — Being One Step Ahead Can Make All the Difference
HeartInsight shifts heart failure management from detection to prediction to allow clinical teams to focus their valuable time on those who need them the most.
Heart failure is a leading cause of hospitalizations, and each hospitalization reflects a deteriorating prognosis for the patient.1,2 Managing heart failure patients is complex and requires significant resources.3 Health care providers face the difficult tasks of reducing costs and preventing hospitalizations through early identification and care of at-risk patients.
HeartInsight is a premium remote heart failure management solution that identifies patients at higher risk of decompensation early on. HeartInsight predicts heart failure hospitalizations — automatically and with high sensitivity — by combining multiple parameters into a single composite score, leading to one actionable alert. Industrywide it has the lowest false-alert rate and provides the earliest notifications of silent clinical changes that may lead to heart failure hospitalizations.4,5
HeartInsight streamlines your work by accurately identifying at-risk patients early on, so you can proactively care for those who need you the most. This may ultimately result in improved patient outcomes, as well as reduced clinical burden and costs associated with heart failure management.
Predicting 2 out of 3 heart failure hospitalizations
Alert time (median)
Only 1 false alert every 17 months
HeartInsight shifts heart failure management from detection to prediction to allow clinical teams to focus their valuable time on those who need them the most.
For Identifying Patients at Higher Risk of Worsening Heart Failure
Receiving multiple inaccurate alerts with vague actionability is inefficient and time-consuming. HeartInsight is different: It provides a single alert to support confident decision making. This enables you to spend less time on false alerts and focus on the patients that need you most.
For Collecting Self-Assessment Information Relevant to Heart Failure
Engaging patients and contacting them to collect clinical information can be challenging and resource-intensive. The Patient App is designed to engage patients to provide behavioral and symptom information by automatically prompting collection of this data. This supports patient management and may free up your time for other tasks.
For Supporting Confident Decision Making
With a growing cardiac device population, gathering and interpreting data to determine patient status is becoming more cumbersome and complex. HeartInsight helps streamline this process by organizing information clearly and intuitively. Through incorporation of patient-reported data from the Patient App, HeartInsight enables you to correlate signs and symptoms – intended to support patient assessment.
For Initiating a Meaningful Change
Heart failure patients often present with serious complications, highlighting the need for proactive care. HeartInsight provides a predictive alert to give you more time for contacting patients and initiating meaningful change. This may improve patient outcomes and reduce costly hospitalizations.
SELENE HF Multi-Center Study
The SELENE HF study assessed more than 900 patients and validated that the HeartInsight algorithm provides sensitive and timely prediction of impending heart failure decompensation with a low false-alert rate.
Key Findings
All-in-One Alert
8 parameters combined into one score and trend.
HeartInsight’s sophisticated algorithm automatically combines 8 highly HF-relevant parameters in one score. When the score crosses a configurable threshold, HeartInsight provides a single, predictive alert identifying patients at higher risk of worsening heart failure. It is intended to allow clinical teams to care proactively and initiate a meaningful changes, even before patients may report symptoms.
This may ultimately result in improved patient outcomes, decreased clinical burden, and reduced costs associated with heart failure management.
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1. Ambrosy AP et al. The Global Health and Economic Burden of Hospitalizations for Heart Failure Lessons Learned From Hospitalized Heart Failure Registries. J Am Coll Cardiol 2014; 63:1123–33.; 2. Gheorghiade M et al. Pathophysiologic Targets in the Early Phase of Acute Heart Failure Syndromes. Am J Cardiol; 2005; 96:11G–17G.; 3. Ponikowski Pet al. HF preventing disease and death worldwide. ESC Heart Fail 2014 Sep;1(1):4–25.; 4. Comparison of alerting time in validation studies: D’Onofrio et al. Europace 2021 doi:10.1093/europace/euab170; Boehmer JP et al. J Am Coll Cardiol Heart Fail. 2017 Mar, 5 (3) 216–225; Cowie MR et al. European Heart Journal (2013) 34, 2472–2480 doi:10.1093/eurheartj/eht083.; 5. Comparison of false alert rate in validation studies: D’Onofrio et al. Europace 2021 doi:10.1093/europace/euab170; Boehmer JP et al. J Am Coll Cardiol Heart Fail. 2017 Mar, 5 (3) 216–225; Cowie MR et al. European Heart Journal (2013) 34, 2472–2480 doi:10.1093/eurheartj/eht083.; 6. D’Onofrio A et al. Combining home monitoring temporal trends from implanted defibrillators and baseline patient risk profile to predict heart failure hospitalisations: results from the SELENE HF study. Europace 2021 doi: 10.1093/europace/euab170.; 7. Home Monitoring daily parameters combined with 1 baseline risk stratifier based on the Seattle Heart Failure Model (Levy WC, Mozaffarian D, Linker DT, Sutradhar SC, Anker SD, Cropp AB, Anand I, Maggioni A, Burton P, Sullivan MD, Pitt B, Poole-Wilson PA, Mann DL, Packer M, 2006. The Seattle Heart Failure Model: Prediction of Survival in Heart Failure. Circulation, 113:1424-1433.); 8. Data on file.
* 42 days refers to median alert time.
** Available for Acticor/Rivacor, Ilivia Neo/Intica Neo, Ilivia/Intica /Inlexa -5 and -7 series ICD DX/DC and CRT-D.
*** Based on current standard practice and clinical judgement
Disclaimer: HeartInsight is approved and available in CE regions only.