Automated Alerts for Heart Valve Issues

(ALERT Trial)

Recruiting at 5 trial locations

Overseen By Loren Wagner, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Tempus Labs

Disqualifiers: Age < 18, Prior valve repair, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: Unknown

2626 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if automated alerts sent to doctors help identify and treat individuals with serious heart valve issues, specifically aortic stenosis (narrowing of the aortic valve) and mitral regurgitation (leaking of the mitral valve). The trial compares two groups: one where doctors receive alerts and another where they do not. Ideal participants are those with echocardiogram results indicating possible severe heart valve problems, who have not yet undergone surgical treatment or scheduled a visit with a heart specialist. The goal is to assess whether these alerts lead to better follow-up care and necessary heart procedures. As an unphased trial, this study provides a unique opportunity to contribute to innovative research that could enhance heart care practices.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What prior data suggests that these automated alerts are safe for use in clinical settings?

Research has shown that automated alerts in healthcare effectively inform doctors about serious health issues. In a previous study, doctors responded to over 70% of these alerts, indicating that the system successfully captures healthcare providers' attention.

In this trial, the alerts aim to improve the treatment of heart valve problems, specifically severe aortic stenosis (AS) and mitral regurgitation (MR). While the alerts themselves don't pose safety concerns like medications might, they are crucial for ensuring patients receive timely care. No reports of safety issues have arisen from using these alerts. In fact, they are designed to help doctors act faster and more effectively, greatly benefiting patient care. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores a new protocol for managing heart valve issues using automated alerts. Unlike typical treatments that rely on regular check-ups and physical symptoms to identify problems, this approach sends real-time alerts to healthcare providers via electronic health records (EHR). This could lead to faster intervention, potentially improving patient outcomes by catching issues before they become more serious. The trial aims to find out if this method can enhance the standard of care by making heart valve monitoring more proactive and efficient.

What evidence suggests that automated alerts are effective for heart valve issues?

Research shows that automated alert systems can effectively notify doctors about serious health conditions, leading to faster responses and actions. In this trial, some care providers will receive automated alerts designed to quickly identify patients with severe heart valve problems, such as aortic stenosis (when the heart valve is too narrow) or mitral regurgitation (when the heart valve leaks). Previous studies have shown that when doctors receive these alerts, they are more likely to act quickly, which can lead to better patient outcomes. Tempus Next, the system used in this study, continuously monitors patient data and sends alerts to healthcare providers, helping them catch heart problems sooner. This kind of early warning has been linked to reducing the under-treatment of severe heart conditions. ^{1 2 4 6 7}

Who Is on the Research Team?

Wayne Batchelor, MD

Principal Investigator

Director of Interventional Cardiology Inova Heart and Vascular Institute

Are You a Good Fit for This Trial?

This trial is for patients with severe aortic stenosis (AS) or mitral regurgitation (MR), as indicated by specific measurements on an echocardiogram. It's not for those who don't meet the required echo criteria, such as AVA ≤ 1.0 cm2 or Dimensionless index ≤ 0.25 for AS, and certain criteria for MR.

Inclusion Criteria

My heart valve area is 1.2 cm2 or less.

My heart's aortic valve area or Doppler velocity index was measured.

My heart's aortic valve area and another echo measurement have been checked.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Automated alerts are sent to clinical providers to support identification and evaluation of patients for Valve Intervention (VI)

90 days

Ongoing monitoring through EHR

Follow-up

Participants are monitored for the impact of automated alerts on clinical follow-up and valve intervention rates

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Automated alert

Trial Overview

The study tests if automated alerts to doctors can reduce under-treatment of severe AS and MR by comparing follow-up rates and valve surgeries between two groups: one receiving alerts and one not.

How Is the Trial Designed?

Group I: Automated alert Experimental Treatment 1 Intervention

Providers that will receive an automated alert sent via the EHR.

Group II: Control Active Control 1 Intervention

Care providers in the control arm will not receive an automated alert.

Automated alert is already approved in United States for the following indications:

Approved in United States as Tempus Next for:

• Support for identification and evaluation of patients possibly indicated for Valve Intervention (VI)

Who Is Running the Clinical Trial?

Tempus Labs

Lead Sponsor

Trials

17

Recruited

20,200+

Tempus AI

Lead Sponsor

Trials

18

Recruited

20,700+

Medtronic

Industry Sponsor

Trials

627

Recruited

767,000+

Geoff Martha

Medtronic

Chief Executive Officer since 2020

Finance degree from Penn State University

Dr. Richard Kuntz

Medtronic

Chief Medical Officer since 2023

MD, MSc

Published Research Related to This Trial

Primary care practitioners (PCPs) received an average of 56.4 asynchronous electronic health record (EHR) alerts per day, which significantly contributes to their workload.

On average, PCPs spent about 49 minutes each day processing these alerts, highlighting the need for further investigation into the effectiveness and management of such alert systems.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Notifications received by primary care practitioners in electronic health records: a taxonomy and time analysis. Murphy, DR., Reis, B., Sittig, DF., et al.[2022]

The study presents an automated approach to managing communication modalities for event monitors, which simplifies the customization process for users and institutions, making it easier to handle multiple clinical conditions.

By using generic notification attributes and criteria, the system allows for more efficient assignment of alerts that are independent of specific clinical conditions, enhancing the reusability and sharability of the event monitor's knowledge base.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Extended attributes of event monitor systems for criteria-based notification modalities. Tao, Y., Wang, D., Shortliffe, EH., et al.[2018]

A new clinical alerting system has been developed to monitor laboratory results for both hospitalized and ambulatory patients in Israel, aiming to improve clinician response to critical results.

This system allows for customizable alerts based on individual clinician preferences and critical thresholds, enhancing its versatility and potential effectiveness in various medical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A comprehensive computerized critical laboratory results alerting system for ambulatory and hospitalized patients. Iordache, SD., Orso, D., Zelingher, J.[2008]

A survey of 30 medical centers revealed that 57% of them use electronic health record (EHR) alerts (e-alerts) for early detection of conditions like sepsis and pneumonia, indicating a proactive approach to patient safety in acute care settings.

Despite the widespread use of e-alerts, only 59% of the sites have assessed their accuracy or validity, highlighting a need for improved evaluation practices to ensure the effectiveness of these alerts in clinical decision-making.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The Nature and Variability of Automated Practice Alerts Derived from Electronic Health Records in a U.S. Nationwide Critical Care Research Network. Benthin, C., Pannu, S., Khan, A., et al.[2020]

In a study of 623 patients across ICU and general ward settings, automated trigger alerts for drug-related hazardous conditions (DRHCs) were found to be clinically significant in about 89% of cases in the ICU and 83% in general wards, indicating their effectiveness in both environments.

The positive predictive value (PPV) for alerts identifying DRHCs was 0.66 in the ICU and 0.76 in general wards, suggesting that while alerts are beneficial, there is room for improvement in their performance across both patient care settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of an automated surveillance system using trigger alerts to prevent adverse drug events in the intensive care unit and general ward. DiPoto, JP., Buckley, MS., Kane-Gill, SL.[2022]

Automated alerts and reminders for patients can significantly improve adherence to healthcare regimens, as shown in a review of 51 studies, indicating their effectiveness in fostering shared accountability for health outcomes.

These reminders can be personalized and are effective across various age groups, suggesting that as technology advances, their use will likely expand, leading to better patient management and potentially lower healthcare costs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Automated alerts and reminders targeting patients: A review of the literature. Perri-Moore, S., Kapsandoy, S., Doyon, K., et al.[2022]

A study analyzing interruptive alerts in electronic health records across 6 pediatric health systems from 2016-2019 found significant variation in alert burden, with custom alerts being the most frequent across all sites.

The choice of metric used to measure alert burden (such as alerts per patient encounter or alerts per clinician day) greatly influenced which provider types and care settings were identified as having the highest alert burden, highlighting the importance of metric selection in evaluating EHR alert systems.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Alert burden in pediatric hospitals: a cross-sectional analysis of six academic pediatric health systems using novel metrics. Orenstein, EW., Kandaswamy, S., Muthu, N., et al.[2022]

In a study analyzing 1012 medication regimens in a nephrology clinic, more specific alerting strategies significantly reduced the number of alerts generated, with the most advanced strategy (D) resulting in alerts for only 7.81% of regimens compared to 87.5% with the least specific strategy (A).

The findings suggest that using patient and drug-specific information in alert systems can effectively minimize alert fatigue among physicians, potentially improving the safety of prescribing medications to patients with renal impairment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease. Czock, D., Konias, M., Seidling, HM., et al.[2017]

A new alert system for inpatients successfully notified physicians about serious clinical conditions, with a high response rate of 70.2% to 1730 alerts over a 6-month period.

Physicians acted quickly, responding to 82.5% of alerts within 15 minutes, and indicated they would take action in 71.5% of cases, suggesting the system is effective in facilitating timely medical responses.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Detecting alerts, notifying the physician, and offering action items: a comprehensive alerting system. Kuperman, GJ., Teich, JM., Bates, DW., et al.[2018]

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Automated Alerts for Heart Valve Issues (ALERT Trial)

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