Clinical Context

Severe aortic stenosis (AS) and significant mitral regurgitation (MR) remain undertreated despite the availability of effective surgical and transcatheter valve therapies. Gaps in evaluation and treatment may reflect fragmented referral pathways, delayed recognition, and disparities across sex, race and ethnicity, socioeconomic status, and geography.

The ALERT trial evaluated whether automated EHR-based clinician alerts could improve guideline-directed evaluation and treatment for patients with significant AS or MR.

Study Design

ALERT was a multisystem, cluster-randomized clinical trial conducted across 5 U.S. health systems and 35 hospitals between August 2024 and September 2025.

The modified intention-to-treat population included 765 clinicians ordering 2,016 echocardiograms in 1,905 patients. Clinicians were randomized to receive an electronic clinician notification (ECN) alert identifying significant AS or MR with care recommendations, or to usual care without an alert.

The primary endpoint was a hierarchical composite of time to surgical or transcatheter valve intervention, followed by time to multidisciplinary heart team (MHT) clinic evaluation within 90 days, analyzed using a stratified win-ratio method.

Key Findings

ECN alerts were superior to usual care for the primary hierarchical composite endpoint, with a stratified win ratio of 1.27 (95% confidence interval [CI]: 1.05–1.54; P = 0.007). The corresponding net benefit was 4.21% (95% CI: 0.63%–7.77%).

Rates of valve intervention and MHT evaluation were higher with ECN alerts:

• Valve intervention: 13.4% vs 9.6%
• MHT evaluation: 22.7% vs 17.9%
• Composite care delivery endpoint at 90 days: 24.3% vs 19.9%.

Time to first MHT visit or valve intervention was 2.5 days shorter in the ECN arm. Cumulative incidence analysis also showed a higher probability of receiving care within 90 days with alerts compared with usual care (24% vs 20%; P = 0.027).

The effect was consistent in sensitivity analyses. ECN alerts remained superior in the intention-to-treat population (win ratio: 1.24; 95% CI: 1.02–1.49; P = 0.014) and per-protocol population (win ratio: 1.50; 95% CI: 1.22–1.85; P < 0.001).

Clinical Perspective

The ALERT trial showed that automated ECN alerts improved timely evaluation and treatment for significant AS and MR across diverse care settings. The benefit appeared strongest for valve intervention in AS and for earlier MHT evaluation in MR.

These findings suggest that EHR-integrated clinical decision support may help reduce undertreatment of valvular heart disease and improve access to specialized valve care when paired with effective clinical pathways.

Key Takeaway

Automated EHR-based clinician alerts improved timely guideline-directed evaluation and valve intervention for significant AS and MR, supporting clinical decision support as a scalable strategy for valvular heart disease care.

Author

Manjusha Shetty is Senior Editor at MedApt, a physician-focused platform covering clinical updates, congress insights, and expert perspectives.