European heart journal. Digital health · 2026
Decentralized community-based hub-intermediary-spoke model for rapid cardiac ultrasound triage for early heart failure detection: findings from the Heart2Miss initiative.
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Foo Diana Hui Ping, Yeo John Jui Ping, Yeo Yenny Yen Yen, Bumphray Stephanie Tayas, Jong Rose Hui Chin, Sumbu Liana Lantong, Jana Claudia Lennya, Michael Jennett, Ishak Maziah, Jerampang Peter, Mustapha Maila, Ahip Sally Suriani, Hamden Lenny, Igo Macnicholson, Sulaiman Mohammad Nor Azlan, Chunggat Jawing, Chong Francesca Gelang, Enggong Deborah Berenai, Chung Yeequant, Ishak Daniel, Anthony Jalin Angela Melinda, Kalra Sonesh, Fong Alan Yean Yip
Аннотация
AIMS: To evaluate the feasibility and system-level performance of Heart2Miss, a decentralized community-based triage model deploying AI-powered point-of-care ultrasound (AI-POCUS) via a hub-intermediary-spoke approach in diabetes primary care for early heart-failure (HF) detection.
METHODS AND RESULTS: In this prospective study, 1000 adults with diabetes and no known HF were screened over seven months across six primary care clinics (spokes); 985 with complete data were analysed. Novice biomedical and bioscience graduates underwent 4-week training to perform focused three-view handheld AI-POCUS. Images were AI-analysed and verified through the hub-intermediary-spoke pathway. The primary outcome was detection of previously undiagnosed HF. Secondary outcomes included reduction in tertiary-centre burden through the hub-intermediary-spoke pathway and novice sonographer performance. 11.1% (n = 109) had Stage B (pre-HF) and 1.0% (n = 10) Stage C HF (symptomatic HF). Rapid triage ruled out abnormality in 77.3% at the spoke and a further 12.6% after intermediary TTE confirmation, reducing tertiary diagnostic burden by 89.9%. Only 1.0% required tertiary referral. Regarding novice performance, >90% analysable scans were achieved for left-ventricular parameters and >85% for left-atrial volume. After 400 scans, scan time fell from 11.0 ± 5.3 min to 8.3 ± 4.4 min (Δ 2.31 min, 95% CI 1.52-3.11; P < 0.001), and complete three-view capture improved from 88.0% to 92.2% (P = 0.035).
CONCLUSION: This decentralized hub-intermediary-spoke model combining AI-POCUS, telehealth verification, and a task-shifted bioscience workforce enabled early HF detection while substantially reducing specialist workload, supporting digital health-enabled workforce innovation and pathway redesign in resource-constrained settings.
METHODS AND RESULTS: In this prospective study, 1000 adults with diabetes and no known HF were screened over seven months across six primary care clinics (spokes); 985 with complete data were analysed. Novice biomedical and bioscience graduates underwent 4-week training to perform focused three-view handheld AI-POCUS. Images were AI-analysed and verified through the hub-intermediary-spoke pathway. The primary outcome was detection of previously undiagnosed HF. Secondary outcomes included reduction in tertiary-centre burden through the hub-intermediary-spoke pathway and novice sonographer performance. 11.1% (n = 109) had Stage B (pre-HF) and 1.0% (n = 10) Stage C HF (symptomatic HF). Rapid triage ruled out abnormality in 77.3% at the spoke and a further 12.6% after intermediary TTE confirmation, reducing tertiary diagnostic burden by 89.9%. Only 1.0% required tertiary referral. Regarding novice performance, >90% analysable scans were achieved for left-ventricular parameters and >85% for left-atrial volume. After 400 scans, scan time fell from 11.0 ± 5.3 min to 8.3 ± 4.4 min (Δ 2.31 min, 95% CI 1.52-3.11; P < 0.001), and complete three-view capture improved from 88.0% to 92.2% (P = 0.035).
CONCLUSION: This decentralized hub-intermediary-spoke model combining AI-POCUS, telehealth verification, and a task-shifted bioscience workforce enabled early HF detection while substantially reducing specialist workload, supporting digital health-enabled workforce innovation and pathway redesign in resource-constrained settings.