{"id":"AIBD-0926","title":"Avalia-t finds that the Willem, Cardiologs and ILR-ECG-A algorithms removed 60.3% to 98% of false alerts from insertable heart monitors","summary":"Avalia-t found that AI algorithms re-reading insertable heart monitor recordings removed 60.3% to 98% of false-positive alerts in three studies. It rated the evidence as low in quality.","date_observed":"2025-01-01","date_basis":"source publication","date_precision":"year","benefit_status":"mixed","source_collection":null,"source_entry":null,"account":"Insertable cardiac monitors record the heart's rhythm for years and flag possible arrhythmias. Many of the alerts are false, and clinicians must review each one. Avalia-t, the scientific advice unit of Galicia's health knowledge agency, assessed AI algorithms that re-read these recordings for Spain's network of assessment agencies in 2025. It searched the literature up to 31 March 2024 and found four diagnostic studies with 445 patients. In three studies, the algorithms removed between 60.3% and 98% of the monitors' false positives. Alerts that the Cardiologs algorithm confirmed were true 74.5% of the time, against 53.9% for the Medtronic monitor alone. IDOVEN's algorithm removed 1,065 of 1,087 false positives from Abbott's Confirm Rx. The algorithms missed between 1% and 2.9% of true events, mostly atrial fibrillation or atrial tachycardia. Avalia-t rated the studies at high risk of bias, and employees or advisers of the makers co-wrote each of them. It found no data on clinicians' time saved and could draw no conclusion on clinical impact.","category":"aggregate result","unexpected":false,"purpose":"Idoven, Cardiologs and Implicity built Willem, the Cardiologs algorithm and ILR-ECG-A to re-read insertable cardiac monitor recordings and screen out false arrhythmia alerts.","system":"Willem (IDOVEN), Cardiologs and ILR-ECG-A (Implicity), AI algorithms that re-read insertable cardiac monitor recordings","model_version":null,"developer":"Idoven (Willem), Cardiologs and Implicity (ILR-ECG-A)","deployer":"Remote monitoring centers in the studies that Avalia-t reviewed: Valley Hospital in the United States (Cardiologs), one center in Italy (IDOVEN) and 31 US and French centers on the Implicity platform","location":"Spain (assessment), with studies in the United States, Italy and France","domain":"Healthcare (cardiology)","segment":null,"benefit_type":"Improved Task Accuracy","work_activities":["4.A.1.b.1","4.A.1.a.2"],"taxonomy_note":null,"registry_ids":{},"ratings":[{"group":"organizational","depth":null,"reason":"The algorithms re-read stored recordings in diagnostic studies, and Avalia-t found no data on the review time that clinicians saved."}],"ai_role":{"status":"assessed","statement":"Experts adjudicated the same events that the monitors flagged and the algorithms re-read, so the false alerts removed are the algorithms' own share. Avalia-t included only algorithms that use AI, and its evidence tables describe deep or convolutional neural networks for all three. No study measured the effect on clinicians' work."},"evidence":[{"kind":"assessment report","citation":"Unidad de Asesoramiento Científico-técnico, Avalia-t, Agencia Gallega para la Gestión del Conocimiento en Salud (ACIS), for the Red Española de Agencias de Evaluación de Tecnologías Sanitarias y Prestaciones del SNS. López Loureiro I, Puñal-Rioboo J, Mejuto Martí T. Evaluación del rendimiento diagnóstico y la seguridad de la inteligencia artificial en la monitorización cardíaca con dispositivos insertables. Informes de Evaluación de Tecnologías Sanitarias. Madrid: Ministerio de Sanidad, 2025. NIPO 133-25-043-1. Resumen, Conclusiones.","title":"Evaluación del rendimiento diagnóstico y la seguridad de la inteligencia artificial en la monitorización cardíaca con dispositivos insertables","url":"https://redets.sanidad.gob.es/productos/buscarProductos.do?metodo=descargarFichero&idProducto=1284","date":null,"written_by":"independent","quote":"Los algoritmos de IA muestran un VPP entre el 74,5% y el 89,74%. Así mismo, producen una reducción de FP entre el 60,3% y el 98%."},{"kind":"assessment report","citation":"Avalia-t (ACIS). Assessment of artificial intelligence's diagnostic yield and security in cardiac monitoring using insertable cardiac monitors. English summary, Conclusions. Madrid: Ministerio de Sanidad, 2025.","title":"Evaluación del rendimiento diagnóstico y la seguridad de la inteligencia artificial en la monitorización cardíaca con dispositivos insertables (English summary)","url":"https://redets.sanidad.gob.es/productos/buscarProductos.do?metodo=descargarFichero&idProducto=1284","date":null,"written_by":"independent","quote":"AI algorithms demonstrated PPV values between 74,5% and 89,74%, reducing FP rates by 60,3% to 98%."}],"replication":{"produced_by":["The algorithms re-read the ECG episodes that insertable monitors had stored as possible arrhythmias.","Electrophysiology experts classified each episode as the reference standard."],"must_hold":["The monitor sends its recordings to a remote platform where the algorithm can analyze them.","Each algorithm is checked on the monitors that it reads, since performance varied with the device and its software."],"echoes":[]},"paired_incident":null,"headline":"*Willem*, *Cardiologs* and *ILR-ECG-A* cut false heart-monitor alerts","metric":"removed between 60.3% and 98% of the monitors' false positives","comparator":{"against":"Alerts from the Medtronic Reveal LINQ monitor without the AI filter (Mittal et al. study)","before":"53,9% (IC 95%: 51.4%-56.5%) positive predictive value","after":"74,5% (IC 95%: 71,8%-77%) with the Cardiologs algorithm","basis":"measured","quote":"Los autores indican que el valor VPP de la IA, 74,5% (IC 95%: 71,8%-77%), es significativamente superior (p<0.001) al VPP del dispositivo subcutáneo, 53,9% (IC 95%: 51.4%-56.5%).","url":"https://redets.sanidad.gob.es/productos/buscarProductos.do?metodo=descargarFichero&idProducto=1284"},"later":null,"value":null,"developer_country":"Multiple: Spain, France","deployer_country":"Multiple: United States, Italy, France","unrated_because":"The false positives were removed in studies that re-read stored recordings, and Avalia-t found no evidence on time saved or clinical impact.","brief_notes":null,"brief":null,"revisions":[{"date":"2026-10-31","change":"Added the record from the finding of Avalia-t.","source":"https://redets.sanidad.gob.es/productos/buscarProductos.do?metodo=descargarFichero&idProducto=1284","editor":"AIBD"}],"confidence":"found","shade":"high","claim_status":"Found by an assessment body","claim_basis":"Sources: one independent assessment report. 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