Can decentralized community rapid cardiac ultrasound triage reduce carbon footprint? Environmental insights from the Heart2Miss study

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides empirical evidence on carbon savings from AI-assisted decentralized triage, useful for healthcare decarbonization research.

🏢実務担当者:Demonstrates that adopting AI POCUS can reduce patient travel emissions and operational costs, supporting ESG reporting.

🏛政策担当者:Highlights the potential of telemedicine and AI to lower healthcare's environmental impact, informing policy on sustainable health systems.

Abstract Background Early heart failure (HF) detection in high-risk diabetes patients is crucial for better outcomes, but transthoracic echocardiography (TTE) access is limited to specialized tertiary center, increasing diagnostic burden. To address this, the Heart2Miss study leveraged AI-powered POCUS and telehealth for decentralized rapid TTE triage in primary care, enhancing accessibility. Purpose To compare environmental carbon footprint of decentralized community rapid TTE triage with a modeled conventional specialized tertiary TTE diagnostic pathway (real-world local single tertiary cardiology center serving 700,000 population). Methods In this decentralized diagnostic pathway, trained novices performed focused 3-view triage TTE at primary care using handheld POCUS device with AI-powered automated analysis. Experienced sonographers remotely verified these automated analyses at an intermediary center. Patients with initial abnormal triage TTE received confirmatory TTE at the intermediary center, and if HF was confirmed, were referred to tertiary cardiology for further management. The environmental substudy interviewed 985 patients undergoing triage TTE at primary care. Data collected on patient and carer travel distances (primary, intermediary, tertiary centers) and transport modes. Carbon emissions and travel distance savings for both pathways were estimated using adapted Excel template from public available resources. Results Data from 716 interviewed patients (55.3% women; mean age 62±11 years) revealed 63.7% attended alone, 36.3% with a carer. Median distance from home to primary care was 5.70km, compared to 16.0km to tertiary cardiology center. Most patients (80.3%) travelled by own car to primary care, others by bus (3.4%), motorbike (12.6%), taxi (2.8%), or on foot (1.0%). The Heart2Miss decentralized pathway resulted in median return journey of 14.0km (median 2.89kgCO2e carbon emissions), compared with 32.0km (median 5.37kgCO2e) in modeled conventional pathway. This saved a median of 17.0km travelled distance and 2.11kgCO2e in carbon emissions. Notably, 77.4% of patients had normal TTE triage results at primary care and required no further confirmatory TTE. For these patients, decentralized pathway significantly lowered travel distance (median 11.41km vs modeled 33.0km for conventional pathway; p<0.001) and carbon emissions (median 2.35kgCO2e vs 5.41kgCO2e; p<0.001). For the 22.6% patients requiring a second confirmatory TTE at intermediary center, total travel distance and carbon emissions did not differ significantly from modeled conventional pathway. Conclusion(s) Decentralized TTE triage significantly reduced travel distance and carbon emissions for most patients triaged at primary care, suggesting a sustainable HF detection approach in high-risk diabetes patients. It has implications for resource-limited settings and aligns AI-powered digital health with UN Sustainable Development Goals for health and climate action.

• openalex https://doi.org/10.1093/ejhf/xuag193.1412first seen 2026-06-30 05:16:02