Early heart failure detection in high-risk diabetes patients typically requires echocardiography at specialist tertiary centres, adding diagnostic burden, long patient journeys, and an often-overlooked environmental cost.

The Heart2Miss study deployed AI-powered handheld POCUS with remote telehealth verification at primary care level, bringing cardiac triage closer to where patients already go. This environmental sub-study measured whether decentralising that triage pathway meaningfully reduces carbon emissions compared to a conventional tertiary referral model.

Across 716 patients interviewed, the decentralised approach saved a median 17.0 km of travel and 2.11 kg CO₂e per patient: a 53% reduction in distance and 39% reduction in carbon emissions. The benefit was most pronounced for the 77.4% of patients whose triage TTE was normal and required no further testing.

 

Key findings

  • 53% less distance travelled per patient (median 14.0 km vs. 32.0 km)
  • 39% fewer carbon emissions (median 2.89 vs. 5.37 kg CO₂e)
  • 77.4% of patients managed entirely at primary care level with no onward referral needed
  • Savings were statistically significant for normal-triage patients (p < 0.001); no significant difference for those requiring confirmatory TTE

Implications

This work suggests that AI-powered decentralised cardiac diagnostics can be both clinically effective and environmentally responsible, a model relevant to resource-limited settings globally, and aligned with UN Sustainable Development Goals SDG 3 (Good Health) and SDG 13 (Climate Action).

 

Heart2Miss Study Results

Learn more about the Heart2Miss Study and explore the presented findings. View results →