Cloud-based ECG reporting in a rural setting: pilot results and projected cost savings at scale

Background Limited access to timely electrocardiogram (ECG) services in rural middle-income settings delays clinical decisions and increases costs. In this region, ECGs are often provided via monthly mobile services, with reports taking weeks. We assessed costs of a cloud-based ECG reporting hub and projected 12-month time and cost savings. Purpose To evaluate feasibility of a cloud-based ECG interpretation network to shorten turnaround time (TAT), reduce per-ECG cost, and generate scalable savings in rural setting versus current infrastructure. Methods We implemented a cloud-based ECG interpretation workflow at a tertiary cardiology clinic supported by board-certified clinicians. Over a 15-week pilot, TAT and per-ECG costs were measured and compared with the rural mobile standard and vendor reporting times. A 12-month projection model was applied to 1,000,000 rural patients, assuming 30% (300,000) require ECG annually. Outcomes included annual costs and patient-days saved (mean TAT difference × annual ECG volume). Results During the pilot, 530 ECGs were reported (mean 36/week). Mean TAT was 1.48 ± 2.23 days for the cloud program versus 30.5 ± 30.2 days for the mobile service standard (p=0.037), and 4.1 ±3.13 days for industry-advertised reporting (p=0.043). This represents a 95.2% reduction versus mobile services (20.7-fold faster, p<0.001) and a 64.0% reduction versus industry benchmarks (p<0.001). The mean TAT difference versus mobile services was 29.02 days per ECG, corresponding to an estimated 52,325.44 patient-days saved annually based on pilot throughput; the number needed to treat (NNT)=1, indicating each ECG routed through the hub yields time saved relative to the standard pathway. Per-ECG cost was $14.46 USD (cloud) versus $22.49 USD (standard), a savings of $8.03 USD per ECG (35.7%). In the 12-month projection (300,000 ECGs/year), total annual cost was $4.338M USD under the cloud model versus $6.747M USD under the standard model, yielding an estimated annual cost savings of $2.409M USD. Based on the observed TAT difference, the model projects 8.679M patient-days saved over 12 months (29.02 days saved per ECG × 300,000 ECGs). Conclusion A cloud-based ECG reporting hub can generate substantial system benefits in rural island settings, with projected annual savings of ~$2.41M USD and ~8.68M patient-days saved when scaled to 1 million rural patients with 30% annual ECG demand. Beyond reducing delays in clinical decision making, this model liberates scarce health system capital by lowering costs and reducing inefficiencies tied to delayed reporting. Reallocating freed funds could directly strengthen other priority areas improving overall system resilience and equity. These findings support technology enabled ECG networks as a scalable, cost-saving approach to expand timely cardiovascular care and may be transferable to other low-resource regions to expand access, shorten diagnostic delays, and reduce costs.