AI-Enabled regional tele-ECG cloud platform and improving access to cardiovascular diagnosis: real-world evidence from southern China - Report - MDSpire
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AI-Enabled regional tele-ECG cloud platform and improving access to cardiovascular diagnosis: real-world evidence from southern China
The implementation of an AI-enabled tele-ECG platform significantly reduced clinical decision-making times and improved diagnostic accuracy in primary healthcare settings.
Background
Cardiovascular diseases are the leading cause of death globally, with significant disparities in outcomes between urban and rural healthcare settings. Access to timely diagnosis and treatment is crucial for improving morbidity and mortality rates, particularly in low- and middle-income countries. Digital health solutions, such as AI-enabled tele-ECG platforms, may enhance diagnostic capabilities in primary healthcare institutions.
Data Highlights
Metric
Before Implementation
After Implementation
Clinical Decision-Making Time (min)
10
3
Report Turnaround Time (min)
N/A
3.79 ± 1.81
Diagnostic Accuracy (%)
82.30
98.11
Survival-to-Discharge Rate (%)
N/A
75.00
Average Patient Saving (CNY)
N/A
26
Annual Net Social Benefit (CNY)
N/A
154,182.50
Key Findings
The AI-enabled tele-ECG platform reduced clinical decision-making time from 10 minutes to 3 minutes.
Report turnaround time was recorded at 3.79 ± 1.81 minutes.
Diagnostic accuracy at the primary healthcare level increased from 82.30% to 98.11%.
The survival-to-discharge rate among acute myocardial infarction cases at primary healthcare institutions was 75.00%.
The budget impact analysis indicated an average patient saving of 26 CNY per encounter.
The annual net social benefit for the regional network was calculated at 154,182.50 CNY.
Clinical Implications
The findings suggest that integrating AI into tele-ECG services can significantly enhance diagnostic accuracy and reduce critical decision-making times in primary healthcare settings. This model may serve as a scalable solution to improve cardiovascular care access in underserved regions.
Conclusion
The AI-enabled tele-ECG platform demonstrates a promising approach to enhancing cardiovascular diagnostic access in resource-constrained areas, potentially reducing disparities in care outcomes.
