HealthPulse AI: Enhancing Diagnostic Trust and Accessibility in Under-Resourced Settings through AI [version 1]
Read the publication
Background
HealthPulse AI enhances diagnostic trust and accessibility by leveraging Artificial Intelligence (AI) for rapid diagnostic test (RDT) guidance, automated interpretation, and real-time data digitization. It addresses challenges including misadministration, misinterpretation, and data reliability, providing quality assurance (QA) for minimally trained users. Designed for low-end devices and offline functionality, HealthPulse AI ensures equitable access to accurate diagnostics in remote and resource-constrained areas.
Results
HealthPulse AI improved HIV self-testing practices (Kenya; South Africa), enabling virtual care models with enhanced access to PrEP and PEP. In Rwanda and Kenya, it significantly increased the ability of CHWs to identify faint positive lines, improving faint-line detection from 13% to 85.2% and knowledge of RDT interpretation timeframes from 79.9% to 97%. Workflows in pharmacies (Nigeria; Uganda; Kenya) using AI automation reduced approval claim time from 5.9 days to less than a day and increased claims processing by 170%, with 60% fully managed through automation, maintaining high diagnostic accuracy and supporting targeted training.
Conclusions
HealthPulse AI addresses diagnostic disparities, strengthens disease surveillance, and promotes equitable healthcare delivery. By automating QA, improving CHW training, and providing actionable real-time data, the platform enables sustainable health system improvements in low- and middle-income countries. With demonstrated scalability and impact, HealthPulse AI exemplifies the transformative potential of AI-driven solutions in addressing critical public health challenges, enhancing diagnostic reliability, and extending access to care for underserved populations.
