Lack of spirometry at primary care level, which is the most essential and fundamental diagnostic modality to determine lung function and understand the presence and severity of various respiratory conditions. Currently, spirometry is available only at tertiary levels because it requires special infrastructure, trained workforce and working requirements with continuous presence of specialists at site. Our AI enabled spirometer with digital eco-system truly decentralizes spirometry. It enables spirometry at all levels, thereby enabling early detection of respiratory conditions and avoiding morbidity, including in community settings with remote monitoring of patients and longitudinal follow-up.
We aim to screen children aged 7-15 under an existing school health program (RBSK) in India's NHM. Integrating our solution with this large-scale program allows us to gather real-world evidence on its scalability. This intervention facilitates early detection and secondary prevention of respiratory conditions, ensuring effective management and preventing worsening health due to delayed diagnosis. Though it will incur incremental costs, it is likely to impact millions of children by addressing a crucial health condition by ensuring availability of essential diagnostic tools like spirometry and setting the ground for establishing necessary screening protocols.
Under RBSK dedicated school health team visit schools in a given geographical area at regular intervals under a defined roaster. We have already initiated the dialogue with various State Govts who have provided in-principle approvals for pilot projects. Operationally school health teams would require either one additional member per team or the support of school level functionaries to carry out spirometry of high risk (symptomatic and asymptomatic) school children as decided by the risk assessment through questionnaire and
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