Madhav Joshi, CEO, India Health Fund talks about the role of technology in managing Tuberculosis (TB)
TB is a serious threat to public health and over the last decade, there has been a significant increase in mortality rates in TB burden regions. India alone has an outsized proportion of TB with 2.6 million people affected in 2020-a quarter of the world’s TB cases. Despite the advances in treatment for TB, high-burden regions like India still face the challenge of inadequate screening tools, which result in diagnostic delay and misdiagnosis and thus poor health outcomes.
While the traditional screening for TB using a lung X-ray, is the most sensitive and cost-efficient way, it is also a workforce-heavy and time-consuming process. As India continues to face an acute shortage of trained radiologists, TB diagnosis can often take weeks leading to missed cases, increased disease spread, delayed treatment, and higher mortality.
In the last decade or so, digital advances like Artificial Intelligence (AI), machine learning, internet of things, deep tech have shown their promise in automated detection of various infectious diseases, including TB where AI-powered deep learning neural networks are increasingly being used to analyse medical images, such as chest radiographs or x-rays. AI algorithms have proven to be highly accurate and useful triage tools for TB detection especially in remote low-resource settings where skilled radiologists are in shortage. One such technology was qXR, developed by Qure.ai, with funding and support from India Health Fund, a Tata Trusts initiative. qXR is a fast and automated chest X-ray screening software for TB that is powered by AI. It scans and reads X-rays and identifies and highlights lung abnormalities, enabling TB detection within minutes. The IHF supported qXR project is already operational across 27 sites in 5 states – UP, Maharashtra, Karnataka, Nagaland, and Rajasthan, with over 40,000 X-rays screened so far. Using qXR, up to 33 per cent of additional TB cases are detected, with a reduction in delay in diagnosis from 50 days to less than 7 days, so that treatment can start promptly. qXR is also more affordable and reduces overall costs by 55 per cent and can be used with ease at primary health centers, without the need for expert radiologists.
AI-based technologies also offer the advantage of multiplexity and rapid adaptability. For instance, following the outbreak of COVID-19, qXR was also quickly adapted to identify and triage cases of COVID-19 along with TB. India Health Fund facilitated the fundraising and deployment of qXR solution for COVID-19 with the Brihanmumbai Municipal Corporation (BMC) bolstering its COVID-19 response efforts across 15 sites in Mumbai. These efforts resulted in reduction in turnaround time by detecting radiological signs of COVID-19 in under a minute; 20 per cent were instantly reported by qXR as having COVID-19 indications – these included asymptomatic cases; COVID-19 screening and triaging using qXR helped optimal utilisation of the limited RT-PCR kits. Such AI-based tools that improve speed, efficiency, reach and costs are truly futuristic, with the power to change the lives of the underserved as well as to save resources for the health systems.
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