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Diagnosing India’s healthcare problem

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Kalyan Sivasailam, CEO, 5C Network sheds light on the issues faced due to incorrect diagnosis and ways to overcome them

A Harvard study estimated the number of medical errors in India to be over 5.2 million every year. A deeper analysis of why these errors happen leads to one of the most fundamental steps in the process – incorrect diagnosis.

Is there a cure for slow and incorrect diagnosis?

The Internet is full of horror stories of people being diagnosed incorrectly even after months of tests and numerous visits to various specialists. Even if you haven’t been subjected to such misery, you are probably one of 8 in 10 people who had to make repeat trips to a centre just to collect your reports.
A dear friend and colleague of mine recently fell ill and was admitted into a Bengaluru hospital. The doctors came up with an instant solution – “get a scan, things will become clear”. But, there was a bigger problem here – while the scan itself took all of 15 minutes, we had to wait for 48 agonising hours for the interpretation. To solve the problem, we first needed to know what the problem was.

Machines machines everywhere, but not a radiologist to think

Radiology is the last word in diagnosing countless ailments – from a fracture on a little toe to a malignant mass in the lung. Over 200 million radiology examinations are performed every year. This number is growing 16 per cent year-on-year due to increased demand from physicians, who do not want to prescribe treatment without a confirmed diagnosis through radiology. Medical equipment giants such as GE, Siemens, and Philips along with new entrants such as SkanRay have realised that India’s “Tier-2 and Tier-3” cities are where the need is, and are investing heavily in innovation to cater to this market.

This looks like a rosy picture until you realise that radiologists – the doctors who can actually read the complex images generated by these machines, number a paltry 10,000 in the whole country. What’s more, they are heavily concentrated in urban areas. In an urban diagnostic centre, radiologists are overburdened with work and this leads to lower quality diagnosis and delays. In a non-urban diagnostic centre, radiologists are mostly not available.

Is technology a friend indeed?

Technology has played an immense role in radiology, which has allowed it to grow exponentially as it has across the world. Manufacturers are investing heavily in capturing images faster using lower doses of radiation. The DICOM standard has ensured interoperability amongst all machines and software. And of course, with the introduction of AI in radiology, we can expect the productivity of radiologists and machines to greatly improve. Predible Health, a healthtech-AI company based in Bengaluru, has done some amazing work in lung cancer screening. Their solution allows caregivers to identify potentially malignant nodules in CT scans, and also track their progress during therapy. This is a great example of the potential use of AI – reducing busy work while also adding value through inferences derived from historical data.

Revolutionising diagnostic delivery

It is no big secret, revolutionising India’s diagnostic delivery will play a vital role in disrupting the existing healthcare system, thereby making accessible and affordable medical facilities a reality for India’s masses. While products are undergoing a revolution through AI, their delivery and accessibility still remain a concern. 5C is one such startup that is addressing this significantly large healthcare delivery problem. It is India’s first diagnostics network to make radiodiagnosis more accessible, affordable and accurate through technology. 5C’s business model is validated by the 1,000+ cases handled per day. Recently, to expand the accessibility to many more people 5C was funded by Unitus Ventures, Axilor, and IIM, Ahmedabad.

While 5C is working on the diagnosis space, there are also innovative companies that are targeting the pre-diagnosis or screening market. Both UE Lifesciences and Niramai are using thermography, augmented with deep learning, to screen women who are at high risk of developing breast cancer. AIndra is working on a similar play – using intelligence to reduce errors in reading PAP-smears which is the current standard in cervical cancer screening. Technology-driven screening and diagnostic platforms will create new markets and help achieve better healthcare outcomes, especially in underserved areas.

Accessible and affordable healthcare is poised to drive India to a healthier future.

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