The global healthcare industry is worth $8.2 trillion but sadly enough, only about 20% of the people have access to secondary and tertiary care. High population growth, mortality rates, vast expanse of landmass and low per capita income accentuates this challenge further for India. In particular, India’s burden of non-communicable diseases (NCD) is very high and an acute shortage of specialists isn’t making things any easier. And, a surfeit of data lies unstructured & fragmented.

Deep tech capability in this environment is like a breath of fresh air, but we must remain mindful that quality, accessibility, and affordability will have to go hand-in-hand. To be sure, NASSCOM has done a deep-dive of healthcare startups (550+) and estimated a 55% growth in value terms for this segment.

Essentially, technology can be leveraged to create impact on three fronts – build awareness about diseases (particularly in remote areas); as a preventive measure, pre-screening in sub-centres being a case in point; and, getting the IT industry to focus on the most important issues. The health-tech startups today aren’t addressing one monolithic structure, but really a sum of many parts. A broad classification here - aggregators (e.g. on-line pharmacy), personal health & fitness discovery (apps, wearables), health information management (EHR), tech-enabled diagnostics & anomaly detection, tele-medicine & medical devices.

There’s tremendous scope for trade bodies such as NASSCOM to play the role of a catalyst to create collaborative platforms and ensure great improvement in healthcare delivery in India. On cue, we came up with a four-point agenda – discover (finding out the best solutions available and mapping them to specific problems being addressed) design & demonstrate (integrate tech companies with the healthcare system to substantially improve outcomes), scale (ensure what is being demonstrated, is scaled) and engage – at a thought leadership level with stakeholders.

Artificial intelligence in healthcare has incredibly powerful applications. Machine Learning algorithms can process heaps of medical data and draw patterns (read early signals) which even experienced doctors are likely to miss. These applications include diagnosis process, treatment protocol development, drug development, personalised medicine, patient monitoring and care. When summed up, it leads to prevention of diseases, better treatment and greatly improved outcomes.

The big C in India is almost taking epidemic proportions with close to two million affected people. And, how many oncologists do we have? Only about 2,000. There are quite a few startups which are leveraging tech-enabled solutions to screen patients in a non-invasive manner which are also affordable. Portability of solutions/devices and ease of use are invaluable add-ons which help expand outreach significantly.

In the U.S., the ratio of radiologists to patients is 1: 1. Whereas in India it is 1: 1 lakh. Again, AI can interpret imaging results and detect the minutest of changes which may have been inadvertently missed by the technician, given the sheer workload. Worldwide there’s a $3 trillion loss due to faulty medical reporting and this is not something we can afford to take lightly any longer.

There are affordable devices that can be fitted like an armband which monitor the vital signs – respiratory rate, oxygen levels, pulse, blood pressure and body temperature. Wearable solutions providers help store all this data on cloud which can be accessed by doctors at any time through a hand-held device. These solutions can instantaneously detect anomalies and alert the doctor concerned. For remote locations, telemedicine is nothing short of a boon which can help save lives through timely intervention.

Arguably, the most important aspect which I have intentionally saved for the last, is about data privacy. At one level, we want to create a tech-enabled ecosystem which encourages information interchange; after all, the differentiation is really about data married to deep technology. Medical records are very sensitive information and we must never lose sight of the fact that the foundation of any doctor-patient relationship is built on trust. At no point in time can we allow the self-serving motive of bad actors to overrule altruistic sentiments. Because, if it does, patients will soon become reluctant to share data which will cause immeasurable harm to the ecosystem. These are early days yet and as we go along, we need to have in place more definitive protocols which will ensure healthcare ethics aren’t compromised.

The author is founder & chairman, Genpact & Clix Capital.

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