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Preventing maternal and infant mortality with AI

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Algorithms leveraging Artificial Intelligence can analyse data from millions of pregnancies spanning the entire pregnancy cycle: antenatal, neonatal and postnatal stages. Venkata Narasimham Peri, founder and CEO, CognitiveCare makes the point that while early detection and prevention can make the pregnancies safer and healthier, their economic impact on the payers (governments, individuals or health plans) will save billions in preventable costs

“Giving birth should be your greatest achievement, not your greatest fear.” —Jane Weideman

Those of us who have had the honour and joy of becoming parents know the feeling. However, advancements in science and medicine, notwithstanding, healthy childbirth still eludes millions of women globally. Complicated pregnancies impact the long-term health of both the mothers and their babies. Despite the rapid strides in reducing maternal and infant mortality rates (MMR) over the years, India, still contributes to 12 per cent of the world’s maternal deaths. Disproportionately higher maternal death rates are from rural India where more than 70 per cent of the pregnant women live with limited access to doctors, equipment, monitoring facilities and even basic maternal health education. More than two-thirds of maternal and infant health complications can be prevented with early detection and intervention.

Statistics of prenatal care in India reveal a very strange conundrum. While 24.4 per cent of rural (21 per cent of urban) women did not seek prenatal care due to its cost; 42.6 per cent of rural (56.2 per cent of urban) women could not get the care as the men/family didn’t think it was necessary or didn’t allow it. These trends indicate the importance of empowering women with not only education but also with simple, easy-to-use technological means to monitor their maternal health. Let us consider a simple app where a woman can upload her blood report and assess the risks in her pregnancy, the nearest doctor that she can meet, including scheduling an appointment and finally, a set of chatbots that can guide her throughout her pregnancy – all in her mother tongue.

Re-imagining maternal health

Such an initiative should begin with re-imagining maternal health.

The focus must be on early detection and prevention. Most of us may be content if we can detect maternal and infant health risks during the early stages of pregnancy. But can such risks be detected before the woman becomes pregnant?  Or when a girl attains puberty? Absolutely, but how?

Algorithms leveraging Artificial Intelligence can analyse data from millions of pregnancies spanning the entire pregnancy cycle: antenatal, neonatal and postnatal stages. They can offer us deep insights on the early signs of risks and how they evolved and manifested in the mother, foetus and the infant. For a 360-degree analysis of the mother, every relevant determinant of risks – namely, medical; clinical; radiological; genetic; social; lifestyle – should be analysed. For example, two women from the same genetic pool of the same age with the same parity may develop different risks because of their different occupations or the place where they live or the medical/clinical attributes of their partners.

Mothers can understand the progress they’re making to overcome the risks. Even when a certain set of risks is unavoidable medically, having the early knowledge of such risks and outcomes will ensure that high-risk mothers receive the desired level of medical attention, specialists and facilities. The precise, granular insights can empower other stakeholders to act. While a doctor can identify the optimal intervention (medical, clinical, lifestyle or otherwise) to reduce or manage the risk, the government can identify specific segments of the population vulnerable to certain risks and outcomes and can define the right intervention policies.

Managing economic and medical imperatives

The long-term costs of managing the health needs of babies and mothers experiencing complicated pregnancies can be significant. By avoiding preventable medical outcomes, billions of dollars can be saved. For example, globally, more than half of C-sections can be avoided and preventing even two-third of those C-sections can save more than $10 billion in healthcare costs. Preventing preterm birth can save babies from developing diabetes and obesity, and preventing haemorrhages can improve mothers’ health exponentially. While early detection and prevention can make the pregnancies safer and healthier, their economic impact on the payers (governments, individuals or health plans) will save billions in preventable costs.

Outlining the government’s role

Only governments can drive an endeavour of this scale. Governments should play the dual role of establishing the policy directives addressing all the possible data security and privacy concerns and creating the right incentive structures for key stakeholders to drive early detection and prevention. In India, where the government pays a large share of pregnancy costs, preventing every avoidable health cost is a critical economic imperative.

The advancements in medicine, AI and quantum biology are enhancing our understanding of cellular and molecular behaviours at a scale that was unfathomable a few years back. We today are at the cusp of discovering how the womb can reveal so much about our future health – prompting scientists to explore the hypothesis that every disease starts in the womb. While we may take a few years to reach the stage where we can discover diseases in the womb itself, we are fully equipped today to detect every maternal, foetal and infant health risk early. Doing so is not only a testament to our collective scientific temper but is also a sacred and moral obligation to every girl, woman and mother. That will be a fitting tribute to womankind.

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