UMA: Every Pregnant Woman’s Friend

In semi-developed and rural areas where infrastructure, lack of information, and restrictive notion of culture adversely impact pregnancy journeys and delivery outcomes, UMA is a pregnancy service that aims to empower pregnant persons and their ancillary support system.

For the pregnant woman and her support system, the service leverages household resources and practices to inculcate medical adherence, proactive decision-making, and building help-seeking behaviours. For medical personnel, UMA lessens the burden of care and smoothens doctor-patient interactions for increased productivity. How is this done? Through videos, a sticker-sheet, and an app!

The pregnant woman and her family watch the explanatory videos during their visits at the health care centre to know how they can use UMA for their benefit. They are given a trimmest-specific sticker sheet (with daily stickers for tracking nutrition, danger signs etc. and scannable stickers that lead to informative videos). They track their pregnancy on their own culturally-relevant calendars at home. They carry along their sticker-marked calendars to their next appointment, where the doctors scans it with the UMA app to derive insights on their overall health (through Optical Character Recognition with Machine Learning).

UMA eases the pregnancy experience by engaging different levels of stakeholders after considering their socio-demographic context, through multiple touchpoints that are accessible to them.

In a 2021 study of Indian maternal mortality trends, the country’s maternal mortality rate is 99/1,00,000 live births – an objective outlined in the 2015 millennium development goal (1). Further, an estimated 1.3 million women have died from maternal causes in the last twenty years, mostly in rural areas (1). While healthcare innovation and reach of technology have reduced maternal deaths, many women cannot access existing healthcare facilities or face a dearth of resources.

In an attempt to capture India’s socio-geographical diversity, we conducted participatory research with women (aged 20-55 years) and their partners from at least 8 states, hailing from rural and peri-urban settings and belonging to the low-income category. Additionally, we spoke to medical and healthcare professionals to understand and map the existing ecosystems of care around a pregnant woman. A critical activity we conducted at this point was unpacking mental models, which unearthed similar inconsistencies in adhering to the doctor’s nutrition and lifestyle recommendations, lack of awareness of pregnancy warning signs, delay in decision-making and help-seeking. We mapped these behavioral patterns back to the socio-demographic culture and their positive/negative reinforcing feedback loops. We then did a causal layered analysis of social, medical, and cultural paradigms around pregnancy and women. These tools highlighted the system interconnectedness and helped us identify the main factors of adverse pregnancy outcomes.

We found a need for effective information dissemination and healthcare tracking methods that fit seamlessly into the lives of pregnant women from the rural poor, and develops their participatory interest in the pregnancy. The three-delay model that identifies the fatal gaps in utilizing healthcare services points to the delay in deciding to seek care (delay 1) as the largest contributor to adverse outcomes. This delay can be traced to a lack of information of pregnancy complications and risk factors, poverty and lack of education (2), thus supporting our conclusion.

We co-created a service with medical personnel that is embedded into existing traditions, with multiple organic touch-points and which leverages mobile penetration in rural areas. Pregnant women receive a sticker sheet at their doctor’s appointment that has stickers representing supplements, warning signs corresponding to their trimester, antenatal care appointments etc.

The women stick them to their calendars for the days that they take their supplements or experience those symptoms. At their next appointment, the doctors scan these stickers to gain insights into the patient’s pregnancy pains and medical adherence, leveraging Optical Character Recognition and machine learning. There are also two scannable stickers: one denote the next appointment and opens to a video on what the patient can expect at their next appointment, and the second connects to a playlist of concise and accurate informational animated videos on pregnancy best practices. Pregnant women and their partners can use it to empower themselves with accessible relevant information and become more involved. In the design and development of our intervention, we strived to be inclusive, conscious in our use of technology, and keep stakeholders at the centre of our design.