Enabling millions of urban low-income women with an AI-based pregnancy care solution
Pitch us on your solution
Every year, 2.6 million still births occur worldwide and most neonatal deaths occur due to prematurity. Both these conditions are linked to antenatal care. Yet, fetal heart rate (FHR) monitoring is absent in the majority of low-income pregnancies, because cardiotocography (the standard used in tertiary hospitals) has poor sensitivity; it is capital-intensive, not portable and requires expertise.
Our solution, ‘Fetosense’, is an AI-based, wireless, portable, smartphone integrated and affordable FHR monitor. We are developing capabilities to auto-interpret results, and monitor uterine contractions to predict premature labour. Frontline workers can use Fetosense via our existing ‘CareMother’ platform, where they conduct point-of-care antenatal tests and record data in a smartphone application to transfer results in real-time to doctors.
Globally there are 200 million annual pregnancies and 20% of them are high-risk. Due to the shortage of gynaecologists, Fetosense and CareMother can enable frontline workers to monitor fetal health and reduce mortality.
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What is the problem you are solving?
In India alone, 0.5 million babies are still born and 3.5 million are premature (leading to deaths and long-term developmental problems) every year, which is linked to antenatal care. Studies have shown that regular antenatal care, bridging gaps through technology, reporting results in-real time to doctors, ensuring follow-ups and effective labour monitoring can mitigate the mortality and morbidity. About 99% of these deaths occur in rural, tribal and low-income urban settings, which underscore the gaps in equitable access to services. However, there are only 35,0000 gynaecologists mainly in hospitals, who are not available to the majority. Moreover, complete antenatal care coverage via the accessible frontline workers is only 21%, partly due to their burden of other health tasks, logistical difficulties and absence of effective tools to monitor risks. The cardiotocography or ‘Toco’, the current standard in hospitals to detect term labour contractions and monitor fetal heart rate, has a sensitivity of only 68% to assess contractions and 6% to predict premature birth. In addition, Toco is expensive, bulky, needs substantial clinical expertise and high maintenance, not portable and not indigenous. Thus, only a segment of the middle and upper income urban women receive effective antenatal risk monitoring in India.
Who are you serving?
Our existing ‘CareMother’ program includes doorstep antenatal tests by frontline workers using portable diagnostic kits and a mobile application to share data with doctors in real-time. Since 2015, we have registered 30,000+ pregnancies (12000+ high-risk) via 260 community health workers across ten states of India, in rural, urban and tribal areas, with 15+ Government, non-profit and corporate partners. Our current solution will be implemented within CareMother, to focus on mothers and foetuses in two urban sites (hospitals and health posts catering to slum population) and two rural sites (primary health centres and sub-centres). These sites include 4153 registered pregnancies and 39.6% are high-risk. Indirect beneficiaries will include community health workers, midwives and doctors who will use our solution for timely management of complications (n=98 staff).
We conducted a needs assessment with 25 gynaecologists in Mumbai and 22 rural health centres to understand the requirement and availability of fetal monitoring and use-case scenarios. We found that cost and space constraints, long time to set up conventional cardiotocography with insignificant returns, and absence of remote monitoring of fetal cardiac and other critical parameters due to shortage of gynaecologists, created scope for an automated digital point-of-care solution and building referral linkages with specialists.
What is your solution?
‘Fetosense’ is a non-invasive, wireless, portable, smartphone integrated and affordable AI based fetal heart rate (FHR) monitor. We are developing an auto-interpretation system of FHR records to measure fetal cardiac function to reduce the dependence on the specialist doctor and a tool to measure uterine electrical activity to predict premature labour. Based on incoming data, we are developing a prediction algorithm to assess the consequences of poor FHR on other critical physiological parameters of the fetus. Fetosense has three distinct strengths:
1. It provides an end-to-end digital automated point-of-care solution, which can be used in low-income settings for monitoring fetal health in high-risk and routine pregnancies.
2. Simple usage that is a value addition - Health workers and midwives will only need to place a belt on the abdomen and start the device, without the need for repositioning and receive flagged fetal cardiac and associated risks, which they can report.
3. Due to its portability, low maintenance and linkage with a smartphone, Fetosense can be used for remote monitoring by doctors and in busy clinics for multiple patients.
We will implement the solution within our larger CareMother program, which includes home-based and centre-based antenatal tests using a portable kit and mobile application, used by a health worker or midwife for real-time transfer of results to doctors. Thus, our solution will be comprehensive enough to enable frontline workers to take informed decisions and refer mothers for timely intervention, to eventually improve neonatal outcomes. Fetosense is unaffected by maternal obesity and movements. It is based on Ultrasound doppler, where studies have shown that changes in variability indices like accelerations, decelerations and beat-to-beat variability significantly correlate to fetal distress (Jezewski et al, 2006).
At the Bottom of Pyramid, Fetosense will be adopted through its easy-to-use configuration and interface, portability and linkage with a smartphone app, by doctors at primary health centres, midwives and ‘doorstep’ community health workers (via CareMother). Fetosense will report transparent real-time data for effective clinical decisions – for e.g. abnormal beat-to-beat variability in FHR could be linked to fetal hypoxia and its prediction will be flagged on the mobile application. This prediction will be based on the analysis of a large sample of ‘training data’ which we are currently performing. Access to thousands of mothers under our CareMother program will allow such an analysis. Fetosense offers the aforementioned strengths at 33% lesser cost than cardiotocography machines.
Which dimensions of the challenge does your solution most closely address?
Where is your solution team headquartered?Mumbai, Maharashtra, India
Our solution's stage of development:Growth
Why are you applying to Solve?
We want CareMother and Fetosense to become an end-to-end solution that measures critical antenatal risks for the child and informs the same to doctors in the easiest way possible, by a frontline worker, and enables early intervention. To achieve that, we will need mentors from various disciplines, because our solution cuts across clinical, public health, operational and technological lines. We are confident to receive such mentoring from Solve’s diverse cross-sector community. The next one year is particularly crucial in view of developing automated fetal heart monitoring systems, predicting sensitive and specific fetal risks and communicating them to doctors for prompt monitoring. We want to avoid making technical and operational mistakes in this phase, particularly in the socio-economically complex regions in India.
We are looking forward to apply for the Innovation for Women Prize and She Innovates Prize for Gender-Responsive Innovation, as they closely relate to our work in maternal health in challenging settings of India since 2015. If we receive funding through these prizes, we can expand our technological team to recruit more expertise in AI, Machine Learning, Data mining and Statistics, to strengthen our outcome analysis.
Since our work will involve validating a fetal health prediction algorithm against real world antenatal and perinatal data, we will also need experienced public health researchers to guide us in performing data analysis (when we will begin evaluating of our intervention). We intend to publish the results in a peer-reviewed journal to add credibility to this model, for future scale-up in India.
What types of connections and partnerships would be most catalytic for your solution?
With what organizations would you like to partner, and how would you like to partner with them?
Below are the names of the organizations that we would like to partner and the details of the partnerships:
1. American International Health Alliance (AIHA): Mentoring on training and supervision of our frontline health workers under the CareMother program, especially given the diversity of these workers in India (i.e. Government workers that are salaried or incentivised, workers under non-profit organizations, workers that are facility-based and those that are ground-level)
2. Massachusetts Institute of Technology, especially MIT-D Lab, for guidance on AI, developing automated clinical results and fetal health prediction models
3. Johns Hopkins Bloomberg School of Public Health, for collaborating with senior public health researchers and statisticians with a focus on maternal health
4. Women Deliver: Since this is a global advocacy organization for improving the health of women and girls with a focus on health system strengthening, capacity-building of health workers and scale-up of evidence-based interventions, it will be useful to align with them for communicating the results of our analysis, pitching the strengths of our solution at a global level and influencing policymakers in India and abroad through their networks.
5. Organizations and individuals that would help us pitch to the local and state agencies of the Government of India: These partnerships will be critical because we would want to scale up the solution through rural primary health centres and urban health posts, which are Government health centres manned by midwives and physicians that are most community-centric in the primary health pyramid.
If you would like to apply for the Innovation for Women Prize, describe how you and your team will utilize the prize to advance your solution.
Annually, 3.5 million premature babies are born in India. Widespread maternal distress is due to the deaths in these infants and the lifelong disabilities in those that survive, such as hearing, visual and learning problems. The annual societal economic cost associated with preterm birth in the United States in 2005 was $26.2 billion and the average hospital stay was 13 days. These figures show that women in developing countries face a catastrophic financial burden due to prematurity, particularly the rural and the urban slum population.
Our solution will utilize the aforesaid prize to predict premature birth and institute early intervention to prevent prematurity or optimally manage the baby in the first hours of life. Fetosense will include uterine electrical activity monitoring, which is proven to be more accurate than the standard cardiotocography to assess the pattern of uterine contractions (Verdenik, 2001) to predict uterine preparedness for labour. Accordingly, the results can be shared with the doctor or gynaecologist, via the smartphone, who can administer tocolytics to prolong pregnancy and prevent prematurity, or give corticosteroids for fetal lung maturation if the delivery should be done. The framework of AI-powered Fetosense, within a mobile health program (CareMother) will allow frontline workers to flag the possibility of premature birth and facilitate early intervention at the 25,650 primary health centres in rural India. The prize will support the development and initial pilot (n=800 women) of this specific capability in our solution, to reduce neonatal mortality and morbidity and address a long-standing maternal need.
Dr. Ameya Bondre Head of Clinical Research and Development, CareNX Innovations Private Limited