Providing Remote Maternal Healthcare

Every day in 2017, approximately 810 women died from preventable causes related to pregnancy and childbirth. The World Health Organization shows that 94% of all maternal deaths occur in low and lower-middle-income countries. High maternal mortality rates in many countries around the world stem from the lack of basic maternal education. Many women in developing countries lack access to the internet and encounter accessibility issues when trying to get affordable healthcare. High maternal mortality rates in some developing countries are a result of birth-related infections caused by a lack of caution and care during pregnancy.

The specific problem and area that we intend on targeting is maternal mortality in Bolivia. Bolivia has the highest maternal mortality rate in the western hemisphere (160 per 100,000 live births) and this is a direct result of poor maternal education. High maternal mortality rates is usually a combination of poor healthcare infrastructure and long travel distances coupled with low accessibility to quality healthcare. In 2019, the government of Bolivia built 2,710 clinics to increase accessibility yet still only 20% of the rural population has access to proper healthcare. The Unified Health System in Bolivia guarantees free healthcare, but the government is unable to make this goal achievable and sustainable. Doctors expressed the need for a budget of around $1 billion USD but only received about $200 million USD. Because of the lack of funds, there are not enough supplies or facilities available to provide the healthcare and education that so many Bolivians need. Even when citizens have a right to free healthcare, there are additional boundaries that may prevent them from getting the help they need. Bolivia’s rural areas tend to be much more burdened with poverty than urban areas. Additionally, there are usually fewer health clinics that are easily accessible in rural areas.

Our solution is an SMS-based messaging system designed to educate mothers about maternal health through simple checkpoint messages throughout the pregnancy and on-demand question answering. The use of GPT-3 and NLP will ensure mothers are receiving the latest information specific to the conditions of their region. Natural Language Processing and Natural Language understanding will be utilized to make questions and answers clear and easy to understand (in both English and Spanish) for mothers in Bolivia. The GPT 3 and NLP/NLU are trained with huge internet datasets, it’s able to process and understand text effectively. Through routine data collection from women (ex: asking about pains, morning sickness, eating habits, sleeping patterns, etc.), our solution provides valuable insights based on patterns to help prevent complications before, during, and after birth. Through our referral program, we are able to identify potentially threatening situations and direct mothers to partner healthcare centers to seek medical attention. 

You can read more about our solution here: mamitahealth.com.

For the moment our solution isn’t in use, but in the next year, we plan on at least having a user base of 5,000. We are currently piloting with small groups in remote areas and making improvements on our prototype. We are working on forming partnerships to effectively distribute our solution once it as able to be used. 

We’ve taken many steps to get a better understanding of where we intend on piloting.

We reached out to doctors and healthcare administrators to get a better understanding of the Bolivian healthcare system and its infrastructure. During our conversation, we ran our idea by them to receive validation and if we would actually be able to implement it in Lake Titicaca. The doctors approved of our idea and they said they would be willing to market this idea to women in the nearby area. We also talked to many Bolivian women to get a better understanding of their day-to-day lifestyle and see if they could actually use our SMS bot. We talked to families and tried to understand some of the sentiments regarding maternal healthcare and while we understand that maternal education is considered a taboo and difficult to talk about the topic in the country, many organizations in Bolivia have succeeded in bringing awareness to issues concerning women’s health.

We’ve also been able to reach many women in Bolivia through social media platforms like Facebook who’ve been able to give us more insight into the problems their communities face regarding maternal healthcare and validation around our solution. We have validation from the VP of MSI Reproductive Choices (which gives contraceptives to women in many developing countries), Andrew Seddon and Karima Ladhani (founder of Barakat Bundle).

As a woman, I've experienced many common issues regarding seeking care for problems considered taboo within my culture. My mother, living in many developing countries for the majority of her life, has experienced firsthand, many issues regarding receiving reliable information and care. I wanted to create a solution for women like her who want to do what is best for their children but lack the proper understanding and resources to take good care of themselves while they are pregnant. In rural communities in India, volunteering in different hospital centres, I've experienced the faults of the healthcare systems in developing countries which stems from a lack of fundamental understanding of what is normal for a woman to be experiencing and what is not. Furthermore, in less educated, rural communities, both education and healthcare are extremely inaccessible. My experiences working in these communities uniquely position me to understand the challenges and struggles of women who seek reliable education regarding their bodies. While the focus of our pilot is on Bolivia, we would like to run tests in other countries as well. We've been in talks with organizations for partnerships in Bolivia and other regions in Sub-Saharan Africa and South Asia. We are planning sites in these countries to effectively monitor the impact of our solutions and hire people on the ground to grow the project.

My team has a heavy background in technology. Personally, I've worked in AI and Blockchain. I have worked in the Blockchain for Good area and started projects for social impact with cryptocurrencies. I have experience with project management and have successfully delivered consulting projects working alongside companies. I've been involved in the startup scene, advising small startups and working on the founding teams of different projects. Overall, my knowledge and experiences working within different teams and environments make me equipped to get the right people to make this project a success. 

Website: https://anyasingh.ca 

Linkedin: https://www.linkedin.com/in/an...

I am applying to Solve because I think this project has enormous potential to make a positive change for women in the developing world. I think Solve will help me overcome some of the barriers I'm facing as I try to engage stakeholders and hire more people to make this project successful. While raising funds has been an issue, I've managed to secure funds to run a small pilot in a region in Mexico. I believe mentorship and advice on implementation and scaling as well as getting the right people would be extremely valuable. I would also like support in improving the technical aspects of the solution. I believe I lack experience running pilots in the healthcare sector which is fundamentally different than a lot of other areas. Specifically, I would like support in deciding how to source talent and where to concentrate efforts when it comes to piloting. Determining the right times and costs for implementing a pilot has also been a challenge so someone with potentially more experience and knowledge could help advise on the right times for a solution to be implemented. Personally, I would benefit tremendously from support to improve the business model and working on improving distribution and managing financing with this fast growing project.  

This solution is innovative because it aims to address the issue of maternal mortality through the use of Artificial Intelligence and SMS-based messaging technology. Currently, technology isn't used to address healthcare issues in developing countries. However, my solution leverages the infrastructure currently in place to solve a huge issue - the lack of healthcare education in an engaging and informative way. I expect that with the greater use of the solution, topics and ideas conventionally considered taboo will be discussed more often. I expect that in the long run, more conversation around female bodies will help break down barriers for women in the healthcare sector. 

Our impact goals consist of 2 main objectives: increasing institutional healthcare visits and increasing the rate of maternal education. Our solution intends to increase the number of women who seek help by raising red flags earlier on so they can receive the right support before it becomes too late. To measure this impact, we’ve connected with healthcare providers, administrators, and physicians to help track our growth and as a means of accessing more potential users for our solution. Currently, Bolivia lacks a structural system of providing maternal education to women. Our solution will fix this issue by prompting women to relay back information they’ve been given and identify next steps for their actions after being given the information. This will help us not only improve our algorithms and models to provide more accurate and understandable answers, but also give us a good starting point of understanding the potential impact our solution is having on the lives of Bolivian women. Our plans to achieve this goal are to connect with more healthcare professionals and establish a firm initial user base. Through this user base, we intend on partnering with MSI reproductive choice. With this partnership, we’ll be able to outreach to more mothers in Bolivia and they’ll be aware of our service. Establishing advertisement partnerships is vital in keeping our solution financially sustainable. Following all of these steps, we’ll pilot our solution and hopefully achieve our impact goals. 

You can read more about our plans here: https://drive.google.com/drive...

In order to measure the impact of our solution, we’re going to track the number of users. For our pilot, our goal is to start with 5000 users and we will track the increase/decrease of our users. Success for us is to notice a 15% increase in users over the months. Tracking this data would allow us to track conversion rates and effectiveness of our solution. If our users are going up, our distribution channels are effectively reaching new users. The next piece of data that we’ll be able to use to measure our goals are the number of recurring users. With access to data such as recurring text messages, we can measure how successful our product is. If users are returning, they are most likely satisfied with the service. On a monthly basis, if at least 50% of the users are returning, we know that our current system is effective and working. Tracking message use would allow us to improve our technology to ensure that we’re meeting our goals. The last data point that we intend on tracking are the increased number of hospital visits. One of the biggest issues we identified was the lack of healthcare visits and we hope that solution prompts mothers to visit the hospital often. We’re going to be in contact with doctors in the place of our pilot and if we’re able to see an increase in the number of visits, our solution has been a success. Seeking medical attention is vital in lowering the maternal mortality rate. 

Implementing the solution in rural areas will increase access to maternal education for women. Women will be able to accurately assess their health and that of their babies. They will receive periodic updates and be prompted to enter data regarding their health during pregnancy. 

Through word of mouth and partnerships with distribution centres, I expect that women will become more comfortable seeking help in a frictionless and free-of-cost way. 

Operating on a wide scale we hope to be able to visit a large number of locations every year to reach women living in remote, rural locations and urban slums where clinics and hospitals are scarce, too expensive to reach, or there’s a shortage of skilled staff and equipment.

We want to reach women living in areas where healthcare options are limited and aren’t readily available. Women living in poverty who can’t afford check-ups and young people particularly young girls, who are put off by services that may be judgemental or non-confidential are less likely to access public healthcare services. 

We want to break down barriers with our solution and help women become comfortable seeking confidential, easy to access, and reliable healthcare wih just the sending of a simple text message. 

In the long run, data about women's health in developing countries can be aggregated and collected to develop more solutions to improve women's healthcare in developing countries. Data on women's healthcare is scarce - this solution can help more companies enter the market and provide women with affordable services and products that reflect their bodies and challenges. 

The core technology is AI and GPT-3.

GPT-3 is trained with huge internet datasets, it’s able to process and understand text effectively. The AI is constantly updating the database with new information to ensure the model stays relevant and is always up to date with the latest information. GPT-3 uses data compress while it’s training/consuming data. It converts the word input into a vector. After this is done, the model unpacks the compressed text into human-like sentences. Through this process of unpacking and packing data, the model’s accuracy is further developed. The second component of our solution is Natural Language Processing. Natural language processing would allow our solution to condense language and summarize the text in meaningful ways for women in Bolivia in both Spanish and English. NLP is used for the processing of written text. After the text has been processed, the GPT-3 is used to retrieve user data from a database. The system also has theories from semantics to guide comprehension based on Bolivia’s literacy rate and English language education. Competing semantic theories of language have specific trade-offs in their suitability as the basis of computer-automated semantic interpretation. These range from naive semantics or stochastic semantic analysis to the use of pragmatics to derive meaning from context. Semantic parsers convert natural-language texts into formal meaning representations. These 2 technologies allow us to deliver effective and efficient maternal education to mothers.

We're currently working on implementing audio and image functionality. The AI Model will soon be able to generate images based on a library to provide more descriptive care to mothers remotely. As our team grows, we would like to incorporate other forms of information sharing like videos and animated images. 

To incorporate equity, diversity and inclusion, we aim to create a workspace and organizational culture that appreciates and celebrates diversity. My team of 7 represents individuals from 3 different countries and of a variety of backgrounds. I am committed to increasing equity and bringing more women into Mamita Health. As a fundamental tech company, there are many opportunities we can create to promote STEM and technology for women and girls everywhere. I am currently seeking to employ more talented women in developing countries (namely India and Bolivia). I believe that by fostering diversity and a culture of appreciation within Mamita Health, we can gain more perspectives, scale quicker, and address the needs of women all over the world. I strive to create an inclusive and equitable environment by being flexible to the needs and wants of my team. I strive to make e very experience rewarding for the team. I believe a committed, driven, and passionate team is all that is needed to create a product that could revolutionize maternal education as it is done today. 

Mamita Health's business model consists of two main parts: ad revenue and data use. 

SMS Marketing is an effective tool for businesses to market their products to customers who may be using the solution. Through a vetting process, we would like to help companies expand their market and provide women with affordable products and services that could potentially be beneficial to their health and wellbeing.

The solution allows for easy integration with an ad service revenue model that allows text messages to be sent at no cost to women in Bolivia. SMS Marketing is a useful and effective strategy for businesses to reach new customers and build brand awareness. Reaching customers in remote areas has always been challenging for businesses but through SMS messaging, businesses can reach all kinds of new customers willing to try out their services and products. 

SMS messaging is a relatively inexpensive way of marketing and reaching new customers. At an affordable price, many businesses prefer SMS marketing to other traditional forms like email and social media. Giving businesses the power to reach potential customers in new areas makes an ad service model highly desirable especially when used for funding to solve this problem.

Exposing women to products and services that are affordable and have a positive impact on their quality of life and health can provide them with greater access to diverse products. Our team plans to vet ads for relevance, affordability, and usefulness to ensure that our service is always serving its purpose.

Data collected from women can prove to be useful information for the scientific community and the creation of new solutions aimed at improving the quality of life of women and girls. Through data extrapolation and aggregation, Mamita Health can become a powerful bridge to obtaining data on female healthcare in developing countries.

The SMS messaging solution is designed to collect data from women regarding their health over time. Through this process, we can collect information regarding pains, sicknesses, infections, and more from women in rural communities that are not served by traditional institutions in an easy and cheap way.

The backend of our platform stores the data collected for easy access and analysis. Aggregating the data from a high level can help get a broader understanding of issues concerning women’s health in countries lacking the infrastructure to track such metrics in an effective way. By aggregating data, we can ensure that privacy is maintained and isn’t specified towards one woman.

The data can help women understand their pregnancies on a deeper level by alerting them about patterns in their health that may be alarming. Data can also be used for the government to decide where to increase healthcare funding and effectively allocate funds for the most efficient use of their resources. From a health standpoint, many developing countries and regions lack sufficient data on healthcare. The data we collect can be sold to other organizations as well.

The plan for becoming financially sustainable is to utilize the business model above. Currently, we are applying for grants and competitions to be able to use the funds to improve the AI model and hire resources on the ground to assess the effectiveness of our solution. In the future, we would like to have a formal contract with governments to provide a steady revenue source and of course greater distribution. For now, as we are working on improving the solution based on feedback from early users, funds from grants are being used for prototypes and costs associated with sending an SMS message. Ad revenue should cover expenses in the long term and additional revenue brought into the company will be used to financially compensate the team members working hard on this project. Partnerships we're working on establishing with large organizations will serve to decrease costs associated with the distribution and advertising of the SMS messaging service. 

We have received grants and donations from city governments. The City of Markham provided $1000 CAD in funding for the project. The Healthcare system in La Paz has established a small fund to help provide remote maternal healthcare around Lake Titicaca, a remote area around the city of La Paz. Additionally, we are working with Twilio to get a discount for SMS messaging to allow us to keep Mamita Health free. Since we are currently not operating off of ad revenue due to still making iterations on our AI model, grants and other award money has helped us in being able to test the model. We are committed to improving our solution, building out a viable prototype and then getting to piloting as soon as possible. Revenue generation is secondary; we want to make sure our solution is making a real impact on the lives of women. With a passionate, dedicated and driven team, I believe that we can make a big difference within maternal healthcare.