India is expected to have 1 billion smartphone users by 2026 with rural areas driving the sale of internet-enabled phones.

Why this area?:

Advances in technology have not led to significant improvements in health outcomes for people, especially in the lower two population quintiles. Much of the attention has been on devices and diagnostics, and though important, these need to be used in low-resource settings for them to lead to an improvement in people’s health. Understanding attitudes towards technology, the constant evolution of technology itself, poor knowledge and skillsets for technology use, infrastructure and finance requirements, and the interoperability of various technologies, are all critical factors that affect the consistent use of technology.

We believe that technology is an enabler, and our focus is on using the appropriate technology solutions to enable vulnerable groups to achieve health and well-being. We work with a range of technology partners, solutions (like water purifiers, thermal imaging), and community contexts to understand the value,  and possibly, strengthen the healthcare ecosystem.

What we have done:

We use Point-of-care diagnostics (blood glucose, hypertension, vision, anaemia, breast examination) in our community health interventions, where we bring ethical medical screening and diagnostics, along with care protocols to work for people. This has led to us learning not just about the devices, but also the models (financial and operational) that work best, in low-resource settings.

We developed an application to serve a cohort of 1,21,000+ people, and ensured that services that reduce their vulnerability were delivered, resulting in community engagement increasing from 56% to 73%, over two years. This experience taught us the importance of standardised workflows at the frontlines, and led to the development of DICEFlow, supported by Cisco Corporate Social Responsibility. This solution is now used within our primary healthcare work, where we will be working on improving TB detection among children in urban poor settings, in collaboration with IIIT-Delhi. We also worked with IIIT-Delhi on applying Machine Learning techniques to discover the influence of non-obvious factors for improving safe-sex practices in FSWs, supported by a grant from Google AI Research. 

The United Nations Office on Drugs and Crime, Nigeria, and the Government of Nigeria uses our Milestone App for effective decision making and better management of projects.