Access to healthcare remains a significant challenge for populations around the world. Many must travel long distances, miss work or struggle to find child care to get the care they need. These obstacles can lead to delayed diagnoses, postponed treatments, and even critical emergencies.
The lack of accurate, up-to-date data to help inform decisions within their communities remains a persistent problem for public health officials and governments. We found a solution to help in an unexpected place: travel information from Google Maps.
Understanding geography and access to medical care
Emergency obstetric care is an area where these access issues are particularly pressing. Data show that long travel times between home and health facilities have a significant impact on pregnancy and delivery outcomes for mothers and newborns. access Access to emergency obstetric care (EmOC) can reduce maternal deaths by up to 50% and intrapartum stillbirths by up to 75%.
Traditionally, estimating access to these services has been based on geographic distance. But anyone who lives in a dense city knows that being located near an establishment doesn’t always mean getting there quickly. Traffic can turn a short distance into a long journey.
This has changed our understanding of the problem: it is not just women in remote areas who struggle to get to the doctor quickly when it matters most; it is also a challenge in urban areas. Last year, we therefore collaborated with the OnTIME Consortium provide travel time information to policymakers in Nigeria, Africa’s most populous country, which accounts for nearly a third of the world’s maternal deaths and where more than 50% of the population lives in dense urban areas . Together, we used information derived from Google Maps to create a tool that identifies hotspot areas where women take a long time to access care. The dashboard estimates travel time to the nearest, second and third closest emergency obstetric care facility for different regions, showing us how long we could expect it takes for a pregnant woman to get to a facility where she can receive emergency care. obstetric care.
We wanted to give public health officials, researchers, and anyone who needs it data-driven insights to identify areas with limited access to EmOC, allowing them to plan improvements to road infrastructure and ambulance routes and upgrade or build new facilities. For example, it has helped organizations like Emergency response in Africa make informed decisions on resource allocation. And we hope this will help others understand the relationship between geography and socio-economic equity.
Expand access to care
We also help shape the conversation around inequalities in access to EmOC care. And beyond EmOC care, we are working with other public health partners to build a clearer picture of access challenges, such as wide accessibility to health careas well as access to vaccination sites as well as parks and other outdoor spaces.
We’ve been exploring ways AI can solve access problems for years, for example by developing AI models for tasks like wayfinding. tuberculosis in chest x-rays and interpretation the size and position of the fetus during pregnancy. We’ve integrated these models into wearable devices so healthcare professionals can easily use them in their communities, instead of requiring people to travel to a doctor’s office for these critical exams. Our tools, including Open Health StackHelp developers around the world adopt health data standards for apps.
We will continue to explore new ways our technology can bring healthcare to more people. Whether it’s launching new tools, enabling more research, or finding creative uses for our products, we will continue to help people around the world live healthier lives.