The AI4HealthyCities Health Equity Network has been launched as a global initiative to reimagine how cities tackle heart health inequities using artificial intelligence—starting in New York City.
The New York University School of Global Public Health (NYU GPH) has joined the network—created by the Novartis Foundation in partnership with Microsoft AI for Health— which aims to use data science techniques to provide health authorities, health system leaders, and other decision makers with insights and tools to help identify the root causes of heart health inequities. These insights will demonstrate how health outcomes could be improved by changing the underlying social, economic, and environmental determinants of health, such as housing, pollution, access to fresh food, opportunities to exercise, racism, wealth, and lifestyle.
Applying data science and artificial intelligence to health and neighborhood information will help urban policymakers target public health resources towards the interventions that can have the greatest impact on cardiovascular disease—the world’s number one cause of death and a leading driver of health inequities in the United States.
“Where people live and work in New York, and their degree of social and economic disadvantage, have a bigger impact on their risk of developing cardiovascular disease than their access to healthcare,” said José Pagán, professor of public health policy and management at NYU GPH, in a statement.
“This initiative will give us better insights into the cardiovascular health of New Yorkers in an effort to identify the most pressing issues to address and shape our city’s policies,” added Pagán, who also is chair of the board of directors of NYC Health + Hospitals, New York City’s public hospital system.
As part of AI4HealthyCities, NYU GPH will lead research in collaboration with Microsoft AI for Health by bringing together data on cardiovascular disease and key social determinants of heart health in New York City. The researchers will evaluate which social determinants are most strongly linked to high blood pressure, a leading cause of heart attack and stroke that affects roughly one in four New Yorkers, particularly Black and Latino adults. The project also aims to create a neighborhood-level cardiovascular risk score and map that can be used by local health leaders to guide their efforts to improve heart health.
“Combining anonymized population data from many different sources enables us to use machine learning to go down to street level in assessing levels of cardiovascular risk. If properly applied this could revolutionize preventive interventions in heart health,” said Juan Lavista, chief data scientist at Microsoft, in a statement.
“We know social determinants play a significant role in shaping health outcomes and disparities. A data-informed approach to addressing these structural drivers of health inequities starts with fostering interdisciplinary efforts that incorporate insights across multiple disciplines and sectors,” said Ji Chang, assistant professor of public health policy and management at NYU GPH and the AI4HealthyCities project’s principal investigator, in a statement. “We are excited to work with our partners to further investigate the mechanisms connecting social determinants to health outcomes and inequities.”
