IBM has launched a multi-year research effort to connect and analyse huge collections of data from a wide variety of sources in order to enable individuals, governments and businesses to better understand which actions to take to improve human health. The project will initially focus on solving the issue of childhood obesity.

The IBM Research project will combine and analyse massive data sources that have never before been integrated to simulate the cause-and-effect relationships between agriculture, transportation, city planning, eating and exercise habits, socio-economic status, family life, and more. Predicting real-world reactions that influence human health, the project aims to provide fact-based recommendations of actions to take and ones to avoid.
"Our ability to advance the health of our population is currently limited to maintaining healthy life choices and working within a health care delivery system because it's been impossible to understand and to quantify precisely how each factor in our environment plays a role," says Dr Martin Sepulveda, an IBM Fellow & vice-president: Integrated Health Services at IBM. "We hope the results of this project will help individuals, governments and businesses actually understand exactly how the actions they take affect health – and then work together to make better decisions that make it easy to be healthy."
In the US, chronic diseases such as diabetes, heart disease and obesity account for 70% of all deaths and more than $1,5-trillion of healthcare spending annually. Factors far beyond the traditional healthcare system – including finance, urban planning, individual behavior, disease transmission, clinical research, media and many others – influence human health. Understanding these interconnected factors is critical to developing effective programmes that enhance health and well-being.
Today, only simple cause–and-effect connections can be made because of the way in which information is collected, stored and accessed.
For example, the connection between obesity and processed foods or lack of exercise is widely acknowledged, but in many cases it is a guessing game as to whether a bigger impact would be made through incentivising a new health food retailer to move into town or expanding the bus routes in an area with a high concentration of dual-income families. These are the complex interactions that make up a 360-degree view of health and the kind of advanced simulations IBM researchers are working to develop, with the goal that they can help predict which programmes would be most successful before they are implemented.
The IBM project could help pinpoint incentives governments and businesses might offer or what types of investments might be needed and how to prioritise them.
"In many cases, the data and models exist. They just need to be put together in a consumable way that shows the wider connections and potential actions that can enhance individual and community health," says Paul Maglio, research scientist at IBM Research – Almaden. "This is a huge challenge from both a social and technological perspective, but we believe our expertise in service science, computational modeling, math and large-scale analytics can help answer these important questions."