How Smartphone (Big) Data Can Make Healthcare Smarter
I’ve written numerous times about the tremendous possibilities for improving medical research when traditional medical data is combined with the new wave of user generated data. The National Institutes of Health launched a Big Data to Knowledge Initiative back in 2013, which is a trans-NIH program with funding from all 27 institutes and centers.
The latest project to emerge from the initiative is a huge new study that was tracking physical activity of people from over 100 countries via anonymized smartphone data. The huge dataset allowed researchers to analyze step data according to country, gender, and community type.
“Big Data is not just about big numbers, but also the patterns that can explain important health trends,” the researchers say. “Data science and modeling can be immensely powerful tools. They can aid in harnessing and analyzing all the personalized data that we get from our phones and wearable devices.”
The data was harvested via the free Azumio Argus app, which is used for tracking physical activity via the sensors built into all smartphones. In total, some 68 million days of data were generated, with researchers given minute-by-minute insight into the activity of over 700,000 people from 111 countries.
“The study is 1,000 times larger than any previous study on human movement,” the authors say. “There have been wonderful health surveys done, but our new study provides data from more countries, many more subjects, and tracks people’s activity on an ongoing basis in their free-living environments versus a survey in which you rely on people to self-report their activity. This opens the door to new ways of doing science at a much larger scale than we have been able to do before.”
The team used the Gini index that’s traditionally used to calculate income inequality to measure activity inequality in each country. The hope was that understanding activity distribution would provide crucial insights into the health diversity of a country.
