Big data holds the promise for helping solve big problems and improve health. In their book Big Data, authors Kenneth Cukier and Viktor Mayer-Schonberger describe how tracking flu symptoms via Google searches is much faster than the traditional methods used by the Centers for Disease Control (CDC).
The problem with traditional data collection on health such as those at the CDC is that they can be time-consuming and cumbersome. A key reporting mechanism that the CDC uses is from doctors, who are, in turn, reporting on the patients they’ve seen in their office consultations. Relying on these reports builds in a delay of a week, sometimes longer, into the data the CDC is collecting.
Big data, the data that’s collected already in a variety of ways, can be mined, analyzed, and curated in ways that can help improve health of whole populations, not just individuals. As with the example of the Google flutrends, there is some hope for addressing asthma through the use of big data.
Making progress in the treatment of asthma requires data outside of the self-reported information from asthma sufferers that doctors generally rely on. The new Asthmapolis may offer part of the solution. Asthmapolis seeks to eliminate the “inability to collect information about where and when people develop symptoms.” Asthmapolis uses inhaler sensors, mobile applications, advanced analytics – in other words, big data – to help physicians identify those patients who need help controlling the disease before exacerbation.
How does this research impact the public? In Louisville, Kentucky, for example, a city with particularly difficult air quality conditions for those with breathing disorders, Asthmapolis teamed up with health officials to collect data by sensor in the inhalers of project participants. This helps Asthmapolis and city leaders understand when and where people with asthma develop symptoms, in turn identifying community-wide asthma triggers that can be eliminated. This means that using big data has the potential to improve health by monitoring individual asthma attacks as well as creating population-level changes in environmental policies that may trigger asthma.
Some policy makers and physicians have raised the concern that the nation’s most pressing health epidemics are in fact appallingly low-tech, and that it’s local reforms and relationships, not high-tech solutions that are needed. The brains behind Asthmapolis are trying to fuse the two approaches together; the on-the-ground experiences of asthma sufferers, the technology that allows for location-specific data, lightweight sensors, and continual monitoring, with a continued conversation about enacting real change on the municipal level.
As promising as Google flutrends and Asthmapolis are, big data raises big questions about that information gets used. Do we have faith in our institutions to create change that will improve health for everyone from the enormous amounts of data that such a project will gather? Or, will political action still be necessary to compel leaders to do the right thing? Only time will tell.
