This week in conjunction with the American Public Health Association Annual Meeting, we are hosting thought leader interviews around the future of health and health care. Thomas Goetz, managing editor of WIRED spoke with us about the potential for "big data" to inform better community health.
What is a strong example of how better data has improved community health?
There is a great project called the Healthy Communities Institute, which is run out of the Bay Area. They have taken publicly available data on communities, including basic population data from county and state health departments and state census departments, and basically crunched it. They create these awesome dashboards for care providers or health care organizations so community hospitals or public health departments or nonprofit care clinics, for example, get fairly simple infographics that give the care providers a sense of the context in which they are providing health. These data help them understand the macro trends that are going on around things like infectious disease rates or chronic disease in the population. It informs, in real time, the way that any care organization might be delivering their care and what they might be choosing in terms of their priorities.
Traditionally a lot of these priorities of community or public health are determined at best in a kind of big time lag where you are looking at year-old data, and driven often, unfortunately, by political interest or the most visible or the most vocal population. This organization has really combined the basic goal of public health, which is to maximize the health of a population in the most efficient way, with really intuitive infographics and data analytics that put people in a less reactive stance and a much more of an immediate response mode.
In what ways does data have the potential to make a difference in improving health?
The thing about data generally is that it lets you understand an issue, measure an action, and adjust in response. That’s the basic mode of science: you measure something; assess whether it's improving it, having no effect or making things worse; and then you adjust course. What the new mode of data does is really that same principle that has been around for 150 years, but it lets us do it in a much quicker time frame in terms of gathering the data, assessing the data, and making the judgment based on it.
Another thing is, all sorts of different data are coming online, so you look at things like environmental data and exposure data that you are able to map. You think about disease clusters and other kinds of efforts at understanding how to do this work in a geographic framework, but it’s just really been hard to connect what seem like patterns with actual correlations, because the data is very wispy. In this new mode of constant measurement and of combining data sets with much more agility, you are able to get, with much more certitude, to exposures and disease rates in populations, and basically open a new lens onto the geographic component which is a huge component of community health.
Mapping tools have been in use for at least a decade in public health. Those have been largely in proprietary systems where the software is expensive and hard to come by, and the data is kind of scant and thin. Now in just the last five years or so we’ve made this huge leap where the mapping tools are publicly available through Google Maps and other open-source or largely free tools, and the data sets are just pouring online as well. So you have these robust sets of data that you are able to combine with mapping tools, and that gives you a greater depth of information with which to make assessments.
How does leadership make a difference when it comes to using data to improve public health?
The leader is the one who has the opinion that determines the organization's policy. What we are moving into in a data-rich world is a very different kuse of leadership. Now you are looking to the leader to present the right questions, not provide the answers. That’s a very different way of leading an organization. Answers are no longer based on a leader's intuitive grasp of an issue. And when it comes to a leader deferring their own judgment to that of the data, that’s a very big shift, but I think that’s the kind of mode that we are going into.
I’d add that too often people think of data and analytic tools as this new world that is not their own, and so they will just wait for some other organization to figure out what the standards are and then adopt it when that’s figured out. That isn’t really how technology really works. Technology is this constantly iterative process of fixing and trying to make things work, but there is increasingly no such thing as the perfect product. Also, this world of data and technology really is the same language that people have been speaking in community health and population health for decades. It is statistics as basic epidemiology. In many ways, public health is way ahead of the game in its use of data. People in the field already speak this language; they just need to figure out what the new tools are, and what the new opportunities are.