In the not-so-distant past, government's involvement in community health generally was limited to providing services for treating illness. Today, we increasingly define public health in terms of improving wellness. Guided by data-driven insights, cities and counties are moving as never before to address the root causes of illnesses that disproportionately affect their jurisdictions, allowing for more focused prevention and treatment.
Some policymakers have already had notable success with wellness-based approaches to public health. Oklahoma City famously went from the "fattest" to the "fittest" list in 2012 when its residents, led by the once-portly Mayor Mick Cornett, collectively shed a million pounds and recorded their progress on a website devoted to the project. In 2014, Austin, Texas, worked with Children's Optimal Health, an Austin-based nonprofit, to map body mass index and cardiovascular fitness scores and convene educators, health experts and community members. Other interventions in communities around the country -- such as soda taxes, calorie "nudges" and bike-sharing programs --- have shown tremendous promise for improving public health.
Just as new diagnostic tools, fitness apps, digital monitoring devices and DNA breakthroughs are changing personal health with new data, public health is undergoing a revolution in the way it approaches epidemiology.
Censuses and anecdotal data -- the policymaker's stethoscope and tongue depressor -- are being supplemented with the information bounty of the Internet of Things, data dashboards and social media. We've profiled a number of these developments on our Data-Smart City Solutions website: how social media is guiding restaurant health inspections, how vacancy rates can predict outbreaks of Zika and how GPS-equipped inhalers are tracking asthma triggered by pollution.
The past few months have introduced a new class of data tools to assist policymakers in their quest to make communities healthier and more productive, tools that access new data sources using sophisticated statistical analysis.
Last November, for example, Blue Cross Blue Shield launched its Health Index, which analyzes the claims of 40 million commercially BCBS insured members across 200 health condition categories. The BCBS metric allows counties to compare themselves with demographically similar counterparts and pinpoint major threats to public health. A county that learns that it has a disproportionately high incidence of hypertension or diabetes, for example could not only investigate the root causes but also could also address diet, exercise and land use as well as treatment options.
Shortly before the launch of the BCBS index, the Centers for Disease Control rolled out the 500 Cities project in conjunction with the Robert Wood Johnson Foundation and the CDC Foundation. The project uses "small area estimation" methods to identify city- and census-tract-level data that in the past has been obscured by the fact that many cities span multiple counties. This effort represents the vanguard in generating the kind of granular, highly targeted population health data that promises to unlock new insights.
Cities also have worked with the nonprofit sector to come up with an impressive assortment of new tools. The city of Santa Monica, Calif., with the help of a Bloomberg Philanthropies, has produced its own in-house health index, the Wellbeing Project, which promises to help configure local government priorities to address wellbeing. And Data2Go.nyc, created by the nonprofit Measure of America with funding from the Helmsley Charitable Trust, allows users to map a number of New York City-related health variables, such as deaths from cancer or pre-term births, against demographic indicators such as race, income and education level. A holistic understanding of the relation between health and identity is invaluable to policymakers in the fight to ensure that the neediest populations in a city are served.
As these data intensive tools continue to crop up, policymakers will be able to refine their understanding of what really ails the disparate populations of communities across the country. And I expect that the more we can compare and contrast data across indexes like the ones listed here -- creating, in effect, an index of indexes -- the more confident local governments will become in designing better approaches to preventing illnesses and treating them when they do occur.