Online population health tool illuminates socioeconomic factors

Jennifer Bresnick Health IT Analytics January 20, 2017 Community Health

Healthcare stakeholders looking for insight into the socioeconomic and environmental factors impacting the wellbeing of their populations can now turn to the City Health Dashboard, an online tool detailing the challenges of urban patients.

Developed by researchers from NYU and the National Resource Network, and supported by the Robert Wood Johnson Foundation, the big data dashboard currently includes twenty-six socioeconomic measures for a starting set of four cities across the nation.

“We created the City Health Dashboard in response to local demand for more accurate data about the health of our cities’ citizens,” says Marc Gourevitch, MD, MPH, chair of the Department of Population Health and principal investigator for the City Health Dashboard.

“City leaders know that ‘what gets measured is what gets done.’ They want accurate, actionable data so they can improve their population’s health, bring down health care-related costs, and focus on community wellbeing. We’re excited to be the first to provide this important information at the city level in a uniform format across a wide range of health conditions and health determinants.”

The tool allows users to explore key health behaviors, outcomes measures, clinical care factors, social and economic traits, and physical environment features in Flint, MI, Kansas City, KS, Providence, RI, and Waco, TX.  Data is available at the city level for all metrics, and at the neighborhood level for certain others.

Socioeconomic disparities, including lack of access to healthy food choices and transportation, housing and utility insecurity, and risk of interpersonal violence, have taken center stage in the population health management debate over the past few years.  As healthcare providers begin to tackle the enormous influence of the patient environment on ultimate outcomes – accounting for up to 80 percent of a patient’s health in some estimates – the integration of non-traditional data sources into patient management programs has become a top priority.

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