Health Matters!

January 21, 2014
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Americans spend more on health care than any other industrialized nation, yet our health outcomes are considerably lower. We are simply not getting our money’s worth when it comes to health care spending. Experts have long known that these high costs are due to a number of factors, including the costs associated with preventable diseases and a perverse health care system that rewards doctors for keeping patients sick because of a fee-for-service reimbursement arrangement.

On January 14, The Clinton Foundation hosted the 2014 Health Matters Conference in effort to engage businesses, governments, NGOs and individuals in a dynamic discussion about health and wellness in the U.S.  Panelists addressed a number of health care issues, including health transformation and cost, mental health and prescription drug abuse, using digital platforms to improve health behavior, closing the health divide, and promoting healthy lifestyles.

Conference presenters suggested a number of ways to mitigate the burdens felt by so many Americans, who are spending such a high percentage of their incomes on health-related costs. They suggested emphasizing preventative care and incentivizing medical providers to keep patients well. They also stressed the importance of personal responsibility for health maintenance and ways that new technology can encourage individuals to choose healthy behaviors, which can reduce occurrences of chronic diseases, particularly those associated with obesity. One of the more troubling issues discussed during the Health Matters Conference is the disparate health between different demographic groups. A few examples discussed during the conference were as follows: 1 out of 3 Latinos in the United States are without health insurance; women are more likely to die of heart attack than a man, and they are more likely to receive inferior care to men; and Native Americans suffer Type II diabetes at a disproportionately high rate. Poor Americans have the worst health and the least access to health care.

In Louisville, as in the entire nation, we see enormous disparities in health outcomes. Panelists at the Health Matters Conference discuss how much ZIP code affects health, much more than medical care does. A recent report by the Louisville Metro Center for Health Equity reflects this as well. It was reported that residents in our poorest neighborhoods have a life expectancy of 67.3 – 70.5 years[i], while on the other hand, residents in our more affluent neighborhoods can expect to live up to 13 years longer. We know there are many social determinants of health, and ethnicity is one of many such determinants, along with education attainment, income, and more.

In order to build a Greater, Healthier Louisville, it is imperative that we understand the direct and indirect influence of health in seeing positive outcomes in jobs and education and experiencing a greater quality of place.

[i] Smith, P. et al. (2011). Louisville Metro Health Equity Report: The Social Determinants of Health in Louisville Metro. Available at http://www.louisvilleky.gov/NR/rdonlyres/29925903-E77F-46E5-8ACF-B801520B5BD2/0/HERFINALJAN23.pdf.

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Natural Breaks Algorithm

For each indicator, Greater Louisville Project assigns cities into one of three groups (high-performing, middle-of-the-pack, and low-performing) based on how they compare to other cities. The assignment is based on how cities naturally cluster on that indicator. Sometimes, the differences between cities are very small, and the difference between a city ranked 5th and 6th could simply be a matter of the sampling error that arises from using survey data. Thus, rather than always make a division that declares the top 5 to be the top tier, we use a natural breaks algorithm to look for a cluster of cities that is outperforming the rest, a cluster that is about average, and a cluster that is lagging. This clustering gives us a better indication of where Louisville is thriving and where Louisville has room to learn from cities that are doing better.

Z-Scores

Z-scores (or standardization) is a way to combine data with different units of measurement into a single index. The z-score is a measure of how far away a city (or census tract, etc.) is from the average city. In order to be comparable across different units of measurement, the z-score is the distance from the mean measured in standard deviations (e.g. if Louisville has a z-score of 1 it means Louisville is 1 standard deviation above the mean of its peer cities).

Data from the Robert Wood Johnson Foundation's County Health Rankings use z-scores and all z-scores are relative to the mean of Louisville's peer cities. (On the County Health Rankings site z-scores are relative to all the counties in each state - thus z-scores reported by GLP will be different, because we are using a different reference group). The Greater Louisville Project also uses z-scores in our multidimensional poverty index, which compares each census tract to the mean of all census tracts in Louisville.