Geographic & Economic Maldistribution
Geographic Maldistribution of health care is usually thought of as the inability of individuals living in rural areas to tap into the health care delivery system, primarily as a result of their distance from population centers where health care resources are centralized. Most people wouldn’t think that geographic maldistribution could occur in a city, no less in a city as great as New York. But, everything is relative. In comparison to Manhattan, which has 24 hospitals, Brooklyn has significantly less hospital resources- half the number of hospitals to deal with 1 million more people. Midtown Manhattan has 4 hospitals within 1000 feet of one another, while there are locations in Brooklyn where an individual must travel 3 miles to get to a hospital. For routine care this might not be difficult, but if you consider someone who has a heart attack at rush hour, it could take a significant amount of time to receive access to an ambulance, no less to an Emergency Department.
Figure 1- Many New Yorkers are over 2 miles from the nearest hospital.
Another type of Maldistribution of Health Care Resources that can occur is economic maldistribution, which occurs when hospitals are preferentially built in wealthier areas, where they are more likely to be profitable because of increased rates of payment. By looking at a map of the census tracts, this is very apparent:
With the exception of the Upper East Side of Manhattan, where Harlem is located, Hospitals are almost entirely built either in or adjacent to census tracts that have a median income higher that $28,000. The best, but perhaps least practical due to high cost, resolution to geographic & economic maldistribution would be for more hospitals to be built in locations where they are not currently located, most notably in Central Brooklyn. As a whole, residents of Manhattan have 4 times as many hospitals given their population as Brooklyn residents have.
One positive spin on Geographic Maldistribution is to view it as an area that can show great improvement by simply spending money. Some problems won’t improve much, even if you spend a great deal of money on an issue- For example, inner city schools often spend significantly more per student than suburban schools, yet have significantly worse outcome measures. One situation where we can look to see whether outcomes improve through spending is by looking at the city’s ‘Free STD Clinics,’ where individuals can go for STD testing, treatment, and prevention and compare their location to rates of condom usage. We can hypothesize that having an STD clinic in an individual’s neighborhood will make them more aware of STDs and make condoms more accessable:
Figure 3- Neighborhoods with lower rates of condom use are less likely to have a STD clinic.
When we look at the data, we can see some support for this. Of the 15 Neighborhoods with ‘moderate’ compliance, 7 have STD clinics; compared with 2 clinics in the remaining 15 neighborhoods. Whice this doesn’t provide scientific proof, maps such as this one can help consider to contribute additional resources to investigate this hypothesis or generate other hypotheses.
