About 9 months ago research director of The Opportunity Agenda, Brian Smedley, guest-blogged on THCB about a New England Journal of Medicine study. his colleague Mike Connery wrote to me to tell me about this:
Yesterday, as part of our Health Equity program, we rolled out a new tool that I think you’ll find very interesting. The tool is a new website designed to visually illustrate the economic and racial disparities that exist in New York City’s health care system, and drive all New Yorker’s of conscience to take action by emailing their elected officials. It’s a Google Map mash-up that takes data on NYC hospital closures between 1985 and 2007, and overlays it on an interactive city-wide map that can display either the racial or economic demographics of the Five Boroughs during three periods: 1985, 1995, and 2005.
Using this tool, visitors can visually see how hospital closures disproportionately impact poor neighborhoods and communities of color. Text on the sidebar guides the user through each decade and demographic overlay, explaining the changing conditions of the city and the impact that closures have on underserved communities.But the site is more than just a visual resource, it is also a data-rich resource for researchers that contains a variety of reports and fact sheets (as well as data on the patient demographics, payer source, and quality scores for each hospital), a community forum for health care advocates and New Yorkers, and an activism tool that encourages New Yorkers to write to their elected officials in support of creating a health care system that works equally for all.
All data on the site is from the census bureau, the New York State Department of Health and the New York State Planning and Research Cooperative System. The data were analyzed by Darrel Gaskin of the Johns Hopkins School of Public Health. The Opportunity Agenda, in partnership with a coalition of NYC health care advocates, assembled this map in response to the activities of The Berger Commission (aka the hospital closures commission), whose recommendations are now sitting on Gov. Spitzer’s desk. You can find more info on the Berger Commission here.
When we talk about health care policy in America, very rarely do we mention the roles that class and race play in determining our access to and the quality of health care that we receive. Hope you find the tool interesting and useful.
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The main purpose of our Google maps is to spread public awareness about the extent to which race and economic status affect access to health care in New York City. In order to accomplish this, we utilized a series of statistical methods (i.e. multiple regression analysis) in order to look at health care and demographic data in ways that it has never been used before to discuss the state of New York City health care. That data was used to write our human rights report, “Dangerous and Unlawful: Why Our Health Care System is Failing New York Communities and How to Fix It” (http://www.opportunityagenda.org/site/c.mwL5KkN0LvH/b.1405941/k.99A0/Policy_Briefs__Publications.htm). Moreover, please take a look at our fact sheets at (http://www.opportunityagenda.org/site/c.mwL5KkN0LvH/b.1407945/k.8E20/Fact_Sheets.htm). After looking at these, please feel free to offer any questions and/or comments that you may have.
Ronald Towns
Opportunity Agenda
It is my view that from the beginning of the change in the racial make up of a communtiy to the closing of its neighborhood hospital is a decades long process. The timing is heavily influenced by the flight, aging and/or retirement of its medical staff. When urban neighborhoods change some community based physicians leave, following their tradtional ocnstituency/patients. A good number stay, patients return to the old neighborhood to see their doctors. The doctors acquire some new minority patients. Over time these physicans retire or die in place. They are never realy replaced. The hospital loses “private” insured patients. The hospital then lives/dies on the admissions from the ER. This is never adequate to support the hospitals – it closes. It is more the speed and magnitude of physician loss in the “inner” city than any other factor which drives these hospitals out of business.
As a New Yorker who deals with demographic and healthcare data regularly, I have to say I find this underwhelming as a means of showing disparities in healthcare. Yes, it is a convenient way to look at some demographic data, and the hospital overlay is neat, but there is really no information on quality and access. The hospital closures do appear to be disproportionately clustered in poorer, less-white areas, however:
1. We are dealing with a very densely-populated area with a hospital every few square miles and more than adequate public transportation. In other words, in many cases it brings almost no additional hardship for a community when a hospital closes because there will be another one only a little farther away.
2. There is no quality data. We don’t know is the closed hospitals were well-operated or if people are actually safer going to the ones that remain.
3. We have no population change data. It may be that some of the neighborhoods with closed hospitals have also lost population.
4. New York used to have an extraordinarily high rate of hospital usage, which was unsustainable and made no medical sense. In fact, as we know now, it is harmful both economically and medically to have excessive hospital utilization. It still has perhaps the highest average length of stay in the nation, but the drop has meant that there has been a reduction in the number of beds that the state needs. You can look at the Berger Commission Report for more on this.
5. Given the reduction in needed beds, the real question is whether there has been a decrease in community clinics and primary care providers. If the map could show that, it would be much more useful as a means of showing if access to healthcare among the poor and non-white has deteriorated in recent years.
None of this is a defense of healthcare access or quality in New York State, just a criticism of the utility of the tool provided in assessing these things. The tool is a nice start but needs more layers of data to really serve its advertised purposes.
This is an interesting tool, this will help educate many ignorant people that shy away from this topic. This tool will be greatly used to show the difference in class and what each class gets. I would be interested in seeing this tool being used with all major demographics in the nation. East St. Louis is a viable candidate for this tool because of large demographic and low paying jobs, hospitals have to close there. Most places in California is like that also. This tool will be able to help in improving health care if used properly.