Since I first heard about them, I have been fascinated, and dismayed, by the concept of “million dollar blocks.” For those of you unfamiliar with the term, it doesn’t refer to, say, Beverly Hills, Chicago’s Gold Coast, or Manhattan’s Hudson Yards -- areas where the wealthy congregate. No, it refers to city blocks for which society spends over a million dollars annually to incarcerate residents of that block.
Million Dollar Blocks.
Credit: Center for Spatial Research
I, of course, have to think about the healthcare
parallels.
The concept dates back many years, credited to Eric Cadora,
now at Justice Mapping, and Laura
Kurgan, a professor of architecture at Columbia University, where she is the
Director of the Center for Spatial
Research (CSR). The power of the
concept is to use data visualization to illustrate the problem.
Here, for example, is CSR’s map of Brooklyn for prison
spending:
Prison spending in Brooklyn. Credit: Center for Spatial Research |
CSR describes the findings as follows:
The maps suggest that the criminal justice system has become the predominant government institution in these communities and that public investment in this system has resulted in significant costs to other elements of our civic infrastructure — education, housing, health, and family. Prisons and jails form the distant exostructure of many American cities today.
Think about that: “criminal justice is the predominant
government institution in these communities.”
Something is wrong with that picture – not theirs, but, rather, the
picture of our society that it presents.
Mr. Cadora told NPR in 2012:
No one had ever actually sat down and gotten the home street address of everyone going into prison and jail, as well as all the background information about their age and their employment status, etc. And when you have all that data, it tells you a lot about what's going on on the block.
In all honesty, what we mapped was not a big surprise to people. But when you actually gather the real data ... on maps, [it becomes] immediately understandable to people who didn't see it — like legislators, city council people, researchers.
No, not a big surprise, not to most people. We know we spend lots of money on criminal justice;
we just don’t always realize how we spend it. We’ve long had the dubious distinction of locking
up more people – in total and per capita – than any other country.
But if, as they say, a picture is worth a thousand
words, then perhaps data visualization is worth a million dollars. Even hardened criminal justice advocates have
to blanche at how spending is so often concentrated in certain blocks, and should
wonder if perhaps there are better ways to use that money for them.
CSR has a variety of projects in addition to their
criminal justice work, including some focused on healthcare. Earlier this year, for example, they created
an interactive
vaccine allocation map to help guide decisions about allocating then-scarce
COVID-19 vaccines, and late last year their New
Politics of Care project used an interactive map to highlight existing
areas of health care needs. They proposed
a New Deal for Public Health, with a million new community health workers
deployed around the country based on the identified needs.
New Politics of Care. Credit: Center for Spatial Research |
Somehow the Community Health Corps didn’t make it into
the Biden infrastructure proposal.
Perhaps no one in the Administration has seen the map.
Data visualization is nothing new for healthcare. The CDC has an Interactive Atlas of
Heart Disease and Stroke, the Dartmouth
Atlas has been highlighting healthcare variations for close to thirty
years, and, more recently, the Johns
Hopkins Coronarvirus Resource Center has been tracking what’s been
happening in the pandemic.
CMS has a dashboard
that purports to show “standardized per capita costs” down to a county level,
based on Medicare fee-for-service claims, but that’s only for Medicare spending
for only a portion of the Medicare population.
That’s still a long way off from total spending for the whole population,
at a city block or even zip code level.
Still, if anyone is tracking where healthcare’s “million
dollar blocks” are, I’d like to hear about it.
We know -- or think
we know – that there are underserved communities where too many people end
up in the emergency room. We know
that there are communities in which maternal and infant mortality/morbidity are
much worse. We know that there are food
deserts that lead to poor nutrition and subsequent poor health
outcomes. We know that environmental
factors like lead
poisoning, air
pollution, or, of course, gun violence,
lead to differences in health and in healthcare spending.
But do we know where these are concentrated, or do we
know how much we’re spending on the results of them? No.
I want to know in which communities the hospitals are
the predominant healthcare institution.
I want to know in which communities diabetes is rampant. I want to know what communities are falling
behind on preventive screenings and vaccinations. I want to know which communities have
suspiciously low healthcare spending, and whether that is a function of better
health or lack of healthcare resources.
I want to see the interactive data visualizations for
these types of issues, and I want smart people acting on them.
If the pandemic has highlighted anything, it’s that
our public health system is woefully inadequate. It’s a patchwork of overworked county and
state public health departments, with a too-tenuous connection to the CDC. It doesn’t have the right resources and doesn’t
have the right data, collected and acted upon at the right time.
Healthcare generates scads of data, but not the right
data, timely, aggregated across all payors for all kinds of services, and we
certainly don’t have anyone in a position to really use it to manage.
The “million dollar block” concept highlights the fact
that we’re good at spending money, but we’re not very good about how we end up
spending it. It emphasizes the rationale
of “defund police” movement, and should be applied to healthcare as well (as I’ve
discussed
before).
I guess we need to see the pictures first.
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