Reading between the (county) lines
How does where you live impact your ability to access mental healthcare? This question isn’t as easy to answer as you might imagine.
Typically, the most accurate snapshots of mental healthcare access have been at the county level. County-level data, however, can obscure access disparities and complexities, especially in large, diverse counties like Kings County (Brooklyn) or Los Angeles County (Los Angeles). As a result, how access varies by neighborhood is not readily understood.
Inciter and seventh-year doctoral student Daniel Tadmon is working to change that.
As part of his doctoral dissertation, Tadmon has aggregated nearly one hundred disparate data sources to create a high-resolution snapshot of mental healthcare access in the US. Factoring in the distribution of patients and services, the transportation networks connecting them, as well as competition dynamics triggered by demand, Tadmon is now able to measure access at a fine-grained, neighborhood level.
His novel dataset is already enabling new insights.
A snippet from Tadmon’s work mapping therapist access in Brooklyn, New York. Even in provider-dense Brooklyn, there are measurable disparities in mental health care access.
Immediate findings underscore how county-level data offers insufficient fidelity to examine access. “We’ve long known that there are access gaps between urban and rural counties,” says Tadmon, “but with granular data, computational analysis can now show that large disparities often also exist between different neighborhoods within the same city.”
This insight is just a beginning—mental healthcare access is complex and multi-layered, explains Tadmon. This work addresses only a foundational element of access: whether or not someone can reach a provider with availability. With this foundation, additional components of access can be layered in, including affordability, insurance coverage, stigma, and discrimination. The resultant spatial-social framework can be used to examine the barriers individuals face when seeking care.
Tadmon’s hope is that his work can be used to better understand how mental healthcare access (or lack thereof) serves to reproduce social disadvantages. According to Tadmon, this work offers a doorway into understanding how the people who are faced with social circumstances that trigger mental illness are the same people facing the greatest barriers to treatment. Moreover, findings stemming out of his research have potential to inform policy affecting mental healthcare access.
In February, Columbia’s Data Science Institute awarded Tadmon, Peter Bearman, and Mark Olfson with a $75,000 grant as part of its Seed Funds Program. This funding will enable Tadmon to further develop his work and keep the dataset updated.
We’ll keep you posted on published research stemming from this project.
For more information, contact Chris Pandza.