And we go to Happyville, instead of to Pain City. –Thomas Pynchon, Gravity’s Rainbow
In this continuing series, we’ve been looking at how ObamaCare, through its inherent system architecture, relentlessly creates first- and second-class citizens; how it treats citizens, who should be treated equally, unequally, for whimsical or otherwise bogus reasons. It’s all in the luck of the draw! If you live in the right place or have the right demographic, you go first class to Happyville. If you don’t, you go in coach to Pain City.
If Social Security were implemented like ObamaCare, citizens in Libby, MT would get a bigger check, because; you couldn’t get a Social Security payment if you were debanked, and didn’t have a checking account; you’d get one kind of Social Security from the government if you were poor, and several other kinds of Social Security from private companies if you were not; you’d get a bonus Social Security check if you worked on Capitol Hill; you’d be encouraged to collect your benefits if you were in the right demographic, but otherwise not; your benefits would depend on your projected income, which would be checked by a private credit reporting agency; and your check would vary wildly from state to state, and even from county to county. Who could possibly support such a crazy system?
We now have addititional confirmation, were additional confirmation needed, of this thesis. I want to draw your attention to the following new study, “Health Care In The Suburbs: An Analysis Of Suburban Poverty And Health Care Access,” by Alina S. Schnake-Mahl and Benjamin D. Sommers, in October’s Heatlh Affairs; The Schnake-Mahl/Sommers study is said to be “the first national analysis comparing health care coverage and access between people living in the suburbs and people in urban and rural areas.” From the abstract:
There are 16.9 million Americans living in poverty in the suburbs—more than in cities or rural communities. Despite recent increases in suburban poverty, the perception of the suburbs as areas of uniform affluence remains, and there has been little research into health care barriers experienced by people living in these areas. The objectives of this study were to compare patterns of insurance coverage and health care access in suburban, urban, and rural areas using national survey data from 2005 to 2015 and to compare outcomes by geography before and after the Affordable Care Act took effect. We found that nearly . Though unadjusted rates of health care access were better in suburban areas, compared to urban and rural communities, this advantage was greatly reduced after income and other demographics are accounted for. Overall, a substantial portion of the US population residing in the suburbs lacked health insurance and experienced difficulties accessing care.
The Harvard School of Public Health summarizes the numbers:
The findings showed that:
- The suburbs were home to 44% of the overall population and 38% of the uninsured population, and the uninsurance rate among suburbanites was 15%.
- The probability of having no usual source of health care in the suburbs was 19%, and for having no routine annual checkup, 34%.
- Among low-income suburbanites, 36% had an unmet health care need due to cost and 42% had not had a recent checkup.
- All poor adults—whether they lived in cities, rural areas, or the suburbs—had 8 times higher odds of being uninsured and 1.7 times higher odds of no recent checkup compared to higher-income adults.
That’s just bad, no matter how you slice it. And (as usual) ObamaCare helped, but not enough. The authors were kind enough to send me a copy of the study, so quoting from page 8:
Exhibit 4 compares outcomes in each type of geographic region before and after implementation of the ACA. In all three types of areas, our coverage and access outcomes significantly improved in the post-ACA period. For suburban areas, there was a 3.8-percentage-point drop in the uninsurance rate in the postACAperiod compared to the pre-ACA trend; for urban areas, the comparable estimate was 4.6 percentage points, and for rural areas, it was 4.2 percentage points. …. Across these models, rates of coverage and access challenges remained high among low income adults in suburban areas, similar to those in urban and rural areas. Despite improvements in access and coverage after the ACA took effect, our results also suggest that sizable barriers remain and that, if anything, gains may have been more limited in suburban areas.
And interestingly, from page 9, on Medicaid: Medicaid expansion also helped, as we know; but not enough. It didn’t help as much as we might have expected, given the high proportion of residents of expansion states that live in suburbs:
Despite this disproportionate presence of suburbanites in expansion states, our findings indicate that the ACA has not differentially improved coverage and access for those in the suburbs.
Finally, the authors speculate on why suburbs face difficulties of their own distinct from urban and rural areas. Quoting from pages 7 and 8:
Our results show a large affordability gap based on income, with . Poverty in the suburbs likely poses unique challenges and consequences for residents, particularly for low-income and uninsured residents who seek care from the health care safety-net…. [T]here is reason to suspect that , which may require different solutions than those needed in urban or rural areas. Previous research shows that even after area poverty rates are controlled for, services and publicly funded infrastructure targeted to the poor are scarce in many suburban areas. For instance, there are important gaps in the availability of health care services such as mental health, substance abuse treatment, and hospitals in suburban areas. And though care systems and provider networks are often and increasingly located in high-income suburban areas with large privately insured populations, many suburban physicians are less willing than their urban counterparts are to treat the uninsured and Medicaid beneficiaries, leaving poor suburban residents with limited options for physician care.
Given the lack of health centers in suburban areas, emergency departments are often the primary source of care for the suburban poor. Even accessing hospital or emergency care can be difficult for this population because of insufficient availability of safety-net hospitals, especially in high-poverty suburbs. Because fewer suburban providers appear to be willing to treat uninsured patients, suburban patients often must travel long distances to urban safety-net providers. On a broader scale, limited public transportation systems and sprawl in the suburbs may present unique barriers to low-income patients, given the long distances they must travel to obtain care.
Current policies that identify areas of medical need and determine safety-net location have not adapted to shifts in the geography of poverty, which makes it difficult to locate services and providers in suburban areas with high levels of need for free or low-cost care. Recent proposals by some states to limit medical transportation services in Medicaid in particular could hamper access to care for suburban populations.
Of the structural issues, the one that leaps out at me is a “tax on time” for travel, variously expressed as “sprawl,” “limited public transportation,” and “travel long distances.” It seems that the burbs, having been designed for the age of cheap gas, aren’t structured so well for those who are “transportationally challenged.” (It takes me an hour by bus each way to get to my nearest health clinic, and my needs have been simple. If I had to travel all over the Bangor area, by bus, for tests and treatment, the tax on my time would quickly become inordinate). I also wonder how much the medical profession’s specialization has led to scattered facilities, each requiring a separate trip. Do any of our suburban readers have thoughts on this? Frankly, I’m reading that long extract just above, and translating it into human terms, and the whole situation looks like it could rapidly transform into a hellscape. Why do we make sick people go through this nonsense, especially when they’re poor?
We’ve heard a lot from Democrat centrists about appealing to the suburbs; but I think it’s safe to say that these suburbanites — the ones who are sent to Pain City by the luck of the draw — aren’t the suburbanites the centrists have in mind. After all, if you don’t have health insurance, you’ll be unlikely to fork over fifty bucks for a rubber chicken dinner with your Congress critter. For the suburbanites in Pain City, Medicare for All would be far more appealing.
In any case, I don’t see the Schnake-Mahl/Sommers study getting much attention outside the professional journals; I think it should, and I hope it does, so please circulate it, especially the Health Affairs link.
The statistical techniques used are above my paygrade (“[W]e used logistic regression models to examine the association between the outcomes (access measures) and the three geographic areas, before and after adjustment for demographic factors (age, sex, race, ethnicity, marital status, education), employment, household income, survey year, and state of residence.”). However, I feel competent to extract information the dataset:
Our study used data from the 2005–15 waves of the Behavioral Risk Factor Surveillance System (BRFSS), an annual national cross-sectional telephone survey of noninstitutionalized adults over age eighteen…. Although our study provides important comparisons of health care access in suburban, urban, and rural areas, several limitations must be acknowledged. First, our sample included only nonelderly adults, while other research in this area has not been age restricted. This limits comparison of our work with other reports. Second, though the study relied on survey data, previous research has found high levels of reliability and validity for the BRFSS health care access questions. Third, our household income measure was imprecise, since it was self-reported and measured in income categories rather than exact amounts; in addition, 12.2 percent of our sample did not provide any response to the income question. In our data, those with missing income were significantly more likely than others to be uninsured and have no usual source of care (p < 0:001); thus, if anything, this omission may have led us to underestimate the suburban health care barriers in our sample. Fourth, we excluded cell-phone respondents from our sample because data on our primary exposure, the geographic indicator, is lacking for this group. Fortunately, even after we excluded cell-phone respondents, the overall trend in the insurance rate in our data was similar to those found in other surveys of national insurance rates. Cell-phone use is more prevalent among low-income households. Therefore, our use of the landline-only sample may also have led to an underestimate of poverty rates and barriers to care. Fifth, our assessment of changes after ACA implementation in 2014 are largely descriptive. We could not determine whether these changes in coverage rates were related directly to the ACA's coverage expansions or were due to unmeasured confounders. However, we did control for several potential confounders, including income, age, state, and the pre-2014 time trend.
The bottom line for me is that from the data, at least, the situtation is no better than the study shows, and could well be worse.