Thinking about health disparities
A number of new research articles and news stories recently have
spurred me to think about how we think about the disparities in
health, and what this vague term means. According to Wikipedia, the
U.S. Health and Resources Services Administration (HRSA) defines it
health disparities as "population-specific differences in the presence
of disease, health outcomes, or access to health care." These
populations are usually defined by race, ethnicity, age, sex,
insurance status, rural vs. urban residence, and/or socioeconomic
group.
I think of health disparities as an element of quality, or the lack
thereof. Sure, everyone may be getting the same (poor-quality) health
care. It's more likely that poor quality health care is seen more
often in some populations than others, via reduced access to quality
care (which could take many forms, from underinsurance to language
barriers) or via discrimination (which can also affect health in ways
unrelated to health care per se). Often, when you look at health
outcomes, it's hard to tease apart the relative roles of access,
discrimination, and other factors. Because access to quality care for
everyone is (or should be) a priority, however, much good research is
emerging on differences in care between different populations. But it
isn't easy, as this post by my blogging colleague Cervantes points
out, starting with the difficulties of defining ethnic populations.
Here are a few recent articles, which I chose because they illustrate
different levels at which disparities are manifested:
Mays and colleagues review research on the psychological/physical
effects of discrimination on health outcomes. A press release on this
article explains the general mechanism of effect of discrimination
thus:
When a person experiences discrimination, the body develops a
cognitive response in which it recognizes the discrimination as
something that is bad and should be defended against, Mays said.
She said this response occurs for the most part even if the person
merely perceives that discrimination is a possibility.
Starting with the brain's recognition of discrimination, the body
sets into motion a series of physiological responses to protect
itself from these stressful negative experiences, Mays said. These
physiological responses include biochemical reactions,
hyper-vigilance and elevated blood pressure and heart rate. With
many African Americans, these responses may occur so frequently
that they eventually result in the physiological system not working
correctly.
A second paper, by Trivedi et al. documents lower-quality care
received by older African-Americans compared to whites. Specifically,
they are less likely than whites to have their blood pressure,
cholesterol, and blood sugar under control. Each of these measures is
a reliable indicator of health-care quality. The results were not
explained by blacks being in lower-quality health plans; the
differences were seen within all 115 of the Medicare plans studied.
The paper did not settle the question of why such differences exist,
but it did find that demographic factors like income and education
explained only some of the gap observed and, of course, lifestyle
factors like diet that do not relate to quality likely explain some of
the results.
I would suggest that a next step would be to tease apart the
contributions of lifestyle and health care quality to the health
differences - one way to do that would be to compare process measures,
which measure actual delivery of care as opposed to health outcomes. I
checked the National Healthcare Disparities Report; the 2005 report
gives a similar result to the Trivedi paper - control of hemoglobin
A1C (a measure of blood glucose) is better in whites than blacks.
However, 2004 report presents a related process measure: adults with
diabetes who had a hemoglobin A1C measurement at least once in the
past year. Interestingly, for this measure, blacks and whites appear
to be approximately equivalent. This is not to say that A1C
measurement is not related to good diabetes outcomes, or in other
words unrelated to quality, but it demonstrates the role of other
factors - possibly even care-related factors - in determining health
outcomes. (By the way, I highly recommend the above-cited Disparities
Report, and its companion the National Healthcare Quality Report, as
useful overviews of U.S. data on healthcare quality; I did play an
advisory role in both of these documents.)
In an accompanying press release to the Trivedi study, the first
author noted that many plans don't even collect information on race
and ethnicity of their patients, so they may not even know they have a
problem. Perhaps this can be explained by a naive and unfortunate
assumption that their care is race-blind, but it certainly means that
any existing disparities will go unaddressed.
A third paper on disparities relates somewhat, but less directly, to
quality. A little background: in the past few years, studies have
emerged that address the hypothesis of whether the number of surgeries
of a particular type (i.e., surgical volume) done by individual
surgeons or within a facility is related to health outcomes. The
consensus seems to be that volume at the facility level, but not at
the surgeon level, is related to outcomes. In other words,
facility-level surgical volume is an indicator of quality. The paper
by Liu et al. found that, minorities c minorities (Blacks, Asians,
Hispanics) compared to white patients, the uninsured, and Medicaid
patients were more likely to receive surgical care at lower-volume
surgical centers. That's not a direct measure of either discrimination
or access to care related to race or ethnicity, but could represent
geographic differences (e.g., proximity to quality hospitals), and the
fact that it's related to economic differences (Medicaid and uninsured
populations) suggests that access to care could play a role. An
editorialist on the study pointed out that referral of patients to
higher-volume hospitals does not solve the problem of quality
differences, but is an "end run" around it, by shifting patients away.
No comments:
Post a Comment