Racialized health disparities and tech-based remedies

The 511

Back in the 20th century, we called 411 for information. Today, information’s aplenty, so you’re looking for something more. The 511 includes: 

  • ~5 short paragraphs about medtech, biotech, or another science-y thing
  • 1 sentence for reflection (and maybe a laugh), and 
  • 1 track I’ve currently got in heavy rotation.

Treatment time: Black vs. white

In 2004, while on a visiting teaching gig in sociology at Case Western Reserve, I befriended a colleague in medical anthropology. She was studying health disparities across racial lines, and she indicated that when American men have heart attacks or strokes in public, the response time for passersby was significantly faster for white victims than black victims. (Alas, I couldn’t find this particular study, but if you know it, please send along the URL.) In these situations, especially, every second matters. Delays persist, too, as:

  • Blacks experiencing acute coronary syndrome (ACS) symptoms have longer pre-hospital delay times compared to Whites (i.e., time of symptom onset until registration in the emergency dept.), and
  • fewer Black patients received thrombolytic therapy within recommended timelines or other recommended treatments within 90 minutes of arrival to the hospital

Predictably, the results vary . As noted in Devon et al., “failure to consider and order diagnostic testing to confirm ACS on the part of clinicians, and less aggressive medical therapy and interventions contribute to poorer outcomes” for Black men and women. Poorer outcomes persist across racial lines during the pandemic. African Americans aged 35 to 44 experience Covid-19 mortality rates that are nine times higher than their white counterparts. Why, we might wonder, is the objective review of symptoms of patients presenting with ACS not addressed via algorithmic solutions? For decades — and perhaps for pretty good reasons — Americans sustained longstanding faith in the notion of better living through technology. Can AI counter the implicit bias of healthcare workers?

AI bias

Not at this point, according to a new report about models designed for combating COVID-19. “These tools [AI-driven models] are built from biased data reflecting biased healthcare systems and are thus themselves also at high risk of bias – even if explicitly excluding sensitive attributes such as race or gender,” noted the researchers.

The American Medical Association and the NIH seem to be paying attention to the Black Lives Matter movement. A recent search of funding announcement opportunities indicates 53 active projects studying health “disparities” in the US. The AMA supported the annual National Healthcare Quality and Disparities Report, but that’s been discontinued. It’s not clear how the recommendations and research translate into action plans. They do offer a health disparities toolkit for $15.00. The AMA, though, according to various sources (Open Secret, The Hill) has long been a top-10 lobbying group, recently doling out $20M a year or so. I wonder if they might have the power (and the $) to design a pilot program for ensuring kids in underrepresented groups who are interested in health careers get the financial and educational support they need the two or three summers before they attend college. Can we imagine the power of an online course through Harvard X (or equivalent), with graduate students and med students providing plenty of one-on-one support time, in order to ensure these students enter college on near equal footing with their prep-schooled peers?

The possibilities are real, so I’ll maintain a Gandalf-like optimism and figure that, like Gollum himself, algorithms and labor-intensive actions (rather than dynamic buzzwords) have some part to play yet.

5(1)1 — On jazz and rock’n’roll and falling apart together

“… jazz only works if we’re trying to be free and are, in fact, together. Rock-and-roll works because we’re all a bunch of flakes. That’s something you can depend on, and … that’s all there is: jazz and rock-and-roll. The rest is term papers and advertising.”

Dave Hickey, Air Guitar, p. 101
51(1) — In rotation: The Plimsouls’ “A Million Miles Away”

An 80s classic, and I just got wind of this live version, which has just the right level of urgency — and it’s pretty cool — and topical, since we all seem so far apart from one another these days. Here ya go.

If you like this stuff, and you know someone interested in health, leadership, and music, all mixed up with a dash of humor, please spread the word.

I’m also on this thing called Twitter (@randaldoane). While it may be a passing fad, drop me a note, if you like what you see.

If you want to talk about a project with words, drop me a line over here.



DeVon, Holli A et al. “Disparities in patients presenting to the emergency department with potential acute coronary syndrome: it matters if you are Black or White.” Heart & lung : the journal of critical care vol. 43,4 (2014): 270-7. doi:10.1016/j.hrtlng.2014.04.019.

FitzGerald, Chloë, and Samia Hurst. “Implicit bias in healthcare professionals: a systematic review.” BMC medical ethics vol. 18,1 19. 1 Mar. 2017, doi:10.1186/s12910-017-0179-8.

Moser DK, Kimble LP, Alberts MJ, et al. Reducing delay in seeking treatment by patients with acute coronary syndrome and stroke: a scientific statement from the American Heart Association Council on cardiovascular nursing and stroke council. Circulation. 2006;114(2):168-182. doi:10.1161/CIRCULATIONAHA.106.176040.

Eliane Röösli, BS, Brian Rice, MDCM, Tina Hernandez-Boussard, PhD, “Bias at Warp Speed: How AI may Contribute to the Disparities Gap in the Time of COVID-19,: Journal of the American Medical Informatics Association, , ocaa210, https://doi.org/10.1093/jamia/ocaa210.

Published by Randal Doane

Living the good life in NE Ohio. I dig science and the written word. Let's build something amazing together.

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