Addressing Health Disparities in Cancer Care: From the Bench to the Bedside and Beyond By Darrell M. Gray, II, MD, MPH

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The Ohio State University Comprehensive Cancer Center –
Arthur G. James Cancer Hospital and Richard J. Solove
Research Institute
The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute
Addressing Health Dispari1es in Cancer Care:
From the Bench to the Bedside and Beyond
Darrell M. Gray, II, MD, MPH
darrell.gray@osumc.edu
@DMGrayMD

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3. Berwick D et al. Health Affairs 2008; 27(3):759-769.

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“For the loved ones we’ve all lost, for the families we
can s6ll save, let’s make America the country that cures
cancer once and for all.”
President Obama, State of the Union Address,
January 12, 2016

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6. § McCarthy AM et al. JCO 2016 May 9. [Epub ahead of print].
§ 3,016 women with invasive breast ca, 808 oncologists, and 732
surgeons.
§ Black women less likely to undergo BRCA 1/2 tes1ng than white
women (OR 0.66; 95%CI, 0.53-0.81)
§ Care highly segregated across surgeons and oncologists
§ Black women less likely to receive a physician recommenda1on for
tes1ng (OR 0.66; 95% CI 0.54-0.82)
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We face the challenge of inequi1es in cancer care and
applica1on of new knowledge

7. § Eggly S et al. Health Expect 2015; 18(5):1316-26.
§ Visits with African American pa1ents (n=11) that included a
clinical trial offer were matched to a sample of visits with White
pa1ents (n=11).
§ Visits with African American pa1ents were
§ Shorter with few men1ons of and less discussion of clinical trials
§ Less discussion of purpose and risks of offered trial(s)
§ More discussion of voluntary par1cipa1on
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We face the challenge of inequi1es in cancer care and
applica1on of new knowledge

8. § Implicit bias contributes to disparate outcomes.
§ Hall WJ et al. Am J Public Health 2015; 105(12):e60-76.
§ Systema1c review including 15 studies
§ Implicit bias has an adverse impact on the following:
§ Pa1ent-provider interac1ons
§ Treatment decisions
§ Treatment adherence
§ Pa1ent health outcomes
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We face the challenge of inequi1es in cancer care
and applica1on of new knowledge

9. § Implicit bias contributes to disparate outcomes.
§ Example: Thrombolysis for ACS (Green AR et al. J Gen Intern Med
2007; 22(9): 1231-1238.
§ Study of 287 residents at 4 academic medical centers
§ Implicit bias measures revealed the following:
§ Preference: White > Black pa1ents
§ Percep1on: Blacks less coopera1ve with procedures and less
coopera1ve generally
§ As pro-White bias é so did the likelihood of trea1ng white
pa1ents and not trea1ng Blacks.
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We face the challenge of inequi1es in cancer care
and applica1on of new knowledge

10. § Clinical trials
§ 1% of trial par1cipants are Hispanic.
§ 5% of trial par1cipants are African American.
§ Biobanking programs
§ Only 9.94% of cases in The Cancer Genome Atlas (NCI-supported)
were collected from racial/ethnic minori1es.
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Racial/ethnic minori1es are underrepresented in
clinical trials and biobanking programs
This is less of a func1on of minori1es’ unwillingness to par1cipate in such
programs and more of a reflec1on of the lack of recommenda1on and access.
Hagiwara N et al. J Cancer Educ 2014; 29:580-587.
Wendler D et al. PLoS Med 2006; 3(2):e19.

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Race alone does not fully explain dispari1es in the
cancer care con1nuum: The example of CRC
Jemal A et al. J Clin Oncol doi: 10.1200/JCO.2014.58.7519

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Race alone does not fully explain dispari1es in the
cancer care con1nuum: The example of CRC
Adjusted Colorectal Cancer Survival by Stage and Insurance Status
among White Pa1ents 18-64 years Diagnosed from 1999-2000, NCDB
Figure courtesy of Dr. O1s Brawley, American Cancer Society
Stage I, privately insured
Stage II, privately insured
Stage I, uninsured/Medicaid
Stage II, uninsured/Medicaid

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Race alone does not fully explain dispari1es in the
cancer care con1nuum: The example of CRC
Siegel RL et al. Cancer Epidemiol Biomarkers Prev;24(8): 1151-6.
Geographic “hot spots”
for CRC deaths

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Utilization
of Care
Access
to Care
Delivery
of
Services
Pa1ent Factors:
- Economic
- Social
- Behavioral
- Geographic
- Literacy
Provider Factors:
- Poor communica1on
- Limited cultural
competence
- Clinical uncertainty
- Bias/Stereotypes
Adapted from Unequal Treatment: Confron1ng Racial and Ethnic Dispari1es in Health Care (2003).
Summary

15. “True compassion is more than flinging a coin to a beggar; it
understands that an edifice which produces beggars needs
restructuring.”
- Dr. Mar1n L. King, Jr.
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16. § How can we provide adequate high quality and high value
care to por1ons of the popula1on that too open do not
receive it?
§ What can I do? What should I do? What must I do?
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Fundamental scien1fic and moral ques1ons

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We must address all determinants of health
Adapted from McGinnis JM et al. Health Affairs 2002; 21(2): 78-93

18. “It is much more important to know what sort of a
pa1ent has a disease than what sort of a disease a
pa1ent has.”
- Sir William Osler
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19. § Refining data collec1on and performance measurement and
monitoring.
§ Exploring the role of genomics and pharmacogenomics in
health dispari1es as we build personalized medicine strategies.
§ Leveraging health informa1on technology to engage, study,
and inform pa1ents and deliver quality care equitably.
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Opportuni1es to address health dispari1es from the
bench

20. § Awareness of implicit biases
§ hrps://implicit.harvard.edu/implicit/takeatest.html
§ Cross-cultural communica1on training of doctors, nurses and
staff
§ Engagement of pa1ents in biobanking and discussions about
clinical trials
§ Use of evidence-based interven1ons to overcome barriers to
access and care delivery
§ Example: Pa1ent navigators
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Opportuni1es to address health dispari1es from the
bedside

21. § Tackle cri1cal shortage of African American medical oncologists.1
§ 2.3% of oncologists in the US; 4.0% of heme/onc fellows in the US
§ Enhance programs and policies that address barriers along the
cancer care con1nuum.
§ Examples include:
§ The Delaware Experiment2
§ Project Access in San Diego (unpublished experience)
§ PACE Program at OSU (unpublished experience)
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Opportuni1es to address health dispari1es in the
community and beyond
1. Hamel LM et al. J Clin Oncol 2015; 33(32):3697-700.
2. Grubbs SS et al. J Clin Oncol 2013; 31(16): 1928-30

22. “Each 1me a man stands up for an ideal, or acts to improve
the lot of others, or strikes out against injus1ce, he sends
forth a 1ny ripple of hope, and those ripples build a current
which can sweep down the migh1est walls of oppression
and resistance.”
- Robert F. Kennedy
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A Call to Ac1on

23. Darrell M. Gray, II, MD, MPH
Deputy Director, Center for Cancer Health Equity
OSUCCC-The James Cancer Hospital & Solove Research Ins1tute
Assistant Professor, Division of Gastroenterology
The Ohio State University Wexner Medical Center
darrell.gray@osumc.edu
@DMGrayMD
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Thank you!

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hrp://interac1onins1tute.org/illustra1ng-equality-vs-equity/
Ques1ons?

25. Courtesy of David Norris, Senior Researcher, The Kirwan Ins1tute
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Bonus slides on dealing with implicit bias

26. Dealing with Implicit Bias
Discover your implicit biases
§ IB’s cannot be accessed
through introspec1on
§ Take the IAT (or several IAT’s;
many available)
§ 8 million tests taken since 1998
§ Google “Harvard IAT” or
“Implicit Associa1on Test” or
“Project Implicit”
§ Be good to yourself
§ Remember: We ALL have implicit biases 26

27. Dealing with Implicit Bias
Commit to Egalitarian Goals
Medical students should be
“encouraged to approach every
encounter with pa1ents who are
members of underprivileged or
stereotyped social groups as an
opportunity to reinforce and act out their avowed
commitment to [egalitarian] values” (Byrne &
Tanesini, 2015, p. 1259).
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28. Dealing with Implicit Bias
Engage in “effor9ul, delibera<ve
processing” in the moment
§ Spontaneous judgments provoke
reliance on stereotypes
§ Delibera1ve processing:
§ Self-monitor your behaviors to
offset implicit stereotyping
§ Rethink the standard ways pa1ent
are classified (race/ethnicity, gender, etc.)
§ Instead, focus on a common iden1ty you share with
each pa1ent
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29. Dealing with Implicit Bias
Reduce your cogni<ve load
(to the extent you are able)
§ Reduced cogni1ve load =
more 1me to process, less
biased decision-making
§ How?
§ Restructure you day (e.g.,
do hardest tasks in the
morning)
§ Advocate for changes in healthcare
workflow, sevng (brainstorm with colleagues)
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30. Dealing with Implicit Bias
Intergroup contact
§ Meaningful engagement w/ people whose iden11es differ
from your own
§ Build new “other” group associa1ons
§ Break down exis1ng implicit associa1ons
§ For op1mal effect, should be:
§ Coopera1ve sevng
§ Working toward a
common goal
§ ***Equal status***
(Be aware of power
dynamics)
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