Addressing Unconscious Bias in Medicine - ACEP · Addressing Unconscious Bias in Medicine Uché Blackstock, MD. Associate Professor, Department of Emergency Medicine . Co-Director,

Addressing Unconscious Bias

in Medicine

Uché Blackstock, MDAssociate Professor, Department of Emergency Medicine

Co-Director, Emergency Ultrasound Fellowship - Department of Emergency MedicineDirector, Recruitment, Retention and Inclusion - Office of Diversity Affairs

Director, Ultrasound Content - Office of Medical Education

NYU School of Medicine

May 1, 2019

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Land Acknowledgement

Bias in Medicine - Uché Blackstock, MD

Wichita, Comanche, Caddo, Cherokee, and Kiowa

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Overview

● Objectives● Why should you care?● Historical context for bias in medicine● What is Unconscious Bias?


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Objectives

● 1) To differentiate unconscious bias from conscious bias

● 2) To explore the ways in which unconscious bias impacts communication and decision-making


NYU School of Medicine5Bias in Medicine - Uché Blackstock, MD

Fixed Growth

Mindsets

Take note of and reflect on any discomfort you feel as you

participate in today’s session.

7Bias in Medicine - Uché Blackstock, MD

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Social Determinants of Health


Racism

Sexism

Homophobia

Transphobia

Etc.

The Historical Context







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Black Infant Mortality● 1850s

○ Black 340/1000 vs. White 217/1000● 1915-1990s

○ Overall infant mortality improved by 90%■ Better hygiene, nutrition, living conditions,

and healthcare● 1960 - 12th among developed countries● 2018

○ Black 11.3/1000 vs White 4.9/1000○ Wider disparity than 1850


https://www.cdc.gov/reproductivehealth/maternalinfanthealth/pregnancy-mortality-surveillance-system.htm

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Black Maternal Mortality

● US - 1 of 13 countries with worse maternal mortality now than 25 years ago

● Black women are 3-4x more likely than their white counterparts to die from pregnancy-related complications○ Higher than that of Mexico, where nearly half

the population lives in poverty ● Persists across socio-economic status


https://www.cdc.gov/reproductivehealth/maternalinfanthealth/pregnancy-mortality-surveillance-system.htm



http://www.commonwealthfund.org/publications/press-releases/2017/jul/mirror-mirror-press-release

Health Care System Performance Rankings

Explicit vs. Implicit Bias

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What is Bias?

● A bias is a tendency, inclination, or prejudice toward or against something or someone.

● Some biases are positive and helpful.● Some biases are negative and

detrimental.


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What is Explicit Bias?

Explicit bias is conscious bias.

● Aware, voluntary, intentional

Explicit bias can often be checked and controlled.

What are examples?



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What is Implicit Bias?Implicit bias is unconscious bias.

● Unaware, involuntary, unintentional● Uncontrolled and automatic

associations between two concepts made very quickly

More complex due to its ingrained and subconscious nature.

What are examples?Bias in Medicine - Uché Blackstock, MD


Mama = Good


Fire = Bad


Good or Bad?

Circle of Trust

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Circle of Trust


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Circle of Trust

Level 3: Know well enough to pass time of day with (acquaintances)

Level 2: Comfortable inviting them in to your home (friends)

Level 1: Made it into your inner circle (the trusted ones)


Level 3

Level 2

Level 1

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Circle of Trust

● What are the implications for the workplace?● As a leader, when you have an important task

or job to get done, to whom do you entrust that responsibility?

● As a physician, how does this phenomenon influence the way you care for your patients?


Why should you care?

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What is known?

Unconscious bias influences:

○ Medical student and resident recruitment and selection

○ Faculty recruitment, selection, and hiring○ Faculty mentoring○ Faculty advancement and promotion


Improving Workforce Diversity

Improving Health Equity


Health Outcomes

Patient -CenteredCommunication

PerceptionImplicit Bias

ClinicalDecision -Making

DiagnosticAbility

+

+

https://www.communitycatalyst.org/blog/community-catalyst-looks-inward-and-outward-in-observance-of-minority-health-month


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Unconscious Bias:Pervasive and Necessary

● Everyone has it!● Helpful & Adaptive

○ Natural tendency to make associations○ Brain uses well-established mental

associations to operate without awareness, intention or control (conserves energy)

○ Provides the ability to categorize information


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System 1:Limbic System

System 2:Prefrontal Cortex

ImplicitEffortlessReflexive

ExplicitEffortfulAnalytic


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Unconscious Bias:Pervasive and Necessary

Not error-free

○ Influences our behaviors and perceptions; tends to replicate the social hierarchy

○ Can conflict with conscious attitudes and intentional behavior

○ Pervasively influences hiring, evaluation, and leadership selection


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“We hear with our eyes”

Orchestra members handpicked

Early 1970s – introduction of screens → “blinding”

Increased numbers of women advanced – 50%


Rouse & Goldin 2000 American Economic Review

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The Power of the Resume:“Emily” or “Lakisha”

STUDY:

Fictitious resumes (n=4980) sent in response to actual “help wanted” ads in Boston and Chicago

Resumes

2 high quality, 2 low quality

African-American or White-sounding names randomly assigned


FINDINGS:Callback rate

10% for resumes with white-sounding names6.6% for resumes with African-American sounding names

Higher qualityWhite-sounding names –30% more callbacksAfrican-American sounding names – 9% more call backs

"Are Emily And Greg More Employable Than Lakisha And Jamal? A Field Experiment On Labor Market Discrimination," American Economic Review, 2004, v94(4,Sep), 991-1013.

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Implicit Association Test (IAT)


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Implicit Association Test

● Developed in 1998 by social psychologists● Detects the strength of an individual’s will to

associate two individual concepts (unconscious prejudices)○ The black-white race IAT has received the

most attention● Millions of people worldwide have taken the

tests


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Implicit Association Test

● Most white respondents show an automatic white preference.

● Most Asian American respondents show an automatic white preference.

● 50% of black respondents show an automatic black preference, but the remaining half show an automatic white preference.


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Implicit vs.Explicit Bias

● Clinicians vary widely in their levels of implicit and explicit bias

● Studies how that most white clinicians are high in implicit bias measures and low in explicit bias measures

● Regardless of specialty, most clinicians demonstrate an implicit preference for white people


Academic Emergency Medicine 2017;24:895–904

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Case

● 25 year old man● CC: severe lower back pain● PMH: none● Physical Exam: no midline tenderness, non-focal

neuro exam● Which is one major factor that will determine

whether he receives the standard of care for his back pain?


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Racial bias in painassessment and treatment

● If he is black, then his pain will likely be underestimated and undertreated.○ Less likely to be given pain medications.○ When given, will receive lower quantities.

● Black patients less likely than white to receive analgesics for extremity fractures (57% vs 74%)in the ED despite similar self-reports of pain.○ Even among young children


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1. Anderson KO, Green CR, Payne R (2009) Racial and ethnic disparities in pain: Causes and consequences of unequal care. J Pain 10(12):1187–1204.

2. Bonham VL (2001) Race, ethnicity, and pain treatment: Striving to understand the causes and solutions to the disparities in pain treatment. J Law Med Ethics 29(1): 52–68.

3. Cintron A, Morrison RS (2006) Pain and ethnicity in the United States: A systematic review. J Palliat Med 9(6):1454–1473.

4. Cleeland CS, Gonin R, Baez L, Loehrer P, Pandya KJ (1997) Pain and treatment of pain in minority patients with cancer. The Eastern Cooperative Oncology Group Minority Outpatient Pain Study. Ann Intern Med 127(9):813–816.

5. Freeman HP, Payne R (2000) Racial injustice in health care. N Engl J Med 342(14): 1045–1047.

6. Goyal MK, Kuppermann N, Cleary SD, Teach SJ, Chamberlain JM (2015) Racial disparities in pain management of children with appendicitis in emergency depart- ments. JAMA Pediatr 169(11):996–1002.

7. Green CR, et al. (2003) The unequal burden of pain: Confronting racial and ethnic disparities in pain. Pain Med 4(3):277–294.

8. Shavers VL, Bakos A, Sheppard VB (2010) Race, ethnicity, and pain among the U.S. adult population. J Health Care Poor Underserved 21(1):177–220.

9. Smedley BD, Stith AY, Nelson AR (2013) Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (National Academies Press, Washington, DC).

10. Todd KH, Deaton C, D’Adamo AP, Goe L (2000) Ethnicity and analgesic practice. Ann Emerg Med 35(1):11–16.Bias in Medicine - Uché Blackstock, MD


Proc Natl Acad Sci U S A. 2016 Apr 19;113(16):4296-301

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Racial bias in painassessment and treatment

● 418 medical students and residents● Two mock cases about a black and a white patient

○ Made pain ratings and medication recommendations● 50% reported that at least one of the false beliefs items

were possible, probably or definitely true○ Blacks’ nerve endings are less sensitive than whites’○ Blacks’ skin is thicker than whites’○ Blacks’ age more slowly than whites○ Participants who held the false beliefs more likely

to rate pain lower and made less accurate treatment recommendations



Time pressure

Lack of solid information to make a decision

Cognitive overload

FatigueAcademic Emergency Medicine 2017;24:895–904

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Patient -Provider Communication:The Effect of Race and Ethnicity on Process and Outcomes of Healthcare


● 75% Black patients interact with non -Black physicians

● Racially discordant interactions○ Less positive affect○ Less relationship

building○ Less treatment

planning○ Less health

information exchangeAm J Public Health. 2004 December; 94(12): 2084–2090

Implicit Bias

Power+

=Reinforce systems of oppression “ -isms”: Racism, sexism, homophobia, transphobia

ActionsDecisionsBehaviors


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Take home points

1. Health inequity does not exist in a vacuum2. Implicit bias influences:

● Clinical decision-making and patient-provider communication

● Recruitment, hiring and selection processes



Questions?

https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=0ahUKEwicgJnL0_vOAhUKox4KHfq2BEMQjRwIBw&url=https://diversityworksnz.org.nz/unconscious-bias-enemy-diversity-inclusion/&psig=AFQjCNE_LqOKVZUXtEbGCOcgYvUqTXoUhA&ust=1473282598224390

Thank you!

Uché Blackstock, MDAssociate Professor, Department of Emergency Medicine

Co-Director, Emergency Ultrasound Fellowship - Department of Emergency MedicineDirector, Recruitment, Retention and Inclusion - Office of Diversity Affairs

Director, Ultrasound Content - Office of Medical Education

NYU School of Medicine

Documents

Addressing Unconscious Bias in Medicine - ACEP · Addressing Unconscious Bias in Medicine Uché Blackstock, MD. Associate Professor, Department of Emergency Medicine . Co-Director,