Enterprise Risk Management (ERM) Patient Safety/Clinical Care

Identifying Implicit Bias in Health Care

Defining common implicit biases is a vital step in delivering equitable health care. This article is excerpted from “Recognizing and Managing Bias in the Ambulatory Health Setting” (1), which is the first of a three-part ASHRM/AHA White Paper series. It provides definitions of the specific implicit biases that commonly occur in health care (2) and is intended to help risk managers increase their awareness of the types of biases patients and staff may experience during the delivery of health care.  

  • Affinity bias – Preference for people who share qualities with you or with someone you like (e.g., someone who looks like you)
  • Anchoring – Tendency to rely too heavily on the first piece of information offered when you are making decisions (e.g., considering the appearance of the individual as the most critical element when listening to a patient’s chief complaint)
  • Attribution bias – Tendency to attribute other people’s successes to luck or help from others and attribute their failures to lack of skill or personal shortcomings; or attributing clinical data to incorrect assumptions (e.g., attributing shortness of breath to body mass index [BMI] and not to other evidence present in clinical data)
  • Beauty bias – Assumptions about people’s skills or personality based on their physical appearance and tendency to favor people who are more attractive
  • Cisnormativity – The assumption that all individuals are cisgender with a sense of personal identity and gender corresponding with their birth sex, and that anything else is abnormal
  • Colorism – Prejudice on the basis of skin shade or tone
  • Confirmation bias – Selective focus on information that supports your initial opinion(s) (e.g., all patients with multiple body tattoos are drug seekers)
  • Conformity bias – Tendency to allow the views of other people to easily sway you (e.g., responding to disparagement of an ethnic group)
  • Contrast bias – Assessment of two or more similar things by comparing them with one another rather than looking at their individual merits (e.g., minimizing a patient’s complaint of pain when it does not correlate to their physical presentation)
  • Halo bias – Focus on particularly positive features about a person that clouds clinical or professional judgment (e.g., focusing on a person’s prominence in the community and ignoring their potential of being a victim of domestic violence/intimate partner violence)
  • Heteronormativity – The assumption that all individuals are heterosexual (and that anything else is abnormal)

These definitions are meant to help risk managers call a specific bias for what it is in order to acknowledge that everyone has unconscious (implicit) biases, which affect assumptions being made that impact others and ourselves.


1. American Society of Healthcare Risk Management (October 2021). “Recognizing and Managing Bias in the Ambulatory Health Care Setting.” Retrived from: ASHRM Diversity White Paper Series | ASHRM

2. American Academy of Family Physicians. (2019). “Implicit bias training: Facilitator Guide.” Retrieved from:https://www.aafp.org/dam/AAFP/documents/patient_care/health_equity/implicit-bias-training-facilitator-guide.pdf

Anne Huben-Kearney is one of the authors of the AHA/ASHRM White Paper on “Recognizing and Managing Implicit Bias in the Ambulatory Healthcare Setting” with co-authors: Doris Fischer-Sanchez, DNP, APN-BC, CPHRM, Moira Wertheimer, Esq., BSN, CPHRM, FASHRM, and Ben Wilburn, MS. She is a member of the Patient Safety Certificate Faculty and is on the ASHRM Board.

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