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Judging film, not skin: can radiologists combat bias in medicine?
Weisberg, Edmund M; Fishman, Elliot K.
  • Weisberg EM; Johns Hopkins University Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline Street, JHOC 3262, Baltimore, MD 21287 USA. Electronic address: eweisbe1@jhmi.edu.
  • Fishman EK; Johns Hopkins University Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline Street, JHOC 3254, USA. Electronic address: https://twitter.com/CTisus.
Clin Imaging ; 81: 60-61, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1439947
ABSTRACT
From the more than 700,000 deaths from COVID-19 in the US and the nearly 5 million worldwide, there emerge even more stories than match the statistics when one considers all of the patients' relations. While the numbers are staggering, when we humanize the stories, we are left with even greater devastation, of course. One of the stories among so many that seemed particularly salient and poignant to us was the death of Dr. Susan Moore. Her plaintive Facebook post, which went viral in December 2020, was made a few weeks before she died at the age of 52 from COVID-19 and claimed that she was a victim of racially biased treatment at a hospital in Indiana. It was Dr. Moore's mentioning of CT scans that led us to reflect on the biases of some health care workers and the role of radiologists. Our initial interface with our patients is actually not with their faces, but with their films. This dynamic does not eliminate any biases we may harbor but shields practitioners and patients from potential glaring racial biases in this first and sometimes only stage of the relationship.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Attitude of Health Personnel / COVID-19 Type of study: Prognostic study / Systematic review/Meta Analysis Limits: Female / Humans Language: English Journal: Clin Imaging Journal subject: Diagnostic Imaging Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Attitude of Health Personnel / COVID-19 Type of study: Prognostic study / Systematic review/Meta Analysis Limits: Female / Humans Language: English Journal: Clin Imaging Journal subject: Diagnostic Imaging Year: 2022 Document Type: Article