Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19

Röösli, Eliane; Rice, Brian; Hernandez‐Boussard, Tina

doi:10.1093/jamia/ocaa210

Cited by 62 publications

(55 citation statements)

References 6 publications

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“…Early models predicting COVID-19 outcomes were mainly developed from non-Hispanic White and Asian patients, reflecting the incidence of disease at the onset of the pandemic. [13][14][15] However, newer data highlight the overrepresentation of Hispanic people among patients who receive a positive test result for SARS-CoV-2. Our work underscores this disproportionate incidence of disease and highlights the trend in test positivity among Hispanic patients.…”

Section: Discussionmentioning

confidence: 99%

Increases in SARS-CoV-2 Test Positivity Rates Among Hispanic People in a Northern California Health System

et al. 2021

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Racial/ethnic minority groups are disproportionately affected by the COVID-19 pandemic. We examined ethnic differences in SARS-CoV-2 testing patterns and positivity rates in a large health care system in Northern California. The study population included patients tested for SARS-CoV-2 from March 4, 2020, through January 12, 2021, at Stanford Health Care. We used adjusted hierarchical logistic regression models to identify factors associated with receiving a positive test result. During the study period, 282 916 SARS-CoV-2 tests were administered to 179 032 unique patients, 32 766 (18.3%) of whom were Hispanic. Hispanic patients were 3 times more likely to receive a positive test result than patients in other racial/ethnic groups (odds ratio = 3.16; 95% CI, 3.00-3.32). The rate of receiving a positive test result for SARS-CoV-2 among Hispanic patients increased from 5.4% in mid-March to 15.7% in mid-July, decreased to 3.9% in mid-October, and increased to 21.2% toward the end of December. Hispanic patients were more likely than non-Hispanic patients to receive a positive test result for SARS-CoV-2, with increasing trends during regional surges. The disproportionate and growing overrepresentation of Hispanic people receiving a positive test result for SARS-CoV-2 demonstrates the need to focus public health prevention efforts on these communities.

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Section: Discussionmentioning

confidence: 99%

Increases in SARS-CoV-2 Test Positivity Rates Among Hispanic People in a Northern California Health System

et al. 2021

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“…During the covid-19 pandemic, demand for rapid response technological interventions might hinder responsible AI design and use. 37 38 In a living systematic review of over 100 covid-19 prediction models for diagnosis and prognosis, Wynants et al have found that owing to the pressure of rushed research, the proposed systems were at high risk of statistical bias, poorly reported, and overoptimistic. Up to this point, the authors have recommended that none of the models be used in medical practice.…”

Section: Equity Under Pressurementioning

confidence: 99%

Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?

Leslie

Mazumder

Peppin³

et al. 2021

BMJ

111

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“…One study found that a major risk-prediction algorithm assigned lower risk scores to Black patients than to White patients with comparable health conditions, attributable to mistakes in the algorithm’s initial design [ 41 ]. There are many more examples of the impact of disparities in research [ 39 , 42 , 43 ], and AI [ 44 , 45 ] and it is crucial to not repeat this oversight when developing a virtual physician.…”

Section: Discussionmentioning

confidence: 99%

Perceptions of virtual primary care physicians: A focus group study of medical and data science graduate students

et al. 2020

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Background Artificial and virtual technologies in healthcare have advanced rapidly, and healthcare systems have been adapting care accordingly. An intriguing new development is the virtual physician, which can diagnose and treat patients independently. Methods and findings This qualitative study of advanced degree students aimed to assess their perceptions of using a virtual primary care physician as a patient. Four focus groups were held: first year medical students, fourth year medical students, first year engineering/data science graduate students, and fourth year engineering/data science graduate students. The focus groups were audiotaped, transcribed verbatim, and content analyses of the transcripts was performed using a data-driven inductive approach. Themes identified concerned advantages, disadvantages, and the future of virtual primary care physicians. Within those main categories, 13 themes emerged and 31 sub-themes. Discussion While participants appreciated that a virtual primary care physician would be convenient, efficient, and cost-effective, they also expressed concern about data privacy and the potential for misdiagnosis. To garner trust from its potential users, future virtual primary physicians should be programmed with a sufficient amount of trustworthy data and have a high level of transparency and accountability for patients.

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Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19

Cited by 62 publications

References 6 publications

Increases in SARS-CoV-2 Test Positivity Rates Among Hispanic People in a Northern California Health System

Increases in SARS-CoV-2 Test Positivity Rates Among Hispanic People in a Northern California Health System

Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?

Perceptions of virtual primary care physicians: A focus group study of medical and data science graduate students

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