Should We Rely on AI to Help Avoid Bias in Patient Selection for Major Surgery
Bibliographic Data
| ID | 15745647 |
|---|---|
| Authors | Charles E Binkley (0000-0001-9290-9876, Hackensack Meridian Health, corresponding author), David S Kemp (Legal Aid New South Wales), Brandi Braud Scully (Boston Children's Hospital) |
| Year | 2022 |
| Volume | 24 |
| Issue | 8 |
| Pages | E773-780 |
| Publication date | 2022-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The AMA Journal of Ethic (JOURNAL) |
| Journal identifiers | ISSN: 2376-6980 • E-ISSN: 2376-6980 |
| Publisher | American Medical Association (PUBLISHER • US) |
| DOI | 10.1001/amajethics.2022.773 |
| PMID | 35976935 |
| OpenAlex | W4297855489 |
| Language | EN |
| References cited | 8 |
Many regard iatrogenic injuries as consequences of diagnosis or intervention actions. But inaction-not offering indicated major surgery-can also result in iatrogenic injury. This article explores some surgeons' overestimations of operative risk based on patients' race and socioeconomic status as unduly influential in their decisions about whether to perform major cancer or cardiac surgery on some patients with appropriate clinical indications. This article also considers artificial intelligence and machine learning-based clinical decision support systems that might offer more accurate, individualized risk assessment that could make patient selection processes more equitable, thereby mitigating racial and ethnic inequity in cancer and cardiac disease
Disease · Environmental health · Intensive care medicine · Intervention (counseling · Pathology · Psychiatry · Selection (genetic algorithm · Socioeconomic status · Cardiac, Anesthesia and Surgical Outcomes · Computer Science · Health and Medical Research Impacts · Healthcare cost, quality, practices · Medicine · Artificial Intelligence
The Effect of Race and Sex on Physicians' Recommendations for Cardiac Catheterization
Physician Implicit Attitudes and Stereotypes About Race and Quality of Medical Care
Racial Differences in the Treatment of Early-Stage Lung Cancer
Dissecting racial bias in an algorithm used to manage the health of populations
Paved With Good Intentions
Research on the Provider Contribution to Race/Ethnicity Disparities in Medical Care
| Highly cited | No |
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