AI Article Synopsis
- The paper highlights that biases related to group identity, especially concerning disability, lead to significant epistemic errors in the medical field that are often overlooked.
- It connects medical errors to social epistemology, emphasizing how biased epistemic schemas can harm marginalized patients, particularly those with disabilities.
- The authors identify four mechanisms—testimonial injustice, epistemic overconfidence, epistemic erasure, and epistemic derailing—that exacerbate these errors and argue for more comprehensive strategies to combat these injustices in healthcare.
Article Abstract
This paper argues that epistemic errors rooted in group- or identity-based biases, especially those pertaining to disability, are undertheorized in the literature on medical error. After sketching dominant taxonomies of medical error, we turn to the field of social epistemology to understand the role that epistemic schemas play in contributing to medical errors that disproportionately affect patients from marginalized social groups. We examine the effects of this unequal distribution through a detailed case study of ableism. There are four primary mechanisms through which the epistemic schema of ableism distorts communication between nondisabled physicians and disabled patients: testimonial injustice, epistemic overconfidence, epistemic erasure, and epistemic derailing. Measures against epistemic injustices in general and against schema-based medical errors in particular are ultimately issues of justice that must be better addressed at all levels of health care practice.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1353/ken.2019.0023 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Nextflow4MS-DIAL: A Reproducible Nextflow-Based Workflow for Liquid Chromatography-Mass Spectrometry Metabolomics Data Processing.
J Am Soc Mass Spectrom
January 2025
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida 32611, United States.
Reproducibility in untargeted metabolomics data processing remains a significant challenge due to software limitations and the complex series of steps required. To address these issues, we developed Nextflow4MS-DIAL, a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing, validated with publicly available data from MetaboLights (MTBLS733). Nextflow4MS-DIAL automates LC-MS data processing to minimize human errors from manual data handling.
View Article and Find Full Text PDFElectrical impedance-based tissue classification for bladder tumor differentiation.
Sci Rep
January 2025
Institute for System Dynamics, University of Stuttgart, Waldburgstr. 19, 70563, Stuttgart, Germany.
Including sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove.
View Article and Find Full Text PDFStudy protocol for a Prospective Observational study of Safety Threats and Adverse events in Trauma (PrO-STAT): a pilot study at a level-1 trauma centre in Canada.
BMJ Open
January 2025
Department of Emergency Medicine, St Michael's Hospital, Toronto, Ontario, Canada.
Introduction: Traumatic injuries are a significant public health concern globally, resulting in substantial mortality, hospitalisation and healthcare burden. Despite the establishment of specialised trauma centres, there remains considerable variability in trauma-care practices and outcomes, particularly in the initial phase of trauma resuscitation in the trauma bay. This stage is prone to preventable errors leading to adverse events (AEs) that can impact patient outcomes.
View Article and Find Full Text PDFPrediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.
Med Phys
January 2025
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to compensate for system latency in RT systems. Notably, for the prediction of future images in image-guided adaptive RT systems, the use of deep learning has been considered.
View Article and Find Full Text PDFImproved ovalbumin accurate quantitative performance in processed foods by full-length isotope-labeled protein.
Food Chem
December 2024
National Key Laboratory of Veterinary Public Health Security, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, and Beijing Laboratory for Food Quality and Safety, Beijing 100193, China; Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China. Electronic address:
Ovalbumin (OVA) is a high-risk allergen with complex tertiary structure in food samples. Here, we developed an accurate UPLC-MS/MS-based assay to improve OVA quantitative performance in processed foods. Full-length isotope-labeled OVA proteins (OVA-I) were synthesized using stable isotope labeling by amino acids in cell culture (SILAC) technique and employed as functional internal standards to ensure similar cleavage sites between internal standards and analytes.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!