Clinical ethics consultation services: public-facing information on NCI-designated cancer center websites.

Clinical ethics consultation services (CECS) can be particularly complex in oncology, and widespread misconceptions exist about their nature. As a result, visibility and accessibility of information regarding CECS is critical. We investigated the availability and content of information regarding CECS on websites of NCI-designated comprehensive cancer centers and cancer centers (CCs). Each website was reviewed for information on CECS and reviewed for benchmarks partially derived from the American Society of Bioethics and Humanities recommendations for CECS. Our analysis revealed that of 70 NCI-designated center websites, 38 had information on CECS, and 17 were found directly on these sites. When CECS information was available, most websites provided a mission statement (71%) and an explanation of what constitutes an ethics consult (74%). Few provided a description of the consult process (45%) or service membership (39%). Our findings reveal a significant gap in CECS visibility on the websites of NCI-designated CCs.

Digital Health to Patient-Facing Artificial Intelligence: Ethical Implications and Threats to Dignity for Patients With Cancer.

Ethical considerations for patient-facing AI for oncology: dignity, autonomy, safety, equity, inclusivity.

Implementation of a Survey Spine MR Imaging Protocol for Cord Compression in the Emergency Department: Experience at a Level 1 Trauma Center.

BACKGROUND AND PURPOSE: Imaging stewardship in the emergency department (ED) is vital in ensuring patients receive optimized care. While suspected cord compression (CC) is a frequent indication for total spine MR imaging in the ED, the incidence of CC is low. Recently, our level 1 trauma center introduced a survey spine MR imaging protocol to evaluate for suspected CC while reducing examination time to avoid imaging overutilization. This study aims to evaluate the time savings, frequency of ordering patterns of the survey, and the symptoms and outcomes of patients undergoing the survey. MATERIALS AND METHODS: This retrospective study examined patients who received a survey spine MR imaging in the ED at our institution between 2018 and 2022. All examinations were performed on a 1.5T GE Healthcare scanner by using our institutional CC survey protocol, which includes sagittal T2WI and STIR sequences through the cervical, thoracic, and lumbar spine. Examinations were read by a blinded, board-certified neuroradiologist. RESULTS: A total of 2002 patients received a survey spine MR imaging protocol during the study period. Of these patients, 845 (42.2%, mean age 57 ± 19 years, 45% women) received survey spine MR imaging examinations for the suspicion of CC, and 120 patients (14.2% positivity rate) had radiographic CC. The survey spine MR imaging averaged 5 minutes and 50 seconds (79% faster than routine MR imaging). On multivariate analysis, trauma, back pain, lower extremity weakness, urinary or bowel incontinence, numbness, ataxia, and hyperreflexia were each independently associated with CC. Of the 120 patients with CC, 71 underwent emergent surgery, 20 underwent nonemergent surgery, and 29 were managed medically. CONCLUSIONS: The survey spine protocol was positive for CC in 14% of patients in our cohort and acquired at a 79% faster rate compared with routine total spine. Understanding the positivity rate of CC, the clinical symptoms that are most associated with CC, and the subsequent care management for patients presenting with suspected cord compression who received the survey spine MR imaging may better inform the broad adoption and subsequent utilization of survey imaging protocols in emergency settings to increase throughput, improve allocation of resources, and provide efficient care for patients with suspected CC.

Empathy and Equity: Key Considerations for Large Language Model Adoption in Health Care.

The growing presence of large language models (LLMs) in health care applications holds significant promise for innovative advancements in patient care. However, concerns about ethical implications and potential biases have been raised by various stakeholders. Here, we evaluate the ethics of LLMs in medicine along 2 key axes: empathy and equity. We outline the importance of these factors in novel models of care and develop frameworks for addressing these alongside LLM deployment.

Compassionate Machines: The Ethics of "Artificial Empathy" in Cancer Care.

This Viewpoint discusses the ethics of artificial intelligence­generated compassion in cancer care and outlines 4 main points of concern.