Developing Physical Exam Skills in Residency: Comparing the Perspectives of Residents and Faculty about Values, Barriers, and Teaching Methods

Background: The physical examination (PE) skills of residents are often not improved since medical school. Unfortunately, how residents learn PE is not well understood. There is a paucity of research on the factors involved and the differences between resident and faculty perspectives. The authors sought to determine resident and faculty perceptions about the value of PE, the major barriers to learning PE, and the most effective teaching methods. Methods: Based on a rigorous process of literature review and semi-structured interviews, the authors developed an online survey which was sent to 406 internal medicine residents and 93 faculty at 3 institutions. Residents and faculty answered questions about both their own opinions and about their perception of the other group’s opinions. Results: About 283 residents (70%) and 61 faculty (66%) completed the survey. Both residents and faculty rated the importance of PE similarly. Residents rated being too busy, followed by a lack of feedback, as the most significant barriers to learning PE. Faculty rated a lack of feedback, followed by a lack of resident accountability, as the most significant barriers. Both groups rated the availability of abnormal findings as the least significant barrier. Both groups agreed that faculty demonstration at the bedside was the most effective teaching method. Conclusion: This survey can serve as a needs assessment for educational interventions to improve the PE skills of residents by focusing on areas of agreement between residents and faculty, specifically faculty demonstration at the bedside combined with feedback about residents’ skills

Communicating Effectively in Pediatric Cancer Care: Translating Evidence into Practice

Effective communication is essential to the practice of pediatric oncology. Clear and empathic delivery of diagnostic and prognostic information positively impacts the ways in which patients and families cope. Honest, compassionate discussions regarding goals of care and hopes for patients approaching end of life can provide healing when other therapies have failed. Effective communication and the positive relationships it fosters also can provide comfort to families grieving the loss of a child. A robust body of evidence demonstrates the benefits of optimal communication for patients, families, and healthcare providers. This review aims to identify key communication skills that healthcare providers can employ throughout the illness journey to provide information, encourage shared decision-making, promote therapeutic alliance, and empathically address end-of-life concerns. By reviewing the relevant evidence and providing practical tips for skill development, we strive to help healthcare providers understand the value of effective communication and master these critical skills

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT

International audienceThis paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H &N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H &N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient (DSCagg) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT

This paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H&N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H&N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient (DSC$_{agg}$) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2