WeChat Mini Program
Old Version Features

Exploring Ward Team Handoffs of Overnight Admissions: Key Lessons from Field Observations.

JOURNAL OF GENERAL INTERNAL MEDICINE(2024)

Weill Cornell Medicine

Cited 2|Views18
Abstract
Background The diagnostic process is a dynamic, team-based activity that is an important aspect of ward rounds in teaching hospitals. However, few studies have examined how academic ward teams operate in areas such as diagnosis in the handoff of overnight admissions during ward rounds. This study draws key lessons from team interactions in the handoff process during ward rounds. Objective To describe how ward teams operate in the handoff of patients admitted overnight during ward rounds, and to characterize the role of the bedside patient evaluation in this context. Design A qualitative ethnographic approach using field observations and documentary analysis. Participants Attending physicians, medical residents, and medical students on general medicine services in a single teaching hospital. Approach Thirty-five hours of observations were undertaken over a 4-month period. We purposively approached a diverse group of attendings who cover a range of clinical teaching experience, and obtained informed consent from all ward team members and observed patients. Thirty patient handoffs were observed across 5 ward teams with 45 team members. We conducted thematic analysis of researcher field notes and electronic health record documents using social cognitive theories to characterize the dynamic interactions occurring in the real clinical environment. Key Results Teams spent less time during ward rounds on verifying history and physical examination findings, performing bedside evaluations, and discussing differential diagnoses than other aspects (e.g., reviewing patient data in conference rooms) in the team handoff process of overnight admissions. Several team-based approaches to diagnosis and bedside patient evaluations were observed, including debriefing for learning and decision-making. Conclusions This study highlights potential strengths and missed opportunities for teaching, learning, and engaging directly with patients in the ward team handoff of patients admitted overnight. These findings may inform curriculum development, faculty training, and patient safety research.
More
Translated text
Key words
Nursing Handover,Hospital Handoffs,Teamwork Training
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined