Chrome Extension
WeChat Mini Program
Use on ChatGLM

Development of Diagnostic Quality Metrics for Prosthetic Joint Infection.

Journal for healthcare quality : official publication of the National Association for Healthcare Qua...(2024)

Hosp Special Surg | Weill Cornell Med Coll | Mathematica

Cited 0|Views7
Abstract
ABSTRACT:Although well-accepted clinical practice guidelines exist for the diagnosis of prosthetic joint infection (PJI), little is known about the quality of diagnosis for PJI. The identification of quality gaps in the diagnosis of PJI would facilitate the development of care structures and processes to shorten time to diagnosis and reduce the significant morbidity, mortality, and economic burden associated with this condition. Hence, we sought to develop valid clinical quality measures to improve the timeliness and accuracy of PJI diagnosis. We convened a nine-member multidisciplinary national panel of PJI experts including orthopedic surgeons, infectious disease specialists, an emergency medicine physician, and a patient previously treated for PJI to review, discuss, and rate the validity of proposed measures using a modification of the RAND-UCLA appropriateness method. In total, 57 permutations of six proposed measures were rated. Populations considered to be at high enough risk for PJI that certain care processes should always be performed were identified by the panel. Among the proposed quality measures, the panel rated five as valid. These novel clinical quality measures could provide insight into care gaps in the diagnosis of PJI.
More
Translated text
Key words
prosthetic joint infection,quality,quality measurers,diagnosis
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
Related Papers
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
GPU is busy, summary generation fails
Rerequest