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Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study

BACKGROUND: An electronic system that automatically collects medical information can realize timely monitoring of patient health and improve the effectiveness and accuracy of medical treatment. To our knowledge, the application of artificial intelligence (AI) in medical service quality assessment ha...

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Detalles Bibliográficos
Autores principales: Wang, Jin, Pan, Chen, Ma, Xianghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506260/
https://www.ncbi.nlm.nih.gov/pubmed/34569942
http://dx.doi.org/10.2196/27285
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author Wang, Jin
Pan, Chen
Ma, Xianghua
author_facet Wang, Jin
Pan, Chen
Ma, Xianghua
author_sort Wang, Jin
collection PubMed
description BACKGROUND: An electronic system that automatically collects medical information can realize timely monitoring of patient health and improve the effectiveness and accuracy of medical treatment. To our knowledge, the application of artificial intelligence (AI) in medical service quality assessment has been minimally evaluated, especially for clinical nutrition departments in China. From the perspective of medical ethics, patient safety comes before any other factors within health science, and this responsibility belongs to the quality management system (QMS) within medical institutions. OBJECTIVE: This study aims to evaluate the QMS for clinical nutrition in Jiangsu, monitor its performance in quality assessment and human resource management from a nutrition aspect, and investigate the application and development of AI in medical quality control. METHODS: The participants for this study were the staff of 70 clinical nutrition departments of the tertiary hospitals in Jiangsu Province, China. These departments are all members of the Quality Management System of Clinical Nutrition in Jiangsu (QMSNJ). An online survey was conducted on all 341 employees within all clinical nutrition departments based on the staff information from the surveyed medical institutions. The questionnaire contains five sections, and the data analysis and AI evaluation were focused on human resource information. RESULTS: A total of 330 questionnaires were collected, with a response rate of 96.77% (330/341). A QMS for clinical nutrition was built for clinical nutrition departments in Jiangsu and achieved its target of human resource improvements, especially among dietitians. The growing number of participating departments (an increase of 42.8% from 2018 to 2020) and the significant growth of dietitians (t(93.4)=–0.42; P=.02) both show the advancements of the QMSNJ. CONCLUSIONS: As the first innovation of an online platform for quality management in Jiangsu, the Jiangsu Province Clinical Nutrition Management Platform was successfully implemented as a QMS for this study. This multidimensional electronic system can help the QMSNJ and clinical nutrition departments achieve quality assessment from various aspects so as to realize the continuous improvement of clinical nutrition. The use of an online platform and AI technology for quality assessment is worth recommending and promoting in the future.
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spelling pubmed-85062602021-11-02 Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study Wang, Jin Pan, Chen Ma, Xianghua JMIR Form Res Original Paper BACKGROUND: An electronic system that automatically collects medical information can realize timely monitoring of patient health and improve the effectiveness and accuracy of medical treatment. To our knowledge, the application of artificial intelligence (AI) in medical service quality assessment has been minimally evaluated, especially for clinical nutrition departments in China. From the perspective of medical ethics, patient safety comes before any other factors within health science, and this responsibility belongs to the quality management system (QMS) within medical institutions. OBJECTIVE: This study aims to evaluate the QMS for clinical nutrition in Jiangsu, monitor its performance in quality assessment and human resource management from a nutrition aspect, and investigate the application and development of AI in medical quality control. METHODS: The participants for this study were the staff of 70 clinical nutrition departments of the tertiary hospitals in Jiangsu Province, China. These departments are all members of the Quality Management System of Clinical Nutrition in Jiangsu (QMSNJ). An online survey was conducted on all 341 employees within all clinical nutrition departments based on the staff information from the surveyed medical institutions. The questionnaire contains five sections, and the data analysis and AI evaluation were focused on human resource information. RESULTS: A total of 330 questionnaires were collected, with a response rate of 96.77% (330/341). A QMS for clinical nutrition was built for clinical nutrition departments in Jiangsu and achieved its target of human resource improvements, especially among dietitians. The growing number of participating departments (an increase of 42.8% from 2018 to 2020) and the significant growth of dietitians (t(93.4)=–0.42; P=.02) both show the advancements of the QMSNJ. CONCLUSIONS: As the first innovation of an online platform for quality management in Jiangsu, the Jiangsu Province Clinical Nutrition Management Platform was successfully implemented as a QMS for this study. This multidimensional electronic system can help the QMSNJ and clinical nutrition departments achieve quality assessment from various aspects so as to realize the continuous improvement of clinical nutrition. The use of an online platform and AI technology for quality assessment is worth recommending and promoting in the future. JMIR Publications 2021-09-27 /pmc/articles/PMC8506260/ /pubmed/34569942 http://dx.doi.org/10.2196/27285 Text en ©Jin Wang, Chen Pan, Xianghua Ma. Originally published in JMIR Formative Research (https://formative.jmir.org), 27.09.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Wang, Jin
Pan, Chen
Ma, Xianghua
Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title_full Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title_fullStr Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title_full_unstemmed Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title_short Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
title_sort assessment of the quality management system for clinical nutrition in jiangsu: survey study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506260/
https://www.ncbi.nlm.nih.gov/pubmed/34569942
http://dx.doi.org/10.2196/27285
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