Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study
BackgroundAn 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...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2021-09-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2021/9/e27285 |
| _version_ | 1827859037843095552 |
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| author | Jin Wang Chen Pan Xianghua Ma |
| author_facet | Jin Wang Chen Pan Xianghua Ma |
| author_sort | Jin Wang |
| collection | DOAJ |
| description |
BackgroundAn 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.
ObjectiveThis 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.
MethodsThe 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.
ResultsA 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 (t93.4=–0.42; P=.02) both show the advancements of the QMSNJ.
ConclusionsAs 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. |
| first_indexed | 2024-03-12T13:02:26Z |
| format | Article |
| id | doaj.art-8cc4fc266d894620b268d1f5accfe615 |
| institution | Directory Open Access Journal |
| issn | 2561-326X |
| language | English |
| last_indexed | 2024-03-12T13:02:26Z |
| publishDate | 2021-09-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj.art-8cc4fc266d894620b268d1f5accfe6152023-08-28T19:08:56ZengJMIR PublicationsJMIR Formative Research2561-326X2021-09-0159e2728510.2196/27285Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey StudyJin Wanghttps://orcid.org/0000-0002-1324-5037Chen Panhttps://orcid.org/0000-0002-9841-7300Xianghua Mahttps://orcid.org/0000-0002-5341-0201 BackgroundAn 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. ObjectiveThis 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. MethodsThe 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. ResultsA 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 (t93.4=–0.42; P=.02) both show the advancements of the QMSNJ. ConclusionsAs 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.https://formative.jmir.org/2021/9/e27285 |
| spellingShingle | Jin Wang Chen Pan Xianghua Ma Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study JMIR Formative Research |
| 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 |
| url | https://formative.jmir.org/2021/9/e27285 |
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