Quality management and improvement for geothermal energy projects using the platform-based tool development technology − ZWERG

Holbein, Benedict; Dietze, Stefan; Hurst, Franziska; Isele, Jörg; Spatafora, Luigi; Wiegel, Friedrich; Hagenmeyer, Veit

doi:10.1016/j.geothermics.2017.10.010

Cited by 6 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…are from nutrition majors. Though it is still less ideal than the proportion of RD/RDN in the US CNM (98.6%) 9 , it had achieved breakthroughs within this time period.…”

Section: Discussionmentioning

confidence: 94%

“…Consistent with the trend of the information technology revolution of our era, AI provides an automated method and various rules that are able to deal with the quality assessment of big data for healthcare 4 . Its advantages have been reported in multidiscipline, such as geothermal systems 9 , medical centers 4 , clinical laboratories 10 , as well as medical QM 11 . The JPCNMP provides a freely available, open-source tool in data collection for CND of QMSNJ, which achieves the goal of intelligent management.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

Pan

Jin

2021

Preprint

View full text Add to dashboard Cite

Objective: To critically evaluate the Quality Management System (QMS) for Clinical Nutrition (CN) in Jiangsu. Monitor its performance in quality assessment as well as human resource management from nutrition aspect. Investigate the appliance and development of Artificial Intelligence (AI) in medical quality control.Data Source: The study source of this research was all the staffs of 70 Clinical Nutrition Department (CND) of the tertiary hospitals in Jiangsu Province, China. These departments are all members of the Quality Management System of Clinical Nutrition in Jiangsu (QMSNJ).Methods: An online survey was conducted on all 341 employees within all these CNDs based on the staff information from the surveyed medical institutions. The questionnaire contains 5 aspects, while data analysis and AI evaluation were focused on human resource information. Results: 330 questionnaires were collected with the respondent rate of 96.77%. The QMS for CN has been build up for CNDs in Jiangsu, which achieved its target in human resource improvements, especially among dietitians. The increasing number of participated departments (42.8%) and the significant growth of dietitians (p=0.02, t=-0.42) are all expressions of the advancements of QMSNJ.Conclusion: As the first innovation of an online platform for QM in Jiangsu, JPCNMP has been successfully implemented among QMS from this research. This multidimensional electronic system can help QMSNJ and CND achieve quality assessment from various aspects, so as to realize the continuous improvement of clinical nutrition. The instrument of online platform, as well as AI technology for quality assessment is worth to be recommended and promoted in the future.

show abstract

“…are from nutrition majors. Though it is still less ideal than the proportion of RD/RDN in the US CNM (98.6%) 9 , it had achieved breakthroughs within this time period.…”

Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

Pan

Jin

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Compared to the lack of RD/RDNs throughout the province two years before, there were 92 now accounted for 26.98% in total, while 38.04% are from nutrition majors. Though it is still less ideal than the proportion of RD/RDN in the US CNM (98.6%) [9], it had achieved breakthroughs within this time period.…”

Section: Discussionmentioning

confidence: 94%

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

Chen¹,

Wang²,

Ma³

2021

JCLR

View full text Add to dashboard Cite

Objective: To critically evaluate the Quality Management System (QMS) for Clinical Nutrition (CN) in Jiangsu. Monitor its performance in quality assessment as well as human resource management from nutrition aspect. Investigate the appliance and development of Artificial Intelligence (AI) in medical quality control. Materials and Methods: The study source of this research was all the staffs of 70 Clinical Nutrition Department (CND) 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 these CNDs based on the staff information from the surveyed medical institutions. The questionnaire contains 5 aspects, while data analysis and AI evaluation were focused on human resource information. An paired sample t-Test was conducted to determine differences between their situation in 2018 and 2020 the application of JPCNMP. Results: 330 questionnaires were collected with the respondent rate of 96.77%. The QMS for CN has been build up for CNDs in Jiangsu, which achieved its target in human resource improvements, especially among dietitians. The increasing number of participated departments (42.8%) and the significant growth of dietitians (p=0.02, t=-0.42) are all expressions of the advancements of QMSNJ. Conclusion: As the first innovation of an online platform for QM in Jiangsu, JPCNMP has been successfully implemented among QMS from this research. This multidimensional electronic system can help QMSNJ and CND achieve quality assessment from various aspects, so as to realize the continuous improvement of clinical nutrition. The instrument of online platform, as well as AI technology for quality assessment is worth to be recommended and promoted in the future.

show abstract

“…Compared to the lack of RD/RDNs throughout the province 2 years before, there were 92 (26.98%) now accounted for, and 38.04% were from nutrition majors. Although it is still less ideal than the proportion of RD/RDN in US CN medicine (98.6%) [ 12 ], breakthroughs were achieved within this time period.…”

Section: Discussionmentioning

confidence: 99%

“…Consistent with the trend of the information technology revolution of our era, AI provides an automated method and various rules that are able to deal with the quality assessment of big data for health care [ 4 ]. Its advantages have been reported in multiple disciplines such as geothermal systems [ 12 ], medical centers [ 4 ], clinical laboratories [ 13 ], and medical QM [ 14 ]. The JPCNMP provides a freely available, open-source tool in data collection for CN departments of the QMSNJ, which achieves the goal of intelligent management.…”

Section: Discussionmentioning

confidence: 99%

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

Wang¹,

Pan²,

Ma³

2021

JMIR Form Res

View full text Add to dashboard Cite

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 (t93.4=–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.

show abstract

Quality management and improvement for geothermal energy projects using the platform-based tool development technology − ZWERG

Cited by 6 publications

References 4 publications

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

Assessment of Quality Management System for Clinical Nutrition in Jiangsu

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

Contact Info

Product

Resources

About