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Research Article | DOI: https://doi.org/10.31579/2768-0487/030
*Corresponding Author: Chen Pan, Human Resource Department, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Citation: J Wang, X Ma, C Pan. (2021) Assessment of Quality Management System for Clinical Nutrition in Jiangsu. Journal of Clinical and Laboratory Research. 3(2); DOI:10.31579/2768-0487/030
Copyright: ©2021 Chen Pan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Received: 02 June 2021 | Accepted: 17 June 2021 | Published: 03 July 2021
Keywords: quality management system; human resource management; artificial intelligence; health services research; information technology; quality improvement methodologies
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.
From the perspective of medical ethics, patient safety is the core before any other factors within health science. As the application of health science, medical services are inseparable from the safety of patients' lives and medical ethics. Scope of its practice is composed of statutory and individual components, includes codes of ethics (eg, health institution, department director, and/or other national organizations) and other resources [1]. As the Quality Management Center of Clinical Nutrition in Jiangsu (QMCNJ), it is the system`s responsibility to standardize and improve the professional performance within the province`s tertiary hospitals. Their quality assessment comes from the reported data of all CND among these hospitals, such as human and material resource, professional practice, foodservice operation, patient`s satisfaction, and nutrition education presentation for hospital and community [1-2]. All of the required information is scheduled based on the Revised 2016 Standards of Construction and Management of Clinical Nutrition Department in Jiangsu, reflects advances in CND practice during the past 6 years and replaces the 2010 Standards [3].
Within this information era, most of the current information is network-based, as well as the data of healthcare [4]. An electronic system that automatically collects medical information can realize timely monitoring of patient health, improve the effectiveness and accuracy of medical treatment. From a medical quality perspective, a reliance intelligent management system can improve data curation, reduce human resource costs, and contribute to facilitating continuous improvement. As one of the inventions in the information era, AI shows its strong adaptability to the network-based health-care system. It can be introduced into clinical behavior detection accurately and automatically, and of great significance for reducing the incidence of treatment errors and ensuring patients safety [4]. However, the amount of digital data has increased dramatically after the appliance of online system [5]. A crucial consequence is that data management has become more complex, which has increased the necessity for methods that are able to deal with the quality assessment of digital information.
To our knowledge, the application of AI into medical service quality assessment has merely been evaluated, especially for CND. There existed a unified platform for all the QM centers of various medical specialties set up by the Jiangsu Provincial Health Commission (JPHC). After its broken-down in October 2017, the QMCNJ became the first center to independently develop and promote the application of its online platforms named “Jiangsu Province Clinical Nutrition Management Platform”. It was officially launched in the QMSNJ in 2019 and successfully promoted to 70 CND within the quality control system. They are required to fill in relevant information regularly in accordance with the regulations of “Strengthening the Management of Provincial Medical Quality Management System” [6] formulated by JPHC, which has revised in September 2020. Since the stable application of this platform for two years, its effect in QM required to be validated. As for the aim of this research, the application value of JPCNMP could be explored while the development of the CND in Jiangsu can also be clarified within this two years.
Materials and Methods
Subjects
An online questionnaire was designed for employees in 70 CND of the tertiary hospitals in Jiangsu Province, which are all members of QMSNJ. There are 341 staffs in total based on the human resource information from the surveyed medical institutions. The questionnaire contains 5 aspects: hospital information, personal profile, education in QM, scientific research achievements, and nutrition education presentation though internet.
Survey recruitment and data collection
Before distribution, the survey and methods were approved by the QMCNJ and JPHC. The data were collected through an online survey (ID: 97003762) through the free-access platform “Wen Juan Xing”. One specific code was requested to fill the questionnaire. An electronic reminder was sent by QMCNJ to the secretary of these 70 CND through SMS, email, JPCNMP and WeChat. The deadline for completing this survey is Nov. 14, 2020.
Ethics
Institutional ethics approval was obtained for this study from Ethics Committee of First Affiliated Hospital with Nanjing Medical University. This survey presents no risks to the participants, neither did it involve any therapeutic intervention. All the personal information within the questionnaire was designed to verify the authenticity of the feedback. After screening valid questionnaires, all personal information would not be included in the statistical analysis. As the result, there is no risk of additional use or disclosure of private information. Key informants were assured that confidentiality would be maintained and that findings would be presented in an anonymous fashion.
Data analysis
Because information about the CND's human resource and service requirements of related hospitals could be automatically captured through the JPCNMP and the Hospital Information System (HIS), the risk of error caused by manual filling should be avoided. All of these information was gathered on Nov. 14, 2020. The original data is online-accessible for the QMCNJ from the link “https://www.wjx.cn/report/97003762.aspx”.
Only completed questionnaires will be included in the data analysis. An overall description was performed to summarize the demographic and professional characteristics of the valid study sample. The current construction of the CND and their human resource has been clarified with this description. Comparing it with the corresponding data when the online management system was not activated, which is documented in the survey “Current Status of the CND among tertiary hospitals in Jiangsu Province” [7] conducted by our research team in 2018, a preliminary evaluation result of the progress of the quality control was obtained. Another criterion is the consistency between “Numbers of Colleges in your Department” in the "Hospital Information" and the number of documented staffs of the CND in their HIS system. It is used to verify the authenticity of the feedback. The questionnaire was considered valid while these two data matched.
Statistical method
SPSS Statistics 22.0 (SPSS, Inc, an IBM Company, Chicago, IL) was used to describe the results. An paired sample t-Test was conducted to determine differences between their situation before and after the application of JPCNMP. Statistical significance was set at p ≤ 0.05 as shown in the “Supplementary Table 1”.
Based on the staff information from the surveyed medical institutions` HIS, there are 341 employees within all these CND. On November 1st, once the survey was delivered to each participant, they were provided 14 days to complete. All of the collected questionnaires were screened according to the rubrics of valid conditions. With a respondent rate of 96.77%, a total of 330 valid questionnaires were counted.
There are 70 departments in this QM system in 2020, which has raised 42.8
The significant growth in the human resource as well as in the number of CND involved in the QM system in Jiangsu provided a promising development of professionals within the nutrition area. This progress certified that the importance of CNM in healthcare services had been concentrated by health institutions, department managers, and other national organizations such as JPHC [8]. The ratio criteria between CND professionals to hospital beds issued by JPHC for hospital accreditation is 1:200 (0.5×10-2), the CND is still in need of implementation for human resource and should make more effort or resource management.
The increasing number of departments that participated in QMSNJ brought their staff into the QM system of CN, which led to an increased total amount of human resources. However, most of this growth was resulted from the hired clinicians and nurses instead of dietitians. This led to a shrink of the professionals who were graduated from nutrition majors and desired to provide nutrition-related medical services. Based on the human resource profile from surveyed hospitals and the documentation in JPCNMP, most of the clinicians employed in CND were educated as physicians, such as gastroenterologists or endocrinologists. As a result, the CND was still in lack of certified dietitians. This vagueness may be induced by the late development of CN in China. The certification of RD/RDNs was officially organized by the CNS in the past five years. 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.
The advancement of CND`s staff resource might be mainly related to the expansion of QMSNJ, which has proved the QMCNJ has achieved initial results in the QM of human resource engaged in CN in Jiangsu in recent years. However, judging from the comparison of the personnel situation of the 48 original CNDs, which had been involved in the 2018 QMSNJ and participated in the last construction survey [7], the number of their dietitians has increased significantly (p=0.02, t=-0.42). From the perspective of balancing the CN resources and health service requirements, the results confirmed that the medical institution and the department`s director had realized the importance of a solid foundation of professional staff to improve the quality of specialist work and ensure patient safety. These 48 CND have continuously increased their emphasis on CNM, while QMCNJ has indicated in promoting the RD/RDN resource within clinical trial by improving CND professionalism. Within the “Education in QM” part of this questionnaire, 327 out of 330 employees took part in the QM training held through the online platform JPCNMP by QMCNJ in 2020. In the exam after the course, the passing rate of trainees was 99.20%.
The expansion of the organization of QMCNJ has been proved through this research and the rising focus on CNM and human resource management by medical institutions and health commission. All of these signs of progresses are inseparable from the introduction of AI instruments. With the implementation of the specialized online platform JPCNMP after 2019, a real-time quality assessment of CND`s daily work could be observed by themselves and by QMCNJ. The platform functions involve quality assessment, information communication, personnel education, and training, etc. It is convenient for QMCNJ to publish the latest QM guidelines, the QM progress of CNDs in Jiangsu, and the frontier QM research trends as well. It is effectively saving the resource consumption caused by traditional forms such as paper information filling and on-site supervision with the application of this AI technology. 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. The part of artificial is still in need of QMCNJ to achieve data curation and evaluation. As a result, QMCNJ highlights the importance of the QM data quality assessment by developing and continuously revising the index evaluation standards since its foundation in 2010. Similar to any data analysis service, the most crucial process of JPCNMP is the data quality assessment, which is related to the evaluation of data metrics, the organizational structure of the data, and the overall information management [4, 12]. Rather than the initial QM system requires artificial analysis of quality control data, it will be more accurate and reliable if an automated framework effectively manages the quality of JPCNMP`s data in the future.
QMS: Quality Management System
CN: Clinical Nutrition
AI: Artificial Intelligence
CND: Clinical Nutrition Department
QMSNJ: Quality Management System of Clinical Nutrition in Jiangsu
QMCNJ: Quality Management Center of Clinical Nutrition in Jiangsu
CNM: Clinical Nutrition Management
JPCNMP : Jiangsu Province Clinical Nutrition Management Platform
HIS: Hospital Information System
JPHC: Jiangsu Provincial Health Commission
RD: Registered Dietitian
RDN: Registered Dietitian Nutritionist
CNS: Chinese Nutrition Society
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