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An ANP-fuzzy evaluation model of food quality safety supervision based on China's data.

ABSTRACT: A government acts as the main supervisor of food quality and safety. How to quantify and improve the performance and efficiency of government supervision, respectively, is an urgent problem. This study constructs a food safety supervision performance index and utilizes an analytic network process-fuzzy comprehensive evaluation model to precisely quantify the performance of government supervision. The evaluation results show that, (a) although the overall situation of food quality and safety in China is controllable, the government does not do well in food safety risk supervision, food recall supervision, and accident summary supervision. (b) Internal supervision is the weakest link in food quality and safety supervision. (c) Grassroots supervision is weak especially in prefecture and county levels. (d) There is no positive correlation between the economy level and supervision level in one region. This paper contributes to accurately reflecting the status quo of China's food safety supervision and realizing the transparency of government regulatory information, which ultimately boosts the government's efficiency in food safety supervision and improves the regulatory situation.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7382133 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background Application of a Clinical Information System (CIS) like Electronic Patient Record (EPR), PACS system and CPOE has turned into one of the most important criteria of priorities of health care systems. The aims of the clinical information system include improving the physicians’ efficiency level, integrating the caring process, and expanding the fuzzy quality of the services offered to patients. Achievement of these benefits in reality is not an easy task, and there are lots of plans in this field which are doomed to failure. About 50% of the implementation plans of clinical information systems in health care organizations have failed, and this trend is significantly affecting industrial countries. Proper implementation of hospital information systems lies in identifying and assessing the relationships among the most important risk factors of fuzzy. The present study aimed to provide an applicable model for identifying, ranking and evaluating the risk factors associated with projects of clinical information technology in hospitals of Shiraz University of Medical Sciences. Method This is an applied study which evaluates the risk factors associated with implementation of clinical information technology projects in hospitals of Shiraz Medical Sciences University. The participants consisted of professionals and senior experts of clinical information technology. Fuzzy logic was used in this study. We also applied ANP-DEMATEL combined model with fuzzy procedure to provide the analytic model of the study Results According to the study findings, lack of top-executive supports, and unstable organizational environment were the two most important risk factors, while the main organizational factors and technology were also highly important. In addition, the factors associated with technology had the highest influence on the other studied risk factors. Conclusion Hospital authorities can benefit from this proposed model to reduce the risk of implementing the projects of clinical information technology and improve the success coefficient of the risk of such projects.

Dataset Information

An ANP-fuzzy evaluation model of food quality safety supervision based on China's data.

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