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Current status of VTE risk assessment and prevention using clinical decision support system: a cross-sectional survey from China
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Abstract
Background and Aim:
Venous thromboembolism (VTE) is an important cause of unexpected death in hospitalized patients. In recent years, Clinical Decision Support System (CDSS) has been increasingly adopted by hospitals worldwide. We conducted a survey with the aim of gaining a comprehensive understanding of the current state and future development direction of CDSS for VTE risk assessment and prevention(VTE-CDSS) in China.
Methods:
A network survey was conducted among hospitals in China. The investigation mainly included 39 questions, such as the implementation details of VTE-CDSS, the scale and the admission capacity of the hospitals. SPSS 20.0 software was used for statistical analysis.
Results:
A total of 587 hospitals responded to this survey, of which 194 (33.05%, 194/587) deployed VTE-CDSS, and less than a quarter (23.71%, 46/194) had Artificial intelligence(AI)-enabled VTE-CDSS. Among the 194 hospitals, the proportion of auxiliary decision support functions related to "risk assessment" was the highest (78.87%, 68.04%, 69.07%), followed by the auxiliary decision support functions related to "prophylaxis execution" (88.66%, 49.48%, 26.80%), and the proportion of auxiliary decision support functions related to "outcome event monitoring" was the lowest (46.39%, 22.68%). More than half of the respondents believed that the risk assessment rate and accuracy of the assessment had been significantly improved (56.19%, 109/194). However, only over one-third of respondents believed that the prevention rate and the standardization of prevention had been significantly improved (37.63%, 73/194). "The overall hospital information foundation is not perfect" was the primary hindrance factor in the implementation and application of VTE-CDSS (40.21%, 78/194). "System functions need to be further improved and more functional applications expanded" (78.35%, 152/194) is the most critical problem that VTE-CDSS needs to be further optimized and solved in the future. There were statistically significant differences between the two groups of hospitals that deployed VTE-CDSS with and without AI function (P<0.005) in the functional realization of various application details, the obstacles encountered in the implementation, and the problems to be further optimized and solved in the future. However, at the present stage in China, the efficiency and effectiveness of VTE-CDSS with AI function in risk assessment and implementation of prophylaxis measures are not significantly different from that of VTE-CDSS without AI function. (0.75<P<0.9).
Conclusions:
The information construction of VTE in China has developed rapidly. The implementation of VTE-CDSS achieved certain results, but there are still some obstacles and problems that need to be optimized in the future.
Springer Science and Business Media LLC
Lei Xia
Kaiyuan Zhen
Zhaofei Chen
Rui Liang
Xiaomeng Zhang
Qian Gao
Mingwei Sheng
Bing Liu
Jiefeng Xia
Chaozeng Si
Yanbi Tian
Lurong Jia
Yaping Xu
Wei Wang
Lintao Zhong
Xianbo Zuo
Dingyi Wang
Wanmu Xie
Jun Wan
Yuanhua Yang
Zhihong Liu
Yingqun Ji
Juhong Shi
Qun Yi
Guochao Shi
Yutao Guo
Nuofu Zhang
Zhaozhong Cheng
Ling Zhu
Zhe Cheng
Cunbo Jia
Zhenguo Zhai
Title: Current status of VTE risk assessment and prevention using clinical decision support system: a cross-sectional survey from China
Description:
Abstract
Background and Aim:
Venous thromboembolism (VTE) is an important cause of unexpected death in hospitalized patients.
In recent years, Clinical Decision Support System (CDSS) has been increasingly adopted by hospitals worldwide.
We conducted a survey with the aim of gaining a comprehensive understanding of the current state and future development direction of CDSS for VTE risk assessment and prevention(VTE-CDSS) in China.
Methods:
A network survey was conducted among hospitals in China.
The investigation mainly included 39 questions, such as the implementation details of VTE-CDSS, the scale and the admission capacity of the hospitals.
SPSS 20.
0 software was used for statistical analysis.
Results:
A total of 587 hospitals responded to this survey, of which 194 (33.
05%, 194/587) deployed VTE-CDSS, and less than a quarter (23.
71%, 46/194) had Artificial intelligence(AI)-enabled VTE-CDSS.
Among the 194 hospitals, the proportion of auxiliary decision support functions related to "risk assessment" was the highest (78.
87%, 68.
04%, 69.
07%), followed by the auxiliary decision support functions related to "prophylaxis execution" (88.
66%, 49.
48%, 26.
80%), and the proportion of auxiliary decision support functions related to "outcome event monitoring" was the lowest (46.
39%, 22.
68%).
More than half of the respondents believed that the risk assessment rate and accuracy of the assessment had been significantly improved (56.
19%, 109/194).
However, only over one-third of respondents believed that the prevention rate and the standardization of prevention had been significantly improved (37.
63%, 73/194).
"The overall hospital information foundation is not perfect" was the primary hindrance factor in the implementation and application of VTE-CDSS (40.
21%, 78/194).
"System functions need to be further improved and more functional applications expanded" (78.
35%, 152/194) is the most critical problem that VTE-CDSS needs to be further optimized and solved in the future.
There were statistically significant differences between the two groups of hospitals that deployed VTE-CDSS with and without AI function (P<0.
005) in the functional realization of various application details, the obstacles encountered in the implementation, and the problems to be further optimized and solved in the future.
However, at the present stage in China, the efficiency and effectiveness of VTE-CDSS with AI function in risk assessment and implementation of prophylaxis measures are not significantly different from that of VTE-CDSS without AI function.
(0.
75<P<0.
9).
Conclusions:
The information construction of VTE in China has developed rapidly.
The implementation of VTE-CDSS achieved certain results, but there are still some obstacles and problems that need to be optimized in the future.
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