{"title":"全面评估医疗保健相关感染监测系统","authors":"Yang Zhou, Genlin Yang, Ping Shao, Yan Cui","doi":"10.22158/rhs.v8n4p66","DOIUrl":null,"url":null,"abstract":"Background & objectives: The electronic surveillance system has been applied in healthcare associated infection surveillance. We conducted an evaluation of the real-time healthcare associated infection surveillance system (RT-HAISS) to understand the early warning effect. Methods: We evaluated our RT-HAISS on a dataset of 29074 patients at the Wuxi traditional Chinese medicine (TCM) hospital in 2020, encompassing sensitivity, specificity, positive predictive value, negative predictive value, Youden index and false alarm rate.Results: 466 HAIs were confirmed in this hospital in 2020, The RT-HAISS warned the monitors a total of 1715 cases, with 2040 early warning entries and 1736 false alarm entries. The sensitivity and the specificity were 65.24% and 95.74%, respectively. The Youden index was 0.62. In addition, the positive predictive value was 14.90%, and the negative predictive value was 83.86%, with 85.10% of false alarm rate.Conclusion: The RT-HAISS is an important technical mean for healthcare associated infection surveillance, it’s necessary to further explore the improvement of real-time surveillance system.","PeriodicalId":74678,"journal":{"name":"Research in health science","volume":"45 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Evaluation of Healthcare Associated Infection Surveillance System\",\"authors\":\"Yang Zhou, Genlin Yang, Ping Shao, Yan Cui\",\"doi\":\"10.22158/rhs.v8n4p66\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background & objectives: The electronic surveillance system has been applied in healthcare associated infection surveillance. We conducted an evaluation of the real-time healthcare associated infection surveillance system (RT-HAISS) to understand the early warning effect. Methods: We evaluated our RT-HAISS on a dataset of 29074 patients at the Wuxi traditional Chinese medicine (TCM) hospital in 2020, encompassing sensitivity, specificity, positive predictive value, negative predictive value, Youden index and false alarm rate.Results: 466 HAIs were confirmed in this hospital in 2020, The RT-HAISS warned the monitors a total of 1715 cases, with 2040 early warning entries and 1736 false alarm entries. The sensitivity and the specificity were 65.24% and 95.74%, respectively. The Youden index was 0.62. In addition, the positive predictive value was 14.90%, and the negative predictive value was 83.86%, with 85.10% of false alarm rate.Conclusion: The RT-HAISS is an important technical mean for healthcare associated infection surveillance, it’s necessary to further explore the improvement of real-time surveillance system.\",\"PeriodicalId\":74678,\"journal\":{\"name\":\"Research in health science\",\"volume\":\"45 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research in health science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22158/rhs.v8n4p66\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in health science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22158/rhs.v8n4p66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comprehensive Evaluation of Healthcare Associated Infection Surveillance System
Background & objectives: The electronic surveillance system has been applied in healthcare associated infection surveillance. We conducted an evaluation of the real-time healthcare associated infection surveillance system (RT-HAISS) to understand the early warning effect. Methods: We evaluated our RT-HAISS on a dataset of 29074 patients at the Wuxi traditional Chinese medicine (TCM) hospital in 2020, encompassing sensitivity, specificity, positive predictive value, negative predictive value, Youden index and false alarm rate.Results: 466 HAIs were confirmed in this hospital in 2020, The RT-HAISS warned the monitors a total of 1715 cases, with 2040 early warning entries and 1736 false alarm entries. The sensitivity and the specificity were 65.24% and 95.74%, respectively. The Youden index was 0.62. In addition, the positive predictive value was 14.90%, and the negative predictive value was 83.86%, with 85.10% of false alarm rate.Conclusion: The RT-HAISS is an important technical mean for healthcare associated infection surveillance, it’s necessary to further explore the improvement of real-time surveillance system.
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