To improve the hospital's ability to proactively detect infectious diseases, a knowledge-based infectious disease monitoring and decision support system was established based on real medical records and knowledge rules. The effectiveness of the system was evaluated using interrupted time series analysis. In the system, a monitoring and alert rule library for infectious diseases was generated by combining infectious disease diagnosis guidelines with literature and a real medical record knowledge map. The system was integrated with the electronic medical record system, and doctors were provided with various types of real-time warning prompts when writing medical records. The effectiveness of the system's alerts was analyzed from the perspectives of false positive rates, rule accuracy, alert effectiveness, and missed case rates using interrupted time series analysis. Over a period of 12 months, the system analyzed 4,497,091 medical records, triggering a total of 12,027 monitoring alerts. Of these, 98.43% were clinically effective, while 1.56% were invalid alerts, mainly owing to the relatively rough rules generated by the guidelines leading to several false alarms. In addition, the effectiveness of the system's alerts, distribution of diagnosis times, and reporting efficiency of doctors were analyzed. 89.26% of infectious disease cases could be confirmed and reported by doctors within 5 min of receiving the alert, and 77.6% of doctors could complete the filling of 33 items of information within 2 min, which is a reduction in time compared to the past. The timely reminders from the system reduced the rate of missed cases by doctors; the analysis using interrupted time series method showed an average reduction of 4.4037% in the missed-case rate. This study proposed a knowledge-based infectious disease decision support system based on real medical records and knowledge rules, and its effectiveness was verified. The system improved the management of infectious diseases, increased the reliability of decision-making, and reduced the rate of underreporting.
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http://dx.doi.org/10.1038/s41598-023-39931-8 | DOI Listing |
Hereditas
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The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, No. 182 Chunhui Road, Longmatan District, Luzhou, Sichuan, 646000, China.
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BMC Nurs
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Department of Clinical Nutrition, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China.
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January 2025
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Flooding greatly endangers public health and is an urgent concern as rapid population growth in flood-prone regions and more extreme weather events will increase the number of people at risk. However, an exhaustive analysis of mortality following floods has not been conducted. Here we used 35.
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Research Institute for Microbial Diseases, Osaka University, Osaka, Japan.
Spermatogenesis is one of the most complex processes of cell differentiation and its failure is a major cause of male infertility. Therefore, a proper model that recapitulates spermatogenesis in vitro has been long sought out for basic and clinical research. Testis organ culture using the gas-liquid interphase method has been shown to support spermatogenesis in mice and rats.
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Center for Genetic Medicine, Children's National Research Institute, Washington, DC, USA.
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