Using “Integrated Reminders of Nursing Written Assignment” to Reduce the Interruptions in Nursing Care

Nursing interruptions can suspend the nursing process and distracting the nurses’ attention. In a nursing information system, there are lots of pop-up windows to notify the nurses to complete the nursing records. These notifications can also interrupt the original work. We proposed an “Integrated Reminders of Nursing Written Assignment” system to reduce the number of interruptions from the nursing information system. The result showed that the number of pop-up windows decreased from 489.48 to 0 per shift. The completeness of the nursing records raised from 97.3% to 100%. The “Integrated Reminders of Nursing Written Assignment” can effectively reduce the frequency of nursing interruptions and improve the quality of nursing records.

Application of Intelligent Nursing Information System in Emergency Nursing Management

This paper is combined with the intelligent nursing information system to build the emergency nursing platform architecture, from the system emergency procedures, system functionality, network environment deployment, and database design aspects of the discussion. Based on hospital information security, the nursing monitoring system of the intelligent nursing information system is constructed to realize network communication, which is clear and intuitive. The intelligent information system is applied to safety control, medical order information, condition information, and information inquiry, which can save working time and complete the rapid transmission and accurate execution of medical order, making the network communication of medical care more quick and convenient and maximizing the overall efficiency. Based on the disordered phenomenon of registration triage, the Relief algorithm is used to classify the aetiology and triage, and the combination of medical advice, information query, and IT technology is optimized, so as to eliminate the phenomenon of round diagnosis, insert number, and improve the medical environment of waiting for diagnosis, taking medicine, examination, and testing. Finally, through the testing of system information security, information traceability, and rapid information query, the problems in nursing management have been basically solved.

Optimization of Clinical Nursing Management System Based on Data Mining

The clinical nursing work based on the establishment and improvement of the clinical nursing system breaks through the traditional nursing work model, which has achieved the advantages of full traceability, practical operation, comprehensive analysis, and individual error correction of nursing work, and greatly improves the nursing quality and work efficiency of nurses. With the advent of the era of big data, how to organically combine data mining technology with nursing information to optimize the nursing information system, apply big data to clinical nursing work through nursing information system, and provide patients with more efficient, high-quality, and safe nursing services is a problem that needs urgent consideration in today’s era. Therefore, this research is based on the framework of the hospital’s existing clinical care system, using data mining technology to improve the Bayesian algorithm and data preprocessing, optimizes the design of functional modules in the clinical nursing management system, and optimizes the patient information management, medical order management, medical order execution management, basic information and expense management, nursing execution process management, system and data management, barcode management, physical sign management, WAP information management, and other subsystems in the clinical nursing information management system. Experiments have proved that the use of a data mining-based clinical care management system can simplify user operations and improve users’ application of software. The application system of nursing methods based on data mining technology more completely integrates nursing information management business, makes nursing information management initially “digital,” and can improve the quality of hospital care to a large extent.

Tracking Hospital Visitors/Chaperones during the COVID-19 Pandemic

Objective The coronavirus disease (COVID-19) is an emerging infectious disease with strong infectious power and fatality rate. To protect national health, government agencies have regulations on hospital chaperoning and visiting. This article presents the development and implementation of a monitoring system for hospital visiting and chaperoning during the COVID-19 pandemic. The study aimed to create a hospital visiting and chaperoning monitor system that uses nation-wide data sources to more accurately screen hospital visitors and chaperones, assist contract tracing, and prevent transmission of severe acute respiratory syndrome coronavirus 2. Methods This project was implemented in 57 ward units of an academic medical center. The system was connected to the National Health Insurance (NHI) system and Hospital Information System (HIS), and built on the data of everyone who accessed either the hospital or ward using an NHI smart card or national identification card. To shorten the time for manual identification, we also developed a new system of “app for appointment visits and chaperones” to make appointments online. Results After the implementation of the system, data from visitors and chaperones in the nursing information system could be accessed. Given that all data were registered in the HIS visiting/chaperoning monitor system, an epidemic investigation could be performed whenever there was a confirmed case. Conclusion Through the establishment of this system, people entering the ward can be accurately controlled, and all the contacts of potential cases can be traced.

Evaluation of Nursing Information System: Nurses' Perspectives

Aim: This study aimed to evaluate nurses' perspectives on the nursing information system (NIS). Method: In this cross-sectional study, 120 nurses participated. The data collection tool was a researcher-made questionnaire developed based on content analysis of related literature. The questionnaire comprises 39 specific questions, and the experts confirmed the validity of the questionnaire, and the instrument's reliability was calculated by Cronbach Alpha (α =0.88). Data were analyzed by SPSS Statistics version 22 using descriptive and analytic statistics. Results: The majority of nurses (50%) believed that NIS reduces medical errors (strongly agree or agree). More than half of the participants (58%) stated that the NIS's tolerance is high (strongly agree or agree). 69% of them were satisfied with the capabilities of the NIS (strongly agree or agree). Conclusion: According to the results, the NIS status is poor and more attention is needed in designing and developing hospital software.