International Journal of Clinical Case Reports 2025, Vol.15 http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved.
International Journal of Clinical Case Reports 2025, Vol.15 http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. MedSci Publisher is an international Open Access publisher specializing in clinical case, clinical medicine, new variations in disease processesregistered at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. Publisher MedSci Publisher Editedby Editorial Team of International Journal of Clinical Case Reports Email: edit@ijccr.medscipublisher.com Website: http://medscipublisher.com/index.php/ijccr Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada International Journal of Clinical Case Reports (ISSN 1927-579X) is an open access, peer reviewed journal published online by MedSci Publisher. The journal is considering all the latest and outstanding research articles, letters and reviews in all aspects of clinical case, containing clinical medicine which advance general medical knowledge; the event in the course of observing or treating a patient; new variations in disease processes; as well as the expands the field of clinical relating to case reports. All the articles published in International Journal of Clinical Case Reports are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. MedSci Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
International Journal of Clinical Case Reports (online), 2025, Vol. 15, No.6 ISSN 1927-579X http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content A Review of the Application of Smart Nursing Systems in Inpatient Safety Management JieWang International Journal of Clinical Case Reports, 2025, Vol. 15, No. 6, 248-258 Molecular Monitoring of Brain Injury Markers During Post-CPR Nursing in the Emergency Department MinLi International Journal of Clinical Case Reports, 2025, Vol. 15, No. 6, 259-270 Analysis of the Immunological Mechanisms of Anaphylactic Shock Following Vaccination and Recommendations for Prevention Jianmin Liu International Journal of Clinical Case Reports, 2025, Vol. 15, No. 6, 271-282 Construction of Caregiver Support Mechanisms and Stress Intervention Practices in Home-Based Care for Disabled Older Adults YongCheng International Journal of Clinical Case Reports, 2025, Vol. 15, No. 6, 283-292 Accuracy Analysis of AI Prediction Models in Early Screening for Diabetes JieZhang International Journal of Clinical Case Reports, 2025, Vol. 15, No. 6, 293-302
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 248 Systematic Review Open Access A Review of the Application of Smart Nursing Systems in Inpatient Safety Management JieWang Zhuji People’s Hospital, Zhuji, 311800, Zhejiang, China Corresponding email: 2308763906@qq.com International Journal of Clinical Case Reports 2025, Vol.15, No.6 doi: 10.5376/ijccr.2025.15.0026 Received: 17 Aug., 2025 Accepted: 22 Sep., 2025 Published: 11 Nov., 2025 Copyright © 2025 Wang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang J., 2025, A review of the application of smart nursing systems in inpatient safety management, International Journal of Clinical Case Reports, 15(6): 248-258 (doi: 10.5376/ijccr.2025.15.0026) Abstract This study investigated the actual application of the intelligent nursing system in the safety management of inpatients, sorted out the problems existing in the safety management of inpatients, and also analyzed the role of this system in improving the quality of nursing services, ensuring patient safety, and making work more efficient. This study also analyzed the main components of the intelligent nursing system. When promoting the intelligent nursing system, we still encounter many difficulties. This requires us to address them from the perspectives of unifying relevant standards, strengthening personnel training, and promoting collaboration among departments. This study explores the future development trends of artificial intelligence, mobile nursing, wearable devices, smart wards, etc. Continuous innovation and the implementation of relevant systems are precisely important methods to constantly enhance the safety guarantee capacity for inpatients. The intelligent nursing system, through automatic operation, data integration and immediate feedback, provides a solid support for creating a safer, more efficient and patient-centered inpatient care environment. Keywords Smart nursing systems; RFID technology; Electronic medical records; Inpatient safety management; Patient safety 1 Introduction A long-term challenge that the global healthcare system has to address is ensuring the safety of inpatients. Relevant studies show that 8% to 12% of hospitalized patients will encounter medical-related adverse situations, and in developing countries, this risk is even higher. Nurses are frontline personnel who prevent medical errors and safeguard the interests of patients. However, the traditional paper-based record-keeping and manual operation mode cannot effectively solve the current problems, often resulting in low efficiency, poor communication, and inability to obtain data in a timely manner (Douma et al., 2024; Naamneh and Bodas, 2024). Nowadays, intelligent medical systems are developing rapidly. They apply technologies such as radio frequency Identification (RFID), electronic medical Records (EMR), Internet of Things (IoT), and artificial intelligence, aiming to achieve real-time monitoring, automatic data collection, and make clinical operations more traceable (Abugabah et al., 2023). For instance, RFID technology can accurately identify patients' identities and record their medication usage, reducing adverse events caused by incorrect identity recognition and incorrect medication delivery (Omran and Salman, 2024). The EMR system can make nursing records more accurate and faster, facilitate team communication, and provide support for scientific nursing (Douma et al., 2024; Omran and Salman, 2024). In addition, the intelligent infusion pump and artificial intelligence-assisted judgment function can reduce manual input errors and alert risks in a timely manner (Alqaraleh et al., 2025). When these technologies work together, they can reduce human errors, help warn of risks, and rationally allocate resources, opening up a new path for the safety management of inpatients. This study will investigate the current status of intelligent nursing systems and their practical application in the safety management of inpatients, with a focus on the two technologies of RFID and EMR. The research will combine the latest practical research data and systematic analysis conclusions to clarify the core principles of these technologies in protecting patient safety, analyze their main advantages and disadvantages in clinical work, and identify unsolved problems and research gaps. This study aims to illustrate the impact of intelligent systems
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 249 on nursing workflows and safety concepts, laying the foundation for their better integration into medical safety programs. 2 Concept and Composition of Intelligent Nursing System 2.1 Definition and core principles of the intelligent nursing system The intelligent nursing system, integrating advanced digital technology, aims to enhance the quality, safety and efficiency of nursing work. Its core is not simply to digitize the workflow, but to build an interconnected system architecture that can continuously collect data from various channels (such as monitoring devices, electronic medical records, sensors, etc.), thereby assisting doctors in making clinical judgments and coordinating nursing work (Zhao et al., 2021). The system design is mainly based on four principles: interoperability, automation, personalization and security. Interoperability enables data transmission between different devices and platforms, which is fundamental for doing a good job in full-process management (Wang et al., 2024). Automation can significantly reduce repetitive manual operations, thereby lowering the probability of errors and allowing caregivers to focus more on directly caring for patients (Zhao et al., 2021; Vasquez et al., 2023). Personalization is to formulate exclusive intervention plans for patients through intelligent algorithms and promote the patient-centered active care model (Guo et al., 2025). Meanwhile, perfect data security measures are also crucial for protecting health information and maintaining doctor-patient trust (Lou, 2025). 2.2 Key supporting technologies Radio Frequency Identification (RFID) can confirm the identity and location of patients in real time, reduce identity confirmation errors and make work more efficient (Zhao et al., 2021). electronic medical records (EMR, full name electronic medical records) is the information core, uniformly managing various types of data of patients and facilitating internal communication and cooperation within the team (Hants et al., 2023). The Internet of Things (IoT) can connect various sensors and devices to continuously monitor patients' physical indicators and the surrounding environment, providing a reference for timely nursing intervention (Wang et al., 2024). Artificial intelligence (AI) and machine learning algorithms further empower the system and enhance decision support and predictive analysis capabilities (Van Velzen et al., 2023). For example, clinical decision support systems can recommend intervention measures based on evidence-based evidence and warn of potential risks. The deep integration of the above-mentioned technologies has jointly constructed a collaborative intelligent nursing ecosystem (Zhao et al., 2021; Wang et al., 2024). 2.3 Basic system modules At the implementation level, the system typically covers core modules such as data collection, information integration and decision support. The data acquisition module acquires real-time information from multiple channels such as monitoring equipment, sensors and manual entry (Zhao et al., 2021), and its reliability directly affects the effect of early identification of clinical risks. The information integration module is the "central link" of the system. It collects data from different places through unified standards to ensure that all parts of the system can be interconnected (Wang et al., 2024), and then these data were integrated into complete patient medical records to facilitate cooperation among different professional teams (Zhao et al., 2021; Hants et al., 2023). The decision support module, with the aid of artificial intelligence and medical norms, helps nursing staff assess risks, arrange nursing work, and ensure patient safety through real-time alerts and handling methods. 3 Application of RFID Technology in Hospital Safety Management 3.1 Characteristics of RFID and its advantages in clinical nursing Radio Frequency Identification (RFID) is an automatic identification technology that can read and transmit data through radio waves without direct contact. This system generally includes labels attached to items (such as patients, medicines or medical devices), readers for reading the labels, as well as databases and intermediate
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 250 software for processing information (Profetto et al., 2022). Traditional barcode scanning requires alignment, while RFID does not need to be deliberately aligned. It can also read multiple tags simultaneously and is more durable. Therefore, it is particularly suitable for use in complex environments like clinical nursing where quick handling of affairs is required. The use of RFID in clinical workflow can bring many conveniences: By tracking patients, medical staff and medical supplies in real time, it can greatly improve work efficiency and avoid wasting repetitive time on finding equipment and verifying identities (Mohammad et al., 2022; Profetto et al., 2022). This technology has good scalability and can also be combined with mobile devices to achieve real-time collection of bedside information. Overall, RFID can help create a safer, more efficient and more responsive clinical working environment. 3.2 Main application scenarios One important application of RFID in inpatient safety management is patient identification. Embedding RFID tags in the patient's wristband can provide a reliable way of identity verification, enabling medical staff to quickly obtain important diagnostic and treatment information, thereby effectively reducing the risk of medication or surgical errors caused by identity confusion. In addition, after installing readers in key areas of the hospital, RFID can also be used to monitor the activities of patients in the hospital, helping to optimize nursing services and take nursing measures in a timely manner (Profetto et al., 2022). In terms of drug management, systems with RFID enabled can automatically verify the information on labeled drugs and patient wristbands, verify "the correct patient, drug, dosage and time", reduce medication errors and generate traceable records. In surgical management, RFID supports comprehensive inventory before, during and after surgery by tracking surgical instruments and materials, which helps to reduce serious risks such as left surgical items (Profetto et al., 2022). 3.3 Contribution to patient safety Research has found that RFID technology can significantly reduce errors caused by manual recording and visual verification through an automatic identification and verification process. For instance, in the field of drug management, the system built with RFID technology can replace the error-prone paper-based work processes and reduce errors in the medical process. During surgery, it can also help avoid serious problems such as the loss of surgical instruments (Figure 1) (Profetto et al., 2022). Figure 1 Radiofrequency identification-tagged instruments (Adopted from Profetto et al., 2022) Another important advantage of RFID is that it can enhance traceability capabilities. This system can record in real time the patient's care situation, medication steps and the usage information of medical equipment. When needed, these records can be quickly searched and verified (Profetto et al., 2022). This not only helps improve medical quality and meet the requirements of relevant regulations, but also enables medical staff to take prompt response measures when drugs need to be recalled or adverse medical events occur. In addition, RFID can automatically handle daily work and rationally allocate medical resources, allowing medical staff to have more energy to directly care for patients. This can not only improve work efficiency but also provide patients with a better medical experience (Mohammad et al., 2022). Although there are still some problems in personnel training,
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 251 system integration and data security, existing research can all demonstrate that RFID plays an important role in improving the safety management level of inpatients. 4 Application of Electronic Medical Record in Hospital Safety Management 4.1 Core functions and information advantages of electronic medical records Electronic medical Records (EMR) are digital tools specifically designed for collecting, storing and managing patients' health information. Its main function is to record patients' medical visit experiences, examination results, medication usage and treatment plans, etc., and it can also store this information on a secure and easily accessible digital platform (Prathiwi et al., 2025). With EMR, medical staff can quickly search for and share data, which not only makes the patient care process more coherent, but also solves the problem of information lag that often occurs in paper records (Sutha et al., 2025). The digital characteristics of EMR can also integrate information from multiple aspects to form comprehensive and real-time updated patient profiles, providing reliable basis for doctors to diagnose and formulate treatment plans. In terms of information management, using electronic medical records to manage information can effectively enhance the accuracy and completeness of medical documents. It can automatically input information, provide a unified record template, and update the content in real time, greatly reducing the problems of record errors and information omissions (Sutha et al., 2025). Meanwhile, EMR has secure information storage and access management methods, which can not only ensure that important information can be found in time when needed, but also protect the personal privacy of patients (Prathiwi et al., 2025). The various reports generated by EMR also provide important data support for improving medical quality and conducting scientific research. 4.2 Typical applications of nursing safety Electronic medical records are usually closely integrated with clinical decision support systems (CDSS) to provide nurses with evidence-based nursing guidelines, reminders and early warnings, helping them identify abnormal test results, possible drug interactions, and offer intervention suggestions. CDSS embedded in EMR can also mark incomplete records or point out operations that do not conform to standard procedures, thereby making nursing work more standardized and responsibilities clearer (Alexiuk et al., 2023). Allergy reminder is a typical function of electronic medical records to enhance medication safety. This system can automatically compare the allergy history of patients with the prescriptions issued by doctors. Once a potentially dangerous drug combination is detected, it will immediately issue a warning to avoid using harmful drugs for patients. Furthermore, EMR enables smooth information sharing among teams from different disciplines, thereby enhancing cross-departmental collaboration. Medical staff can access the latest medical records and keep abreast of the diagnosis and treatment progress of patients in a timely manner. This can reduce the risks caused by poor communication and discontinuous care (Sutha et al., 2025). 4.3 Results of safety improvements The use of electronic medical records can reduce errors in medical treatment. EMR can automatically input medical instructions, provide real-time reminders, and has a standardized recording method. These functions can all reduce the risks brought by human error and misjudgment (Prathiwi et al., 2025). Studies have shown that after the use of EMR, medication errors have significantly decreased, and the proportion of doctors practicing medicine in accordance with clinical guidelines and the quality of medical records have also improved. In terms of traceability, EMR can establish detailed time-marked records for nursing work, greatly enhancing the transparency and analytical value of process data (Douma et al., 2024), and it also provides a data basis for the continuous improvement of medical quality (Sutha et al., 2025). In addition, the EMR content is complete and easy to retrieve. It can not only provide support for scientific nursing work, but also enable patients to participate more in diagnosis and treatment through functions such as the patient portal, thereby improving the overall quality of nursing (Adeniyi et al., 2024). Although there are still problems in terms of acceptance by medical staff, complexity of information and system compatibility, a large number of studies have proved that EMR plays a key role in enhancing inpatient safety, strengthening traceability capabilities and improving the quality of care (Sinaga and Sumartini, 2025).
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 252 5 The Integrated Application of the Intelligent Nursing System in Key Safety Areas 5.1 Strengthen medication safety The combined use of Radio Frequency Identification (RFID) technology and electronic medical Record (EMR) technology has significantly enhanced the medication safety of inpatients. After connecting the medicines with RFID tags, the patients' wristbands and the EMR system, medical staff can automatically verify the patients' identities, types of medicines, dosages and administration times, ensuring that "the right patients receive the right medicines at the right time". The built-in prescription automatic check and reminder function in EMR can mark possible drug interactions, allergic risks or dosage issues before dispensing, thus forming a complete management chain, minimizing the occurrence of errors in manual recording, and leaving traceable digital records for each link (Rangaswamy and Kiran, 2025). Using these two systems in combination not only reduces medication errors but also makes nursing operations more standardized. Nurses no longer need to spend time reading handwritten prescriptions or repeatedly check them manually, thus allowing them to focus more energy on directly caring for patients. The system will automatically record the details of medication, facilitating quick verification and analysis of problems. In addition, by integrating RFID with electronic medical records (EMR), the medical team can share drug information in real time, which is particularly crucial for ensuring the rationality and safety of drug combinations (Rangaswamy and Kiran, 2025). This combined medication management model has become a good way to enhance the safety of drug use in hospitals. 5.2 Prevent patients from falling and related bedside events The intelligent care system, by leveraging intelligent monitoring and artificial intelligence (AI) to predict risks, makes the measures to prevent patients from falling and bedside accidents more effective. This AI-driven system can constantly monitor the patient's movements and the surrounding environment. Once any dangerous situation is detected, inform the medical staff immediately. These systems will also combine various data such as patients' activity levels and vital signs to determine the risk level of each patient at any time and guide medical staff to take timely protective measures (Gervasi et al., 2025; Lo et al., 2025). Compared with traditional assessment tools, AI prediction models have a higher accuracy rate in identifying high-risk patients and can allocate preventive resources more reasonably (Lo et al., 2025; Kasali, 2025). The real-time positioning system, when used in conjunction with the electronic medical record (EMR), can continuously track the patient's location and treatment status, making fall prevention measures more comprehensive (Kim et al., 2025). This approach not only enables timely handling of emergencies but also lays the foundation for formulating personalized care plans. Intelligent monitoring can also relieve the pressure of frequent manual ward rounds for medical staff, allowing them to focus on caring for high-risk patients. The actual application results of several hospitals show that this system can significantly reduce the occurrence of patient falls and related injuries, fully demonstrating its role in improving patient safety and work efficiency (Figure 2) (Gervasi et al., 2025; Kasali, 2025). Figure 2 On the left, a fixed camera monitors patients within the room's field of view and detects their movements (Adopted from Gervasi et al., 2025) Image caption: Anonymized data are processed by an AI system to analyze potentially risky situations and falls that may require notifying the nursing personnel. On the right, a remote mobile device receives and displays alerts sent to the nursing personnel (Adopted from Gervasi et al., 2025)
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 253 5.3 Infection control and workflow management The intelligent nursing system monitors the locations and movement routes of medical staff, patients and key medical equipment through real-time positioning technologies such as RFID. This helps to quickly identify possible infection transmission routes, thereby doing a good job in isolation management, rationally allocating human resources, and reducing the risk of cross-infection (Rodriguez et al., 2022; Lee et al., 2024). Meanwhile, non-contact monitoring devices can continuously collect patients' vital signs, reducing the possibility of pathogen transmission due to direct contact with the source of infection (Santos et al., 2021). These technologies will automatically handle daily tasks, such as patient registration and equipment tracking, making administrative procedures more convenient and reducing management pressure. This comprehensive platform can send reports and prompts in real time, helping medical staff make timely decisions and implement infection prevention and control regulations. With the support of the Internet of Things and cloud storage, authorized individuals can quickly access important information across locations. So when public health events occur, everyone can cooperate and respond more efficiently (Lee et al., 2024). Overall, integrating the intelligent nursing system can create a safer, more efficient and convenient medical environment and handle various patient safety issues more properly (Rodriguez et al., 2022). 6 Challenges and Countermeasures for Implementing the Smart Nursing System 6.1 Technical and equipment challenges Intelligent nursing systems (such as RFID, artificial intelligence platforms, electronic medical records, etc.) are often constrained by technical and equipment conditions in practical application. Integrating these new technologies with the existing information systems of hospitals is a complex and labor-intensive task. The lack of unified norms among different standards and platforms will cause problems such as troublesome data transmission and scattered information (Qutishat and Shakman, 2025; Katebi et al., 2025). Meanwhile, intelligent devices require regular maintenance and technical support. If there are situations such as unstable network or sensor failure, it may affect the usage effect of the system (Lin et al., 2024). Medical technology is evolving rapidly, and hospitals have to constantly spend money on upgrading basic equipment and medical instruments, which imposes a long-term burden on budgets and IT support capabilities (Qutishat and Shakman, 2025). When resources are insufficient, problems such as power consumption, battery life and sturdiness of the equipment become more obvious (Lin et al., 2024). Without comprehensive technical planning, these problems may affect the intelligent care system from playing its due role. 6.2 Management and personnel challenges Management and personnel factors also have a significant impact on the implementation effect of the system. Due to inadequate training, medical staff often cannot operate these systems proficiently. Coupled with busy work, frequent staff turnover and a wide variety of equipment, the training effect is even more affected (Qutishat and Shakman, 2025; Ramadan et al., 2024). Meanwhile, employees often resist change, such as suspecting new technologies, not using or relying on old working methods, which reduces the actual value of technological investment (Qutishat and Shakman, 2025; Katebi et al., 2025). Adjusting the workflow is no easy task either. After the introduction of the intelligent system, the original working methods and communication habits of nurses all need to be adjusted. If there is no detailed adjustment plan, it may increase the psychological pressure of medical staff and may also cause new work mistakes (Katebi et al., 2025). The lack of clear institutional rules within the hospital, coupled with insufficient leadership support, will make compliance issues more difficult to handle (Khalil et al., 2025). Therefore, systematically addressing these personnel and management issues is a necessary condition for the smooth operation of the intelligent nursing system. 6.3 Countermeasures and suggestions For the problems mentioned earlier, relevant studies have also provided corresponding solutions. We need to unify the data format, communication standards and device interfaces to improve device compatibility and avoid the
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 254 trouble of system integration (Qutishat and Shakman, 2025). By building an upgradable modular system framework, smooth system updates can be achieved, and different technologies can also be mutually adapted (Upadhyay et al., 2023). Regular maintenance of the equipment, strengthening of technical support, and active attention to the operation of the system can all make the system more stable to use (Lin et al., 2024; Xu and Li, 2025). In terms of personnel training, it is necessary to strengthen talent reserves, enhance the professional capabilities of medical staff, and offer continuing education courses that combine technical operations with clinical applications. Methods such as simulation practice, colleague mentoring, and the establishment of "nurse leaders" can make everyone more willing to accept the system and more enthusiastic when using it (Khalil et al., 2025). In addition, IT technology is also crucial for promoting the cooperation among the IT department, the nursing department and the management department, so that the application of technology can better meet the actual clinical needs (Katebi et al., 2025). The explicit support from hospital leadership, a clear institutional system, as well as a hospital atmosphere that encourages feedback and continuous improvement, can all further help this system better integrate into clinical work and play a long-term role (Qutishat and Shakman, 2025; Ominyi et al., 2025). 7 The Future Development Trend of Intelligent Nursing System 7.1 In-depth application of smart nursing driven by artificial Intelligence Predictive models developed by artificial intelligence (AI) are advancing rapidly. They can determine whether a patient's condition will worsen, scientifically allocate medical resources, and also assist doctors in making decisions regarding diagnosis and treatment. These models will collect various types of data from electronic medical records and monitoring devices to identify subtle abnormal situations that need to be dealt with as soon as possible. In addition, AI-supported early warning and risk classification tools can make nursing interventions more precise and timely, and help reduce complications (Hassanein et al., 2025; Zhou et al., 2025). AI automatic medical record recording is another key development direction. This type of AI system employs multiple language processing technologies and can record and organize patients' relevant conditions in real time through audio, video and other data, significantly reducing the pressure on nurses to write materials. This automated approach not only makes medical record recording more accurate and standardized, but also helps nurses provide more targeted care for patients and facilitates the sharing of patient information by the medical team (Yadav, 2024; Ju et al., 2025). However, to popularize these technologies, it is necessary to improve relevant ethical norms, continuously promote clinical testing work, and conduct systematic AI knowledge training for nursing staff (Hassanein et al., 2025). 7.2 Integration and promotion of mobile care and wearable devices Wearable devices such as smartwatches and biosensing patches are now being used more and more frequently. They can continuously monitor the vital signs and daily activities of patients (Nasr et al., 2021; Conte et al., 2024). If these devices are used in combination with AI algorithms, early signs of deterioration in patients' conditions can be detected in time, and personalized care can also be provided (Hassanein et al., 2025). Most nurses think this type of equipment is good, but they also have concerns, such as whether the data is accurate, whether it is expensive to use, and whether the equipment is reliable (Alzghaibi, 2025). The mobile medical platform enables smoother communication among the nursing team and makes bedside ward rounds and nursing handows proceed more smoothly (Fotsing et al., 2021). In scenarios such as home care, wearable Internet of Things systems support remote monitoring and early intervention, enabling care services to reach more places (Wang et al., 2024). With the increasing popularity of technology, as long as the problems of data privacy and device compatibility can be solved systematically, their application in inpatient safety management will definitely be more in-depth (Nasr et al., 2021; Alzghaibi, 2025). 7.3 Develop towards fully integrated intelligent wards and human-machine collaboration The fully integrated intelligent ward combines Internet of Things, cloud computing and robot technology to achieve unified management of patient data, automatic adjustment of the environment and intelligent allocation of
International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 248-258 http://medscipublisher.com/index.php/ijccr 255 resources (Wang et al., 2024; Choi et al., 2025). Practice has proved that this system can shorten the response time of nurses, improve nursing efficiency and patient satisfaction (Wang et al., 2024). The combination of AI and robots can also automate daily tasks such as dispensing medicine, allowing nurses to devote more energy to complex diagnosis and treatment judgments and humanistic care for patients (Zhou et al., 2025). Human-machine collaboration is an important development direction. In this mode, the role of artificial intelligence and robots is to assist nurses in their work rather than replace their professional judgment and humanistic care (Zhou et al., 2025). The system design must revolve around user needs, ensure a close integration of technology and clinical processes, and embody the patient-centered nursing concept. Long-term interdisciplinary cooperation, policy support and effect evaluation are crucial for giving full play to its role in improving patient safety and the quality of care (Hassanein et al., 2025). 8 Concluding Remarks Intelligent nursing systems such as RFID, electronic medical records, and Internet of Things platforms have played a significant role in strengthening the safety management of inpatients. They can simplify the workflow, significantly reduce medication errors, keep track of patients' conditions at any time, quickly solve problems, and thereby effectively lower the risk of adverse events. Automation and digitalization not only make medical records more standardized, but also enhance team communication efficiency, while providing reliable assistance for scientific decision-making and clarifying security responsibilities. The use of intelligent nursing systems is particularly important for the overall improvement of medical service levels. These systems can alleviate the paperwork pressure on medical staff, support timely intervention, improve treatment outcomes and patient experience, and enable nurses to have more time to directly care for patients. Combining the concept of system management with nursing management can help form a more forward-looking management approach in patient safety and resource allocation, and assist medical institutions in consistently providing high-quality services to patients in complex environments. The intelligent nursing system is not without its drawbacks. For instance, different systems cannot cooperate with each other, the training of medical staff has not kept up, and the workflow also needs to be re-planned. In the future, we should pay attention to its long-term effects in various clinical scenarios, promote standardized use, and also conduct a comprehensive analysis of its economic cost and technical feasibility. To enable it to play a broader and more lasting role, it requires the joint efforts of medical service personnel, technical researchers and policymakers to ensure that the relevant projects can be easily implemented and gradually promoted, and also to meet the needs of frontline medical staff. Only through continuous investment and innovation can it fully play its role, thereby enhancing the safety guarantee level for inpatients and the quality of medical services. Acknowledgments The author extends sincere thanks to Mr. Wang for his feedback on the manuscript. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Abugabah A., Smadi A., and Houghton L., 2023, RFID in health care: a review of the real-world application in hospitals, Procedia Computer Science, 220; 8-15. https://doi.org/10.1016/j.procs.2023.03.004 Adeniyi A., Arowoogun J., Chidi R., Okolo C., and Babawarun O., 2024, The impact of electronic health records on patient care and outcomes: a comprehensive review, World Journal of Advanced Research and Reviews, 21(2): 1446-1455. https://doi.org/10.30574/wjarr.2024.21.2.0592 Alqaraleh M., Almagharbeh W., and Ahmad M., 2025, Exploring the impact of artificial intelligence integration on medication error reduction: a nursing perspective, Nurse Education In Practice, 86: 104438. https://doi.org/10.1016/j.nepr.2025.104438
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International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 259-270 http://medscipublisher.com/index.php/ijccr 259 Review Article Open Access Molecular Monitoring of Brain Injury Markers During Post-CPR Nursing in the Emergency Department MinLi The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China Corresponding email: limin@qq.com International Journal of Clinical Case Reports 2025, Vol.15, No.6 doi: 10.5376/ijccr.2025.15.0027 Received: 02 Sep., 2025 Accepted: 05 Oct., 2025 Published: 21 Nov., 2025 Copyright © 2025 Li, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li M., 2025, Molecular monitoring of brain injury markers during post-CPR nursing in the emergency department, International Journal of Clinical Case Reports, 15(6): 259-270 (doi: 10.5376/ijccr.2025.15.0027) Abstract This study explored the research progress and nursing implications of molecular monitoring of biomarkers for brain injury in the emergency department (ED) after cardiopulmonary resuscitation (CPR), analyzed the roles of traditional and emerging biomarkers in the early identification of brain injury and the assessment of neurological prognosis, and summarized the advantages of multi-biomarker combination and multimodal prediction models in improving prognosis accuracy. It also elaborates on the application of specimen selection and monitoring time Windows, result interpretation, risk stratification, comprehensive brain protection and individualized nursing pathways, emphasizing the importance of multidisciplinary collaboration and quality management in standardized monitoring. After comparing the differences in research and practice at home and abroad, it is pointed out that there are still problems such as insufficient sample size, inconsistent detection and threshold standards, and insufficient transformation of some new markers at present. In the future, it is necessary to better integrate molecular monitoring into the standardized and individualized nursing system after CPR in the emergency department through large-sample multi-center research, standardization of detection processes and construction of localization paths. To improve the neurological prognosis of survivors of cardiac arrest. Keywords Cardiopulmonary resuscitation; Emergency; Department; Brain injury Biomarker; Molecular monitoring I Introduction Cardiac arrest is an emergency with acute onset and a high fatality rate. Although cardiopulmonary resuscitation (CPR) techniques are constantly advancing, brain damage after resuscitation remains the main cause of death or long-term disability for patients. Epidemiological studies have shown that among patients receiving advanced resuscitation treatments such as extracorporeal cardiopulmonary resuscitation, approximately a quarter will develop acute brain injury, among which hypoxic-ischemic brain injury is the most common. Even if patients can survive until discharge, only a few have good neurological recovery, which is sufficient to demonstrate the significant impact of brain injury after cardiopulmonary resuscitation on patients and the medical system (Taccone et al., 2024). The emergency department (ED) is usually the first visit place for such patients. Here, a rapid and accurate assessment of the patient's neurological condition is crucial for subsequent treatment and prognosis judgment. There are significant deficiencies in evaluating brain injury in patients after cardiopulmonary resuscitation in the emergency department using traditional neurological examinations, imaging methods (such as CT), and clinical scoring systems. Sedation therapy, metabolic disorders or targeted body temperature control can all affect clinical examination results, making it difficult to reliably predict prognosis in the early stage (Hoiland et al., 2022; Shen et al., 2023). Although imaging examinations can detect abnormalities in brain structure, they are not sensitive enough to early or minor injuries, and often require patient transfer, which poses risks for patients with unstable conditions (Campagna et al., 2025). Furthermore, the existing clinical imaging diagnostic criteria are sometimes not uniform enough, which may lead to patients being exposed to unnecessary radiation and also waste medical resources. All these issues indicate that we need an auxiliary tool that can objectively, rapidly and stably assess the degree and development of brain injury after acute resuscitation.
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