Tongji Hospital of Huazhong University of Science and Technology to Transfer Clinical Nursing Management Technology for RMB 200,000

Recently, Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology released a public notice on the transformation of scientific and technological achievements. The university intends to transfer the relevant technologies through negotiated pricing.“Clinical Nursing Management Methods and Related Equipment”The relevant patents have been assigned to Wuhan Nisheng Intelligent Technology Co., Ltd., with the transfer amount being200,000 yuan. The inventors of this patent areYang Qiao and her team。

The assignee of this patent isWuhan Nisheng Intelligent Technology Co., Ltd.,is a technology-driven enterprise focused on the research, development, and integration services of intelligent systems. The company holds qualifications including Grade I Professional Contracting for Electronic and Intelligent Engineering and Grade B Specialized Qualification for Architectural Intelligent System Engineering Design, and has been recognized as a High-Tech Enterprise (2023) and a Technology-Based Small and Medium-sized Enterprise (2024). Its core business activities include the design and construction of building intelligence projects and electromechanical engineering contracting.

This technology belongs toIntelligent Management Solution for Clinical Nursing, with its core focus on leveraging wearable smart devices, intelligent language models, and automated management mechanisms to address challenges in clinical nursing such as task complexity, susceptibility to omissions, and intricate workflows, thereby achieving refined, efficient, and standardized nursing care.

With the continuous advancement of medical technology, clinical nursing procedures have become increasingly complex. Meanwhile, a long-standing shortage of nursing human resources has led to a sustained increase in the workload of on-duty nursing staff, resulting in mounting pressure within the nursing profession. However, traditional clinical nursing management models suffer from numerous critical deficiencies, significantly increasing the likelihood of errors, omissions, and mistakes in nursing practice. This has severely compromised nursing quality and patient satisfaction, becoming a core obstacle to achieving high-quality development in the clinical nursing industry.

Traditional clinical nursing management has defects in core mechanisms:On one hand, task management relies excessively on manual labor, with nursing staff depending on their personal experience and memory to schedule work, lacking systematic task recording and scheduling mechanisms. In clinical nursing scenarios, frequent work interruptions are highly likely to result in the omission or delay of routine nursing tasks. Furthermore, equipment operations, procedural standards, and documentation metrics vary across different nursing processes, and these cumbersome and complex procedures further increase the risk of human error. On the other hand, task coordination lacks a scientific basis; when multiple nursing tasks conflict within the same timeframe, prioritization relies solely on the subjective judgment of nursing staff, making it difficult to accurately align with task urgency and patient needs. This often leads to delays in critical nursing interventions, thereby adversely affecting patient treatment outcomes.

In terms of practical application scenarios,Traditional management models exhibit significant practical shortcomings.Nursing staff are required to handle multiple tasks simultaneously in their daily work. When their hands are occupied, it is difficult to perform manual documentation in real time, leading to inefficient transmission of task information. Meanwhile, the lack of standardized support for nursing processes results in variations in operational protocols among different nurses. This not only affects the consistency of nursing services but also poses challenges for subsequent quality traceability. Furthermore, the continuity of nursing care is suboptimal; after completing a nursing task, related follow-up procedures (such as documentation feedback and subsequent care arrangements) rely entirely on manual handoffs. This makes the process prone to breakpoints and prevents the achievement of closed-loop management.

More critically,Traditional models lack the capability for dynamic adaptation to patient status.The execution of nursing tasks is largely planned according to fixed schedules, without adequate adjustment based on patients’ real-time physiological changes and behavioral status. This may compromise the accuracy of results for tasks that are sensitive to patient conditions, such as vital signs monitoring, due to suboptimal timing. Meanwhile, the evaluation of nursing care effectiveness and process optimization lack data support, making it difficult for managers to gain a comprehensive understanding of nurses’ work performance and to implement targeted improvements in management strategies.

These issues collectively lead clinical nursing into"Complex tasks prone to omission, non-standardized processes prone to error, and inefficient coordination compromising quality"...dilemma, the market urgently needs an intelligent and refined nursing management solution to resolve end-to-end challenges spanning task initiation, scheduling, and execution.

Addressing core pain points in clinical nursing, such as “complex tasks prone to omission, non-standardized processes susceptible to errors, and inefficient coordination compromising quality,” the team leverages“Intelligent Full-Process Task Management + Scenario-Based Precise Adaptation”This core advantage underpins an integrated solution encompassing task entry, creation, scheduling, and execution, effectively breaking the limitations of traditional manual management models and paving a new path for the refined and efficient development of clinical nursing.

In the field of intelligent task management, this technology has achieved end-to-end automation, significantly reducing reliance on manual labor and the risk of errors. Traditional nursing tasks primarily depend on manual recording, memorization, and prioritization; consequently, omissions are prone to occur when workflows are interrupted or particularly complex.This technology employs a triple mechanism of “voice input + intelligent parsing + dynamic scheduling” to achieve full-process intelligence in task management.Caregivers can use wearable smart healthcare terminals (such as smartwatches) to directly input task instructions via voice (e.g., “Measure Mr. Zhang’s blood pressure at 3:00 PM”). The system employs speech recognition technology, based on deep learning algorithms such as CNN and LSTM, to rapidly convert speech into text. It then leverages large language models like BERT and GPT to automatically extract key features, including nursing items, patient information, and scheduled execution times, thereby generating standardized to-do tasks without the need for manual entry.

To address multi-task scheduling conflicts, the system intelligently determines task priorities and automatically allocates optimal execution time slots based on the urgency of nursing interventions or by integrating patients’ real-time vital sign data (such as blood pressure and heart rate, updated cyclically every 15 minutes). For instance, urgent tasks like “blood pressure measurement” are prioritized, while non-urgent tasks such as “dressing changes” are reasonably deferred, thereby fundamentally preventing task delays or disordered sequencing.

In terms of process adaptation and precise reminders,This technology closely aligns with the needs of clinical scenarios, achieving a “personalized, closed-loop, and highly precise” management model.Traditional nursing reminders are mostly triggered at fixed times, lacking dynamic adaptation to task characteristics and patient status. This innovation constructs a multi-layered reminder mechanism, making nursing execution more precise and efficient. For tasks with specific requirements for patient status, such as vital signs measurement, the system uses video surveillance data to analyze the patient's behavioral state (e.g., whether they are in a quiet resting state) and only sends reminders when the patient meets ideal execution conditions, ensuring the accuracy of measurements. For basic tasks, the system sends operation instructions via terminal vibration, voice prompts, etc., before the ideal execution period. If the task is not completed, the system will automatically repeat the reminders, effectively preventing task omissions.

Meanwhile,The system features intelligent prediction of associated tasks:After creating a new task or completing an existing one (e.g., “dressing change”), the system can automatically predict subsequent related tasks (e.g., “documenting patient medication response”) and provide voice prompts. Upon confirmation by nursing staff, the related task can be quickly created, establishing closed-loop management and preventing breaks in the workflow. Furthermore, based on nursing items and patient information, the system intelligently predicts task execution intervals (e.g., dressing changes every 8 hours) and automatically generates recurring to-do tasks, significantly enhancing the planning and continuity of nursing care.

In terms of standardization and practical applicability, this technology demonstrates“Easy to operate, highly adaptable, and traceable”outstanding advantages. Nursing staff can operate the system proficiently without extensive training, achieving voice interaction through wearable terminals that align seamlessly with clinical scenarios where hands are often occupied; the system supports integration with existing medical equipment, enabling periodic acquisition of patient vital signs data without imposing additional burdens of manual collection. Information such as task execution time, personnel involved, and outcomes is automatically recorded and stored, facilitating performance evaluation and quality traceability for managers, thereby ensuring that the entire nursing process is controllable and auditable. The core technical parameters are clearly defined and manageable, with standardized settings for task priority determination rules, reminder trigger conditions, and data collection intervals, allowing rapid adaptation to clinical nursing scenarios in hospitals of varying scales without requiring large-scale equipment modifications, thus possessing strong value for replication and promotion.

Furthermore, this technologyEnhancing Nursing Quality and Improving Work Experienceremarkable results have been achieved. By leveraging standardized processes and intelligent reminders, human errors can be effectively reduced, the incidence of adverse nursing events lowered, and patient satisfaction during hospitalization improved. Automated task entry, intelligent prioritization, and predictive task association significantly alleviate nurses’ cognitive load and documentation burden, mitigate occupational anxiety stemming from heavy workloads and complex workflows, and substantially enhance their work experience. Meanwhile, the long-term accumulation of nursing data within the system enables intelligent analytics, empowering managers to gain insights into patterns and trends in nursing practice. This provides robust data support for nursing resource allocation, process optimization, and decision-making, thereby driving continuous improvement and high-quality development in clinical nursing care.

Intelligent clinical nursing management has become one of the core tracks in healthcare informatization. Leading domestic and international healthcare technology enterprises and information service providers have all launched mature nursing management solutions, focusing on the core needs of "closed-loop processes, efficiency enhancement, and risk control," thereby formingCentered on Two Main Threads: “Electronic Health Record (EHR) System Integration” and “Specialized Nursing Management Platform”competitive landscape.

Epic’s EpicCare Nursing Management Module: As a global leader in healthcare IT solutions, Epic integrates comprehensive nursing management capabilities into its EpicCare system. Core modules include nursing task workqueues, closed-loop medication administration, and clinical communication and collaboration. The system supports customized classification and filtering of nursing tasks, enabling the creation of specialized workqueues for patient follow-ups, order execution, and charge auditing. Nurses can defer tasks, transfer them across departments, and document the rationale for these actions, ensuring full traceability throughout the task lifecycle. Its clinical communication feature, Epic Secure Chat, facilitates real-time collaboration between nurses and the broader care team, ensuring efficient transmission of task-related information.

Cerner CareAware Smart Nursing Solution: Cerner’s CareAware suite is a specialized solution focused on clinical nursing scenarios, with its core strengths lying in device interoperability and intelligent infusion management. The system achieves deep integration with medical devices such as infusion pumps and patient monitors, enabling real-time acquisition of infusion status—including infused volume, remaining volume, and infusion rate—and displaying this data graphically on nursing terminals, thereby eliminating the need for frequent manual checks. Leveraging the CareAware iAware module, device data is automatically synchronized to patients’ electronic health records (EHRs), achieving closed-loop management of “physician order–execution–documentation” and preventing errors associated with manual entry. This solution has been deployed at scale in top-tier tertiary hospitals across multiple countries worldwide.