Application of digital technology in medical practice

Abstract

Digital technology application in medical practice has become a key focus of stakeholders, with its rapid integration into primary care-encompassing electronic health records (EHRs), teleconsultation, home health monitoring, and moretransforming healthcare delivery [1]. Supported by policies like China ' s 2018 Opinions on Promoting "Internet +Medical Health" (which guides trusted network construction, digital medical education, and intelligent medical device development), recent advancements (e.g. generative AI, blockchain) have further expanded its use into disease diagnosis, treatment, and service provision, unlocking great potential for improving efficiency, timeliness, and precision in public health. However, growing reliance on digital systems also raises critical challenges (data privacy, technical reliability, equitable access) that require rigorous assessment. Thus, this study critically evaluates the strengths and challenges of digital technology in medical practice, aiming to provide a nuanced perspective for its seamless, sustainable integration into primary care.Digital technology is a general term for the technical methods that use digitalization to collect, store, process, transmit, and present information [2]. It encompasses a series of modern information technology tools and methods, including computers, the internet, big data, artificial intelligence, the Internet of Things, blockchain, and so on. Specifically, this technology has the following characteristics. First, digitization of data. Digital technology converts physical signals such as sound, images, and text into binary data that can be processed by computers, making the storage, processing, and transmission of information more flexible and efficient. Second, strong data processing capabilities. With the help of big data analysis technology, digital technology can extract valuable information from a large amount of unstructured data in a short time, assisting in decision-making and prediction [3]. Third, intelligence. The development of AI technology enables digital technology not only to process data simply but also to perform pattern recognition, natural language processing, and machine learning, thus automatically completing complex tasks. Fourth, connectivity and interoperability. Digital technology can enable the connection between devices and systems through the internet and other communication means, allowing information to be seamlessly shared across different devices and platforms. Fifth, strong scalability and flexibility. The architecture of digital technology can be expanded and updated according to changes in demand. The modular design of software systems and hardware devices also makes technological upgrades and functional expansion easier. Sixth, data visualization. Digital technology can transform complex data into intuitive graphics and images, thereby helping users better understand the information.Digital technology, which integrates an array of contemporary informational tools including big data, artificial intelligence (AI), the Internet of Things (IoT), and blockchain, presents both substantial opportunities and challenges within the domain of medicine. The deployment of such technology necessitates careful consideration of several critical issues. Foremost among these is the potential for data processing bias, wherein the efficacy of big data and AI systems is contingent upon the caliber and variety of the training datasets employed. An absence of diversity within these datasets may lead to biased predictions or diagnostic inaccuracies, with a disproportionate effect on underrepresented populations. Furthermore, there is a palpable concern regarding an over dependence on technological solutions, as there exists a risk that healthcare professionals may assign excessive confidence to AI and automated systems. Such reliance could potentially erode the indispensable human elements of clinical judgment and empathy that are integral to the provision of patient care.Digital technology has transformed hospital management by automating personnel scheduling, financial processes, and equipment monitoring. Despite these benefits, critical issues persist:1) Personnel Management: In terms of personnel management, digital technology is mainly used for the development of intelligent scheduling systems, Human Resource Management Systems (HRMS), and performance management systems. Among these, the intelligent scheduling system utilizes algorithms to automatically generate scheduling plans based on personnel skills, availability, and hospital demand, and can be dynamically adjusted in real-time to ensure the rational allocation of medical and nursing resources and improve work efficiency [4].Research data indicate that the incidence of depression among shift nurses reaches 58.82%, with anxiety rates as high as 62.08%. These emotional issues are closely associated with multiple factors, including fatigue during shifts, psychological stress before and after night shifts, postrest recovery, medication use for sleep during night shifts, physical discomfort during shifts, workload intensity, dietary habits during shifts, weekly work hours exceeding 40 hours, and sleep quality before and after night shifts [5]. To address this situation, various intelligent algorithms have been applied to optimize nurse scheduling, significantly improving satisfaction among hospital nurses, their families, and patients. Through multi-objective programming models, these algorithms effectively balance conflicts between subobjectives, enhancing overall scheduling efficiency. This approach ensures equitable distribution of working hours for each nurse while preventing overexertion in certain shifts. [6]. The HRMS integrates processes such as recruitment, onboarding training, attendance, and compensation management through digital technology, achieving automation and standardization of internal personnel management in medical institutions and reducing the error rate of manual operations. The performance management system, by recording employees' work performance and training progress, provides data support for the development of personalized training plans and performance evaluations, thereby enhancing the overall quality of the medical team. Nevertheless, intelligent scheduling systems may inadvertently disregard human factors, such as team dynamics or personal preferences, which could result in discontent among the personnel.2) Financial Management: In financial management, digital technology is mainly used in Financial Information Systems (FIS), electronic invoice systems, and budget management platforms, thereby optimizing the financial processes of medical institutions. Among these, the financial information system is capable of integrating and automatically processing various financial data of medical institutions, including income, expenses, cost accounting, and report generation, improving the accuracy and efficiency of financial data processing [7]. The electronic invoice system simplifies the charging and reimbursement processes and reduces the burden of manual operations through automation, lowering the risk of errors and omissions in accounting. The budget management platform utilizes digital technology and big data analysis techniques to predict future trends in income and expenses, assisting the finance department in formulating reasonable budget plans, achieving efficient resource allocation, and effective cost control.However, the dependence on financial management platforms may expose vulnerabilities to cyber-attacks, thereby potentially jeopardizing the integrity of sensitive financial information.In the management of materials and equipment, digital technology is mainly applied in medical equipment management systems, material supply chain management systems, and asset management platforms. Among these, the medical equipment management system can collect real-time operational data through sensors installed on the equipment and aggregate this data using digital technology and the Internet of Things. It then utilizes big data analysis to predict fault trends, thereby improving the management of materials and equipment, reducing downtime, and extending the lifespan of the equipment [8]. A controlled study demonstrated that the implementation of the PDCA cycle (Plan-Do-Check-Act) management tool for medical devices reduced the failure rate from 2.5 times per 1000 hours to 1.2 times per 1000 hours, while the average repair time after a failure decreased from 8 ±0.7 hours to 5±0.5 hours [9]. This significantly improved equipment operation and maintenance efficiency as well as clinical support capabilities. This not only ensures the continuity of clinical services but also effectively extends equipment lifespan by avoiding costly emergency repairs and maximizing utilization, thereby delivering substantial return on investment. The material supply chain management system achieves automated management of procurement, inventory, and distribution of materials through a digital platform, thereby optimizing the supply chain process and ensuring the timely supply of medical materials. The asset management platform records the usage, location, and maintenance history of equipment and materials, thereby improving the utilization rate of materials, avoiding duplicate purchases, and preventing resource wastage [10]. However, predictive maintenance systems are contingent upon Internet of Things (IoT) devices, which could become vectors of failure in the event that cybersecurity measures are insufficiently robust.In the practice of disease diagnosis and treatment, digital technology is mainly used to acquire and provide relevant information support, enabling medical staff to carry out medical activities more accurately and effectively.Decision Support Systems (CDSS), and other aspects. Among these, AI-assisted diagnosis systems use deep learning algorithms to automatically analyze medical images (such as X-rays, CT, MRI) to detect abnormal lesions, assisting doctors in early diagnosis of diseases such as cancer and stroke, and improving the speed and accuracy of diagnosis [11]. Clinical Decision Support Systems integrate patients' medical history, genomic data, laboratory test results, and medical imaging information to provide doctors with personalized diagnostic recommendations and treatment plans, reducing the incidence of misdiagnosis and missed diagnosis [12].Al-assisted diagnosis has shown promise in improving speed and accuracy.However, algorithms trained on limited datasets risk being less effective for populations not represented in the data. Additionally over-reliance on Al might lead to complacency in human oversight,increasing the likelihood of errors in complex cases.2) Disease Treatment: In disease treatment, digital technology has promoted the widespread application of surgical navigation systems, personalized treatment, intelligent nursing systems, smart beds, and nursing robots. Among these, surgical navigation systems, combining virtual reality (VR), augmented reality (AR), and robotic technology, assist surgeons in performing high-precision minimally invasive surgeries, improving the safety and effectiveness of operations through real-time image guidance [13]. Personalized treatment platforms use patients' genetic information, medical history, and lifestyle data to formulate targeted treatment plans, significantly improving treatment outcomes, especially in cancer and chronic disease management. Intelligent nursing systems can monitor patients' vital signs (such as heart rate, blood pressure, oxygen saturation, etc.), providing timely alerts for necessary interventions. Smart beds and nursing robots assist nursing staff in completing routine patient care tasks, such as adjusting body positions, administering medication, and arranging meals, reducing the workload of nursing staff [14]. Additionally, digital technology records patients' nursing plans, implementation, and assessments through Nursing Information Systems (NIS), promoting the standardization and personalization of nursing work and ensuring that patients receive comprehensive and continuous care services [15].While surgical navigation systems and personalized treatments offer significant advancements, their success depends on the reliability of underlying technology. Failures in these systems could lead to adversepatient outcomes. Furthermore,ethical concerns arise when Al-driven systems suggest treatments without clear explain ability.Digital technology has provided various new methods for the conduct of medical skills training activities, significantly improving the quality and effectiveness of training for doctors and nurses. Specifically, the application of this technology in this area is mainly manifested in the following aspects.Technologies: VR and AR technologies have created an immersive learning experience environment for medical skills training, allowing medical staff to practice operations in a simulated environment. For example, with the help of VR technology, surgeons can simulate complex surgical scenarios and anatomical structures, practice surgical procedures in a risk-free virtual environment, and repeatedly practice specific steps to enhance the precision of surgery [16].A cross-over controlled study published in 2024 involving three mainstream virtual reality simulators demonstrated that VR-trained trainees exhibited significant improvements in laparoscopic basic skill tasks, with a 44% reduction in median instrument manipulation path length and a 45% decrease in median task completion time, indicating substantial progress in both operational efficiency and precision. [17]. Moreover, AR technology can overlay digital anatomical information onto actual operations, providing real-time guidance for doctors performing minimally invasive surgery or needle puncture procedures. In nursing skills training, VR technology can be used for training in emergency operation skills such as simulated cardiopulmonary resuscitation (CPR) or trauma care, helping nurses practice correct methods and steps in emergency situations, improving their emergency response capabilities and reaction speed.2) Simulation Training: Digital technology can be used to support the development and utilization of simulation training systems, thereby providing doctors and nurses with highly realistic operation training platforms, allowing them to engage in training ranging from basic operations to complex surgeries. For example, doctors can use simulation training systems to practice high-difficulty operations such as heart surgery, minimally invasive interventional surgery, and endotracheal intubation. Moreover, the system provides realtime feedback on the precision of the operations and changes in the patient's vital signs, helping to improve their operational skills and strategies. Nurses can use the system's simulated dolls and virtual ward training functions to practice basic nursing skills such as intravenous infusion, wound care, and catheterization. The system also provides real-time feedback on the correctness of the operations, ensuring the precision of nursing skills.The rapid development of digital technology has broken through the traditional limitations of time and space in medical education and training, allowing doctors and nurses to engage in personalized learning through online learning platforms such as WeChat mini-programs, adapting to the increasingly complex medical needs [18]. Online learning platforms not only provide a wealth of learning resources for medical staff but also create a flexible learning environment that can meet the learning needs of medical staff at different stages. For doctors, online platforms offer a variety of learning resources, including surgical video demonstrations, clinical case discussions, diagnostic and treatment guidelines, and academic lectures. Through surgical video demonstrations, one can gain a detailed understanding of the steps and techniques of various surgeries, especially those that are more complex or emerging, such as minimally invasive surgery and robot-assisted surgery. In addition, the clinical case different of disease treatment plans and which doctors can to enhance their clinical decision-making Moreover, online platforms can based on their (such as internal surgery, and etc.), further the time, can also the diagnostic and treatment and clinical through online platforms, with the of medical development and their and For nurses, online learning platforms also offer a wealth of learning resources basic emergency skills, medication management, and patient communication The platform simulated nursing scenarios and operational which can help nurses the of basic skills and complex nursing improving the accuracy and standardization of actual operations. 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