Application of digital technology in medical practice

摘要

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