市场调查报告书
商品编码
1568888
扩增实境在医疗保健中不断变化的作用:元宇宙和数位健康 4.0The Evolving Role of Extended Reality in Healthcare: The Metaverse and Digital Health 4.0 |
医疗保健产业扩增实境(XR) 产业的趋势、挑战与转型
扩增实境(XR) 是一个涵盖广泛身临其境型的术语,包括混合实境(MR)、扩增实境(AR) 和虚拟实境 (VR) 技术。就医疗保健IT而言,早期和中期医疗保健行业的扩增实境市场前景广阔,其使用案例可以扩展到地理范围并扩展到其他应用程式尚未找到。
扩增实境在医疗保健产业的应用可分为治疗/护理、手术/影像诊断、教育/训练等应用。其中一些可能会重迭,从而使解决方案更加复杂且更易于使用。在生命科学领域,XR应用仍处于起步阶段,其中製药和生物技术应用是重点。
Frost & Sullivan 的这份分析研究了市场的现状,重点关注医疗 IT 领域 XR 技术实施的趋势、挑战、市场驱动因素/促进因素分析、市场驱动因素/促进因素分析以及市场发展潜力。医疗保健专业人员和患者对设备和软体的了解越来越多,但采用率仍然很低。由于监管合规问题、技术开发、许可和医学测试,实施将是一条漫长的道路。在医疗保健领域实施 XR 技术的挑战包括预算限制、变革阻力、可扩展解决方案、互通性、产生人工智慧、大规模语言模型(LLM)、医疗物联网(IoMT),其中包括与该领域其他技术的平滑连接,如云。
主要问题
Trends, Challenges, and Transformation in the Healthcare Extended Reality Industry
Extended reality (XR) is an umbrella term that encompasses a broad spectrum of immersive technologies, including mixed reality (MR), augmented reality (AR), and virtual reality (VR) technologies. Regarding healthcare IT, the early-medium stage healthcare XR market is still finding use cases through which it can expand geographically and to other applications, making this a promising market.
Healthcare XR can be segmented by application-treatment and care, surgery and imaging, and education and training. Some of these can overlap, making solutions more complex and increasing their usability. In life sciences, XR applications are still nascent, and they focus on pharmaceutical and biotechnology applications.
This Frost & Sullivan analysis explores the trends, challenges, drivers, restraints, performance, and challenges of XR technology adoption in healthcare IT, focusing on the current state of the market and its potential development. Providers and patients are getting to know the devices and software-knowledge and adoption rates are still low. Deployment will be a long path due to regulatory compliance issues, technology development, licensing, and medical trials. Some challenges for implementing XR technologies in healthcare include budgetary constraints, resistance to change, scalable solutions, interoperability, and smooth connection with other technologies in the field, such as generative AI, large language models (LLM), Internet of Medical Things (IoMT), and Cloud.
Key Issues Addressed