市場調查報告書
商品編碼
1568888
擴增實境在醫療保健中不斷變化的作用:元宇宙和數位健康4.0The Evolving Role of Extended Reality in Healthcare: The Metaverse and Digital Health 4.0 |
醫療保健產業擴增實境(XR)產業的趨勢、挑戰與轉型
擴增實境(XR)是一個涵蓋廣泛身臨其境型的術語,包括混合實境(MR)、擴增實境(AR)和虛擬實境(VR)技術。就醫療保健IT而言,早期和中期醫療保健行業的擴增實境市場前景廣闊,其使用案例可以擴展到地理範圍並擴展到其他應用程式尚未找到。
擴增實境在醫療保健產業的應用可分為治療/護理、手術/影像診斷、教育/訓練等應用。其中一些可能會重疊,使解決方案更加複雜且更易於使用。在生命科學領域,XR應用仍處於起步階段,其中製藥和生物技術應用是重點。
Frost & Sullivan 的這份分析研究了市場的現狀,重點關注醫療 IT 領域 XR 技術實施的趨勢、挑戰、市場促進因素/促進因素分析、市場促進因素/促進因素分析以及市場發展潛力。醫療保健專業人員和患者對設備和軟體的了解越來越多,但採用率仍然很低。由於監管合規問題、技術開發、許可和醫學測試,實施將是一條漫長的道路。在醫療保健領域實施 XR 技術的挑戰包括預算限制、變革阻力、可擴展解決方案、互通性、產生人工智慧、大規模語言模型(LLM)、醫療物聯網(IoMT)雲端等,與該領域其他技術的平滑連接。
主要問題
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