โก Quick Summary
This systematic review highlights how artificial intelligence (AI) can enhance the clinical and rehabilitation management of knee osteoarthritis (KOA), particularly through the innovative contributions of specialized nurses. Key findings include the use of AI-powered remote monitoring systems and predictive analytics that significantly improve patient care and outcomes.
๐ Key Details
- ๐ Study Period: January 1, 2019 – May 1, 2025
- ๐ Sources: Peer-reviewed studies from PubMed, Google Scholar, and IEEE Xplore
- ๐งโโ๏ธ Focus: Integration of AI in KOA management and implications for nursing practice
- ๐ ๏ธ Methodology: Systematic review with data extraction and quality appraisal by independent reviewers
๐ Key Takeaways
- ๐ค AI-powered remote monitoring allows real-time tracking of patients’ pain levels and mobility.
- ๐ Predictive analytics help identify patients at risk for rapid disease progression.
- ๐ฌ Virtual health assistants enhance patient education and adherence to treatment plans.
- ๐๏ธ Automation of routine tasks reduces administrative burdens on nurses.
- ๐ฅ Improved patient outcomes through tailored and timely interventions.
- ๐ Study emphasizes the role of specialized nurses in leveraging AI technologies.
๐ Background
Knee osteoarthritis (KOA) is a prevalent condition that significantly impacts patients’ quality of life. Traditional management strategies often fall short in providing personalized care. The integration of artificial intelligence into healthcare offers a promising avenue for enhancing the management of KOA, particularly through the unique capabilities of specialized nursing professionals.
๐๏ธ Study
This systematic review aimed to explore the role of AI in the management of KOA, focusing on how these technologies can support nursing practice. The review followed established protocols and included a comprehensive search of relevant studies, ensuring a robust analysis of the current landscape of AI applications in KOA care.
๐ Results
The findings revealed that AI-powered remote monitoring systems are a key innovation, enabling nurses to continuously assess patients’ symptoms and intervene promptly when necessary. Additionally, AI-driven predictive analytics allow for early identification of patients at risk for complications, facilitating proactive adjustments to care plans. These advancements not only enhance patient care but also empower nurses to focus more on direct patient interactions.
๐ Impact and Implications
The integration of AI in KOA management has the potential to revolutionize patient care. By enabling nurses to deliver more effective and tailored interventions, AI can significantly improve patient outcomes. This study underscores the importance of embracing technology in nursing practice, paving the way for enhanced care delivery in various healthcare settings.
๐ฎ Conclusion
This systematic review highlights the transformative potential of artificial intelligence in the management of knee osteoarthritis. By equipping nurses with advanced tools and insights, AI can lead to more effective, personalized care, ultimately improving patient outcomes. The future of KOA management looks promising with the continued integration of AI technologies in nursing practice.
๐ฌ Your comments
What are your thoughts on the integration of AI in healthcare, particularly in managing conditions like knee osteoarthritis? We would love to hear your insights! ๐ฌ Share your comments below or connect with us on social media:
Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review.
Abstract
OBJECTIVES: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizing the unique contributions of specialized nurses.
DESIGN: A systematic review was conducted to examine the integration of AI in the management of KOA, with a specific focus on implications for nursing practice.
METHODS: This review followed established systematic review protocols. A comprehensive search of peer-reviewed qualitative and quantitative studies was conducted across PubMed, Google Scholar, and IEEE Xplore from January 1st, 2019, to May 1st, 2025. Studies were selected based on predefined inclusion and exclusion criteria. Data extraction and quality appraisal were independently performed by two reviewers using standardized tools.
RESULTS: One key innovation is the use of AI-powered remote monitoring systems that collect data from wearable devices, allowing nurses to track patients’ pain levels, joint mobility, and physical activity in real time. These systems enable continuous, remote assessment of symptoms, so nurses can intervene promptly if a patient’s condition deteriorates. Additionally, AI-driven predictive analytics are helping nurses identify patients at higher risk for rapid disease progression or complications, allowing for early, proactive adjustments to care plans. Virtual health assistants and AI-based chatbots are also transforming patient education by answering common questions, guiding patients through home exercises, and providing reminders for medication and lifestyle adherence. By automating routine tasks such as documentation and appointment scheduling, AI reduces administrative burdens, giving nurses more time to focus on direct patient care.
CONCLUSIONS: AI holds promise in revolutionizing KOA disease management by enabling nurses to deliver more effective, tailored care and ultimately improving patient outcomes.
Author: [‘Wang F’, ‘Wang L’, ‘Zhong L’, ‘Feng J’, ‘Wang X’]
Journal: Pain Manag Nurs
Citation: Wang F, et al. Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review. Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review. 2025; (unknown volume):(unknown pages). doi: 10.1016/j.pmn.2025.07.013