Application of metaverse technology in medical quality control

Medical quality control is very important to improve medical services, protect patients’ rights and interests, and improve medical efficiency. It is like a precise ruler to measure whether each medical procedure meets the standards. Through quality control, problems can be found and corrected in a timely manner, such as diagnostic accuracy, treatment appropriateness, medication rationality, etc., to ensure the safety, effectiveness, appropriateness and consistency of medical services. However, at present, medical quality control faces many difficulties: (1) data collection and processing are challenging, medical data are diverse, complex and scattered, and integration is difficult; (2) data analysis is difficult to use, and professional medical personnel need to interpret it in order to find problems and propose improvement plans; (3) quality control supervision is not in place, and the medical quality management system needs to be improved, and the investment is large; (4) It is difficult to make continuous improvement, which requires medical institutions to have the motivation and ability to continuously improve, and apply new quality control technologies that keep pace with the times. For example, the application of metaverse decentralized data sharing technology to medical quality control is a major innovation in the medical field, which can comprehensively improve the quality of medical services by establishing a sound quality control system, simplifying processes, strengthening supervision, and vigorously improving the quality of quality control personnel, strengthening information management and effect evaluation, and combining the real-time monitoring and feedback advantages of metaverse technology: (1) build a decentralized medical quality control platform to realize real-time collection, transmission and analysis of medical data, and ensure real-time monitoring and feedback of medical quality; (2) using decentralized technology to optimize medical processes, improve efficiency and reduce error rates; (3) implement telemedicine quality control, so that experts can remotely guide primary medical work; (4) in-depth mining and analysis of medical quality data, discovering patterns and providing basis for continuous improvement; (5) carry out medical quality education and training to improve the quality awareness and skills of medical staff; (6) carry out medical quality prediction and early warning, analyze data in real time, and grasp the quality trend. Although the Internet of Things and metaverse decentralization technology have brought new opportunities for medical quality control, there are still some challenges, such as immature technology, low user acceptance, data security and privacy protection, and cost.

Key Words: medical quality control; Internet of Things; metaverse; artificial intelligence; machine learning