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Orthopedics Department independently develops intelligent follow-up system for clinical research
CopyFrom: PUMCH UpdateTime: 2019-09-20 Hits: 204 Font Size: SmallBig

The 16th Beijing Orthopedics Annual Meeting & the 3rd Great Wall Orthopedics Forum & the 3rd Beijing-Shanghai Orthopedics Summit was held in Beijing from July 26th to 28th, 2019. Over 1,200 orthopedic experts and peers from Beijing and Shanghai attended the conference. During the meeting, Bian Yanyan and his team from the Department of Orthopedics of Peking Union Medical College Hospital (PUMCH) shared their new advances in the application of artificial intelligence (AI) follow-up system in the postoperative follow-up of orthopedic patients.

The AI follow-up system is an automatic follow-up system developed by using both speech algorithm optimization and semantic analysis model construction and iteration. Postoperative patient satisfaction and its relevant technical indicators and scenarios are also integrated. This intelligent follow-up system can simulate human voices and work continuously in a friendly manner; it can select the appropriate time points for automated and personalized follow-up visits in large quantities, during which patients who are inconvenient to answer calls will be recorded and scheduled for another visit; finally, it can automatically collect the patients’ responses and convert the voice information into structured text data in real time, enabling the medical staff to quickly obtain the follow-up conclusions.

The pilot operation in the past three months has confirmed that this system can optimize the follow-up process and save the time required for data access and analysis. The system completed about 400 follow-up visits after discharge every month. Up to 92.2% of the patients answered the calls, and follow-up information was collected from 92.8% of these patients. The average call duration was (87.73±39.54) seconds. Obviously, the AI follow-up system is more efficient than the traditional nurse call systems. It frees the medical staff from simple and time-consuming work, enabling them to be focuses more on the development of disease treatment protocols and the analysis and processing of follow-up data. The audience was amazed by the AI follow-up system and many of them discussed with Bian Yanyan for further cooperation.


Meeting venue (photo: Department of Orthopedics)