1. 北京航空航天大学 a. 生物与医学工程学院丨 b. 生物医学工程高精尖创新中心，生物力学与力学生物学教育部重点实验室，
生物与医学工程学院丨c. 医学科学与工程学院，北京 100191丨2. 北京北铃专用汽车有限公司，北京 101500丨3. 中国食品
药品检定研究院 医疗器械检定所，北京 102629丨4. 国药集团医疗器械研究院，北京 100028
Research on Key Indicators Screening for Quality Management System Construction of
Artificial Intelligence Medical Device Enterprises
LIU Yi1a, 2，WANG Hao3，LI Shu3，REN Haiping4，FAN Yubo1b,1c
1. a. School of Biological Science and Medical Engineering丨 b. Beijing Advanced Innovation Centre for Biomedical Engineering,
Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and
Medical Engineering丨 c. School of Engineering Medicine, Beihang University, Beijing 100191, China丨 2. Beijing Beiling Special
Purpose Vehicle Co., Ltd., Beijing 101500, China丨 3. Institute for Medical Devices Control, National Institutes for Food and
Drug Control, Beijing 102629, China丨 4. Medical Technology Academy of Sinopharm Group Co., Ltd., Beijing 100028, China
Abstract：Objective To screen out the key indicators related to the quality management system of artificial intelligence medical
device (AIMD), so as to provide reference for the further construction of AIMD quality management system in the process of
production and development. Methods Based on YY/T 0287-2017 Medical Device Quality Management System Requirements for
Regulatory Purposes, two rounds of expert consultation were conducted to select the indicators related to AIMD quality management
system, and Likert 5-point method was used for weight scoring of these indicators. After data formatting, IBM SPSS 21.0 was used
for statistical analysis to calculate the weight mean, standard deviation (SD), coefficient of variation (CV) and full score rate of each
index. Results A total of 15 questionnaires were issued and 15 questionnaires were collected, with the response rate of 100%, and
the authority coefficient (Cr) value of experts of 0.91. A total of 5 first-level indicators, 12 second-level indicators and 36 third-level
indicators were screened. The average scores of all indicators ranged from 3.40 to 4.93, with SD less than 1.00 and CV less than 25%.
The average scores of “design and development verification”, “design and development confirmation” and “design and development
change control” were 4.93, 4.87 and 4.87 respectively, the SD were 0.26, 0.35 and 0.35 respectively, the CV were 5.23%, 7.23%
and 7.23% respectively, and the full score rates were 93.33%, 86.67% and 86.67% respectively. Conclusion Through two rounds of
expert consultation, the key indicators for the construction of product quality management system in the production and development
process of AIMD enterprises are basically determined, which will provide reference for the further construction of product quality
management system.
刘毅1a, 2，王浩3，李澍3，任海萍4，樊瑜波1b,1c. 人工智能医疗器械企业质量管理体系构建关键指标筛选研究[J]. 中国医疗设备, 2021, 36(3): 24-27.
LIU Yi1a, 2，WANG Hao3，LI Shu3，REN Haiping4，FAN Yubo1b,1c. Research on Key Indicators Screening for Quality Management System Construction of
Artificial Intelligence Medical Device Enterprises. China Medical Devices, 2021, 36(3): 24-27.
