XU Jiajie 1,2,3,4 , CHEN Yiwei 5 , CHEN Keyu 5 , HUANG Xingyi 5 , TAN Zhuo 1,2,3,4 , ZHENG Chuanming 1,2,3,4 , XIN Ying 1,2,3,4 , TAN Mingming 6 , GUO Haiwei 1,2,3,4 , GUO Yawen 1,2,3,4 , YANG Wenjing 7 , GE Minghua 1,2,3,4
  • 1. Department of Head and Neck Surgery, Otolaryngology & Head and Neck Center, Cancer Center, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital of Hangzhou Medical College), Hangzhou 310014, P. R. China;
  • 2. Thyroid Cancer Expert Committee of National Cancer Quality Control Center, National Cancer Center, Beijing 100000, P. R. China;
  • 3. Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou 310014, P. R. China;
  • 4. Zhejiang Provincial Clinical Research Center for Malignant Tumor, Hangzhou 310014, P. R. China;
  • 5. Second Clinical Medical College, Zhejiang University of Chinese Medicine Hangzhou 310014, P. R. China;
  • 6. Department of Quality Management, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital of Hangzhou Medical College), Hangzhou 310014, P. R. China;
  • 7. National Cancer Center, National Cancer Clinical Medical Research Center; Quality Control Office of Cancer Diagnosis and Treatment, Cancer Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100000, P. R. China;
YANG Wenjing, Email: wenjing86824@126.com
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Objective Explore the impact of a digital-intelligence-based quality control platform for thyroid cancer on the effectiveness of clinical diagnosis and treatment quality management. Methods The digital-intelligence-based quality control platform for thyroid cancer at Zhejiang Provincial People’s Hospital was launched at the end of July 2022. In its initial phase, six quality control indicators related to the standardized diagnosis and treatment of thyroid cancer were deployed. This study analyzed the changes in these six quality control indicators between January 2022 and November 2023, comparing data before and after the platform’s implementation. Results Compared with the period from January to July 2022 (prior to the platform’s launch), the rates of preoperative cytopathological examination (t=–8.450, P<0.001) and postoperative pTNM staging for thyroid cancer patients (t=–3.001, P=0.013) increased from July to November 2023 (one year post-launch). However, the proportion of minimally invasive surgeries among thyroid cancer patients (t=4.278, P=0.002) decreased. The linear regression model results indicated that, following the platform’s launch, there was a gradual increase over time in both the preoperative cytopathological examination rate for thyroid cancer (standard β=0.765, P=0.001) and the postoperative pTNM staging rate (standard β=0.499, P=0.049). Conclusion Preliminary results of this study suggest that the thyroid cancer digital-intelligence-based quality control platform developed by our team can effectively enhance the standardized quality control of clinical diagnosis and treatment for thyroid cancer.