Optimization and evaluation of smart follow-up workflow for day-case breast surgery based on action research
10.3760/cma.j.cn115682-20240809-04445
- VernacularTitle:基于行动研究法的日间乳腺手术智慧随访流程优化及效果评价
- Author:
Lingmei YIN
1
;
Ning ZHANG
;
Haixin BO
;
Dongju FAN
;
Yuanyuan NIE
;
Yiling LIU
;
Chengjing XU
;
Songjie SHEN
;
Qinghua BAI
;
Ying HAO
;
Xiaojie WANG
Author Information
1. 中国医学科学院北京协和医院日间病房，北京 100730
- Publication Type:Journal Article
- Keywords:
Day surgery;
Breast surgery;
Follow-up;
Informatization;
Action research;
Transitional care
- From:
Chinese Journal of Modern Nursing
2025;31(19):2641-2647
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To optimize the smart follow-up workflow for day-case breast surgery patients using an action research approach and evaluate its effectiveness.Methods:A total of 648 post-discharge patients who underwent day-case breast surgery at the Day Surgery Unit of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences between February and May 2024 were selected by convenience sampling. Patients who received routine smart follow-up (automated+telephone) from February to March 2024 served as the baseline group. Patients enrolled in April 2024 ( n=218) and May 2024 ( n=202) formed the first and second cycle groups, respectively, in which the smart follow-up workflow was optimized iteratively using action research. Outcome indicators included automated recovery rate and total recovery rate of follow-up forms, as well as the incidence of postoperative discomfort symptoms. Results:The automated and total recovery rates of follow-up forms in the first and second cycle groups were significantly higher than those in the baseline group, with statistically significant differences observed ( P<0.01). The proportion of patients experiencing persistent chest distress was significantly lower in the first and second cycle groups compared to the baseline group, and further reduced in the second cycle group compared to the first, with statistically significant differences observed ( P<0.01). Pain levels in the first and second cycle groups were also significantly lower than those in the baseline group, with statistically significant differences observed ( P<0.01) . Conclusions:Optimizing the smart follow-up workflow for day-case breast surgery patients based on an action research approach can significantly improve the automated and overall recovery rates of follow-up forms, reduce postoperative discomfort, and enhance both the efficiency and quality of follow-up care.
