Exploration and effect evaluation of a clinical teaching model in respiratory medicine based on the "LungSmart" smart healthcare system
- VernacularTitle:基于“LungSmart”智慧医疗系统的呼吸病学临床教学模式与效果评价
- Author:
Yuhang LI
1
;
Junqi WU
2
;
Yi CHEN
2
;
Yayi HE
1
;
Chang CHEN
2
Author Information
1. Department of Thoracic Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, P. R. China
2. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, P. R. China
- Publication Type:Journal Article
- Keywords:
Artificial intelligence;
smart healthcare;
medical education;
"LungSmart" system;
respiratory medicine
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2026;33(08):1203-1211
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the teaching model of the "LungSmart" smart healthcare system in clinical pulmonology teaching and its effectiveness in enhancing the clinical reasoning skills of postgraduate students. Methods A single-center, single-group pretest-posttest educational intervention study was conducted among 30 postgraduate students who participated in respiratory medicine-related teaching activities and enrolled in the "LungSmart" smart healthcare course at Shanghai Pulmonary Hospital from 2024 to 2025 academic year. The course was structured around three core components, namely an AI case repository, dynamic simulation, and immediate feedback, and was delivered over 16 weeks with a total of 64 class hours. Teaching effectiveness was assessed using pretest and posttest clinical reasoning ability scores, while students’ acceptance of the course was evaluated using a 5-point Likert questionnaire. Results All 30 students completed the teaching activities and were included in the final analysis. The pretest score was (78.83±6.25) points, and the posttest score increased to (93.50±4.18) points, with a mean improvement of (14.67±7.06) points (95%CI, 12.03 to 17.30), indicating a statistically significant improvement after the intervention (t=11.37, P<0.001). A total of 30 valid questionnaires were collected at the end of the course, with a response rate of 100.0%. The overall satisfaction score was (4.67±0.15) points, and the mean scores for content satisfaction, practical value, interest stimulation, and professional competence were (4.72±0.23) points, (4.53±0.35) points, (4.72±0.39) points, and (4.75±0.43) points, respectively. Conclusion These findings suggest that the clinical teaching model based on the "LungSmart" smart healthcare system is feasible and well accepted, and may help improve postgraduate students’ clinical reasoning ability.
