Objective To analyze the research hotspots and development trend of medical advice at home and abroad, and provide the basis for the research related to medical advice in China. Methods The China National Knowledge Infrastructure and Web of Science were searched from January 1991 to November 2023 to collect domestic and international studies on medical prescriptions. Bibliometrics and CiteSpace software were used for analysis. Results A total of 3 155 articles were included. The number of publications on medical advice reached its peak in 2013, and the trend of domestic and foreign publications was consistent; the institution with the largest number of publications in China was Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology; the top three hotspots of attention in China were rational medication use, intravenous medication dispensing center and nursing care; the top three hotspots of attention in foreign countries were care, impact, and system; the top three hotspots of attention in China were intravenous medication (centralized) dispensing center and medical prescription audit 2 emergent words emergent rate had been continued to date; foreign polst, palliative care and advance care planning 3 emergent words emergent rate had been continued to date; domestic in the past five years, the key words were quality improvement, lean management, transitional care, rationality evaluation, prescription front audit system and medication adherence; the keywords for the last five years in foreign countries were assessmen, risk factor, clincial pathway. ConclusionsDomestic research on medical prescriptions needs to pay more attention to the decision-making of doctors when they give medical prescriptions and the timely monitoring of medication errors, and based on the more mature research on medical prescriptions in foreign countries, domestic research needs to combine the concepts of computer-assisted decision-making and value-based medicine to explore in-depth the correlation between medical prescriptions and the quality of medical care and patient value. It is also needed to combine computer-assisted decision-making and the concept of value-based medicine to explore the intrinsic connection between medical advice and medical quality and patient value.
ObjectiveTo 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. MethodsA 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. ResultsAll 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. ConclusionThese 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.
