Objective To explore the influencing factors of the usage behavior of the scientific research management system and provide references for hospitals in constructing scientific research management systems. Methods Data were collected through questionnaires in April 2024. Based on the unified theory of acceptance and use of technology (UTAUT), the information system success model, and the self-efficacy theory, a research model on the influencing factors of the usage behavior of the scientific research management system among medical staff was constructed from the dual perspectives of users and information systems. The structural equation model was utilized to explore the influencing factors of the usage behavior of the scientific research management system. Results A total of 527 questionnaires were collected. Among them, there were 157 males and 370 females. The overall Cronbach α coefficient of the questionnaire was 0.916, and the KMO value was 0.896. For Bartlett’s test of sphericity (P<0.001). The composite reliability of each latent variable was greater than 0.7, and the average variance extracted was greater than 0.5. Therefore, this questionnaire had good reliability and validity. The research showed that information quality, performance expectancy, effort expectancy, and system quality all had significant positive impacts on the usage intention of users of the scientific research management system (P<0.05). Meanwhile, facilitating conditions and usage intention both had significant positive impacts on the usage behavior of users (P<0.05). Conclusions The construction of the scientific research management system should be guided by management needs, comprehensively sort out the general scientific research work needs of medical staff. Through the apply information-based means, various forms of training, and strengthening policy guidance, the aim is to improve the intelligence level of system operations, enhance the convenience of user self-service, and promote the effective construction of the ecosystem of the scientific research management system.
ObjectiveTo understand the current status of healthcare human resources (HHR) in a large public hospital, predict the HHR demand aligned with the development of the hospital, and provide reference basis and feasible solutions for HHR planning for high-quality development of the large public hospital. MethodsBased on grey model and auto regressive integrated moving average model, a variance reciprocal method for weight allocation was applied to set up the combination forecasting model. Different types of HHR demand of the large public hospital from 2024 to 2026 were predicted and the accuracies of the three different model predictions were compared. ResultsThe numbers of total personnel, health technical personnel, physicians, nurses, and technicians predicted by the combination forecasting model for 2026 were 17654, 13041, 4389, 6198, and 2264, respectively. The corresponding average annual growth rates from 2024 to 2026 were 5.54%, 5.55%, 5.37%, 4.27%, and 5.60%, respectively. Compared with the two single forecasting models, the combination forecasting model had the smallest average absolute errors, mean squared errors, and mean absolute percentage errors for predicting the numbers of total personnel, nurses, and technicians. It also had the smallest average absolute error and mean absolute percentage error for predicting the number of health technical personnel, and the smallest average absolute error for predicting the number of physicians. ConclusionsCompared with the single forecasting model, the combination forecasting model shows fewer system errors and better predictive results. The demand for total personnel, health technical personnel, physicians, nurses, and technicians of this large public hospital will continue to increase, so planning and reserving staff in advance is a key to high-quality development of the hospital.