Clinical Engineering Benchmarking Comparison Between Zhejiang Province and American Hospitals

Clinical engineering(CE) has evolved rapidly over the last 25 years in China. Among the 34 provincial-level administrative units within China, the Zhejiang Province is one of the most advanced in terms of healthcare technology maintenance and management. In order to determine Zhejiang's current stage of development and opportunities for further improvement, a comparison of the performance of its CE departments was made against hospitals in the USA. Data were collected from 21 Zhejiang hospitals and compared to those from 270 acute-care hospitals in USA collected by Truven Health Analytics. The benchmarking comparison was made in three categories: operational, financial, and productivity. Within the operational category, the following metrics were compared: equipment inventory size/operating beds, annual repairs/inventory size, and annual scheduled maintenance/inventory size. Within the Financial category, the following metrics were compared: total CE expense/operating beds and total CE expense/total hospital expense. Within the Productivity category, the following metrics were compared: total CE full-time equivalent(FTE)/inventory size and total CE FTE/total hospital expense. These comparisons showed that:(1) While the equipment inventory in Zhejiang tends to be much smaller than USA for hospitals of comparable amount of operating beds, the numbers of repairs and scheduled maintenance per inventory size are similar;(2) The total CE expense/total hospital expense ratio is around 1% in both Zhejiang and USA; however, the total CE expense/operating beds and total CE expense/cost of equipment inventory are significantly lower in Zhejiang than USA;(3) The FTE amount in Zhejiang is significantly higher than in USA relative to both inventory size and total hospital operating expense, but significantly lower relative to the number of operating beds. The fact that repairs and scheduled maintenance are similar in Zhejiang and USA shows that CE leaders are managing equipment in comparable manner. Most of the differences found in the comparisons were traced to a few factors. First, the average length of stay in China is substantially higher than USA, which explains why hospitals in Zhejiang tend to have more operating beds but fewer pieces of equipment. Second, labor cost is significantly lower in China than USA, thus allowing Zhejiang hospitals to employ more workers than their American counterparts. Third, there is significantly difference in the cost of living between China and USA; Finally, being public entities Chinese hospitals are managed and operated in a different manner than American hospitals, which are mostly private, albeit nonprofit organizations. Nonetheless, it is interesting to note that hospitals in both areas spend roughly 1% of their total expenditure for CE. The results suggest that CE in Zhejiang is comparable to USA in terms of managerial excellence but there could be some room for improvement in financial management and productivity.

Prediction of SMILE surgical cutting formula based on back propagation neural network

AIM:To predict cutting formula of small incision lenticule extraction(SMILE)surgery and assist clinicians in identifying candidates by deep learning of back propagation(BP)neural network.METHODS:A prediction program was developed by a BP neural network.There were 13188 pieces of data selected as training validation.Another 840 eye samples from 425 patients were recruited for reverse verification of training results.Precision of prediction by BP neural network and lenticule thickness error between machine learning and the actual lenticule thickness in the patient data were measured.RESULTS:After training 2313 epochs,the predictive SMILE cutting formula BP neural network models performed best.The values of mean squared error and gradient are 0.248 and 4.23,respectively.The scatterplot with linear regression analysis showed that the regression coefficient in all samples is 0.99994.The final error accuracy of the BP neural network is-0.003791±0.4221102μm.CONCLUSION:With the help of the BP neural network,the program can calculate the lenticule thickness and residual stromal thickness of SMILE surgery accurately.Combined with corneal parameters and refraction of patients,the program can intelligently and conveniently integrate medical information to identify candidates for SMILE surgery.

Design of a Web-based Medical Equipment Management System for Clinical Engineering

Objective: Medical equipment safety in clinical use has been an increasingly concerned issue in China. This paper aims to design and implement a web-based medical equipment maintenance system to be used at clinical engineering department, orienting to the improvement of quality and efficiency of technology service so as to meet the 2010 regulations homologated with China's Ministry of Health. Methods: The system adopted three-layer structure based on B/S mode with oracle database and ASP.NET development technologies. Based on risk management and inclusion criteria for maintenance, the software system modules consist of hospital equipment inventory management, personnel information management, breakdown maintenance, preventive maintenance(PM) and analysis graphical representations.Results: An user friendly web interface was provided for easy and secure access to the system. Medical equipment management activities from log-in to acceptance test to maintenance services were implemented. Conclusion: The application of this system has achieved benefits for the risk management of medical equipment.