Objective: To establish a quality control model ensuring good stability and compatibility of manually compounded total nutrient admixtures (TNA). Methods: A parenteral nutrition medication order entry system was establish for standardizing nutritional medication usage and supporting physician's TNA prescribing. TNA medication orders were reviewed by pharmacists for validating the stability and compatibility. TNAs were compounded by pharmacists in a standard way following "four factors of sterile compounding" . The goal of quality control was achieved by establishment of the preliminary standard. Results: The quality of manually compounded total nutrient admixtures achieved the goal since pharmacy intravenous admixture service (PIVAS) started on 2003. Conclusions The quality of TNA is well assured while manually compounded by pharmacists in PIVAS.

Objective:To establish a design of a clinical decision support (CDS) system ithin the computerized physician order entry (CPOE) system to ensure the correct prescribing of total nutrient admixture (TNA) orders.Methods:An improved new workflow was designed in consideration of both the TNA and doctor's prescription work flow. An exclusive CPOE interface for TNA physician order was established, within which a CDS mode was also created. When individual components of the TNA physician order are inputted, automatic calculation is performed through CDS to determine whether patient's clinical nutritional needs and pharmaceutical process requirements are both met. The generated feedback is presented directly to the prescribing clinician in the interface. Through rationality assessment of physician orders and real-time alarm feedback for inappropriate orders, the system can achieve pre-review of TNA orders as well as the education for clinicians on parenteral nutrition order prescription.Results:The usable drug catalog is created at the back end of CDS, thus precluding unreasonable medical orders of therapeutic drugs in TNA regimens. The background CPOE auxiliary support system for parenteral nutrition can correctly evaluate the reasonability of the carrier solution and provide real-time feedback in the CPOE interface.Conclusion:The establishment of the CPOE auxiliary support system eliminates the possibility of unreasonable component proportions and admixture with other therapeutic drugs in TNA orders to ensure TNA orders with rationale component proportion and good compatibility and stability, ultimately satisfying patient's daily calory need and guaranteeing medication safety of parenteral nutrition.

Components and compounding of parenteral nutrition solutions were different in different hospitals and different parts of China.In order to raise awareness,reduce improper compounding and improve patient safety,Pharmacy Cooperative Group of Chinese Society for Parenteral and Enteral Nutrition composed the Consensus for Parenteral Nutrition Solutions Compounding,providing evidence for standardization in this field.

Objective To explore the fluctuation characteristics of long-term doctor's order workload in pharmacy intravenous admixture services (PIVAS) and build a daily workload fluctuation prediction model and provide reference for the adjustment of PIVAS work mode. Methods Daily workload data of long-term doctor’s orders from PIVAS in the East Campus of Zhongshan Hospital affiliated to Fudan University from July 2020 to June 2021 were selected , and the time series analysis method was used to analyze the workload fluctuation characteristics and a prediction model was established. The accuracy of the model was verified by fitting parameters and prediction results. Results The fluctuation of PIVAS long-term doctor's daily workload data had the characteristics of periodicity, short-term slow rise and irregular variation. The Winters multiplier model was used to fit the series with R² = 0.777, the significance value of Ljung-Box statistic value (P value) was 0.060, and the mean absolute error percentage between the fitted and actual values was 4.45%, indicating that the model fitting accuracy was high. The average relative deviation between the predicted and actual results was 3.81%, indicating that the model prediction was effective. Conclusion The model constructed in this study could be used for the analysis and prediction of long-term doctor's orders workload of PIVAS. However, because the workload of doctor's orders has fluctuations such as periodicity and irregular changes, it is necessary to adjust the working model according to the fluctuation characteristics of the workload and the prediction results to ensure the efficient operation of PIVAS.