Objective To explore the predicted precision of discharged patients number using curve estimation combined with trend-season model. Methods Curve estimation and trend-season model were both applied, and the quarterly number of discharged patients of 363 hospital from 2009 to 2015 was collected and analyzed in order to predict discharged patients in 2016. Relative error between predicted value and actual number was also calculated. Results An optimal quadratic regression equation Yt=3 006.050 1+202.350 8×t–3.544 4×t2 was established (Coefficient of determination R2=0.927, P<0.001), and a total of 23 462 discharged patients were predicted based on this equation combined with trend-season model, with a relative error of 1.79% compared to the actual number. Conclusion The curve estimation combined with trend-season model is a convenient and visual tool for predicting analysis. It has a high predicted accuracy in predicting the number of hospital discharged patients or outpatients, which can provide a reference basis for hospital operation and management.
To achieve policy goals of new medical reform, a control line of drug proportion was delimited for hospitals by the Department of National Administration. However, to formulate criteria of drug proportion in a scientific and rational approach has been a challenge, which plagued numerous medical workers. This study aims to analyze the baseline data of drug proportion and its impact factors in clinical departments, and quality control charts are applied to explore an estimating method and process for rationally formulating an index criterion of pharmaceutical management, so as to provide a reference for hospital management practice.