ObjectivesBased on the historical data of inpatients, a logistic regression model was established. It aimed to identify the influencing factors of patient's admission scheduling decisions and compare them with the actual scheduling rules, so as to discover the differences and deficiencies.MethodsWe extracted data of outpatients and inpatients in Department of Respiration in West China Hospital of Sichuan University from January 1st, 2016 to December 31st, 2016, and standardized the original dataset. We established the binary multivariate logistic regression model through R software and ‘glm’ package.ResultsThe analysis of multi-factor logistic regression showed that the effect of the five variables (type of medical insurance, time of registration, waiting time, type of disease and admission priority) on patient schedule was statistically significant.ConclusionsThe logistic regression model constructed in this study has a good effect on patient planning, which is helpful to provide decision support for admission schedule through identification factors.