ObjectivesTo survey the features of reservation bed and investigate the factors of hospital operation which may affect the patient loyalty of reservation bed in large general hospital. MethodsAll patients who reserved bed before July 2013 in hospital service center of a large general hospital were investigated by questionnaire in telephone and collected the basic data. Measurement index was designed to conclude the characteristics of patient loyalty of reservation bed in different departments. Multivariate statistical analysis was used to analyze the influence factors of patient loyalty. ResultsIn the large general hospital, significant difference was found in patient loyalty of reservation bed in different departments. The diversity was mainly impacted by average waiting time of admission, cancelling waiting length, loyalty of patient inside the province, average length of stay, readmission rate on the day of discharge. ConclusionLarge general hospital should pay more attention to dynamic monitoring and disclosure of supply and demand information of bed resources, to improve the management of beds resources and optimize reservation system, to elevate patient's loyalty of reservation bed in hospital.
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.
Patient priority evaluation has been studied and applied abroad for a long time, which is a mature theory and widely used in practice now. This article uses the priority, patients, waiting list and criteria as keywords to search Wiley Inter Science, Web of Science, Scopus Pub Med, The Cochrane Library, Science Direct, Springer, and Jstor database (searching time is up to December 2017), to collect relevant indicators for patient admission priority evaluation. In addition, relevant citations and grey literature were searched, and experts from relevant fields in China were consulted to obtain more comprehensive research literature. On this basis, this article describes the concept of patient admission priority evaluation, and describes the meanings of the indicators and the countries of application from the three dimensions of clinical indicators, expected results, and social factors. It is considered that the research and implementation of the evaluation of the priority of patient admission has been relatively many. However, there are only a few related researches in the country and without unity. There is no systematic patient-related priority evaluation. It is necessary to use foreign mature theory research to establish a hospital admission priority evaluation system suitable for China’s national conditions.