Ribah Adnan; Adeleh Hashemi fard; Seyyed Ehsan Saffari
Volume 20, Issue 4 , January and February 2014, , Pages 447-456
Abstract
Background: The number of hospitalization days is an important issue for the hospital managers, patients and their families. Regarding to the importance of this issue and few similar researches, this study aimed to model the number of hospitalization days for myocardial infarction (MI) patients admitted ...
Read More
Background: The number of hospitalization days is an important issue for the hospital managers, patients and their families. Regarding to the importance of this issue and few similar researches, this study aimed to model the number of hospitalization days for myocardial infarction (MI) patients admitted in Vasei hospital of Sabzevar, and to investigate its effective factors.
Material and Methods: This descriptive-analytical study was performed to model the number of hospitalization days for myocardial infarction (MI) patients admitted in Vasei hospital of Sabzevar, in 2012. By using census method, 201 patients were entered to this study and the value of the length of hospitalization as the response variable, and the value of gender, age and residence location of the patients as the independent variables are considered. The data were analyzed using an advanced and new model, zero-truncated generalized poisson regression model, and SAS9.2 software.
Results: The results showed that the average length of hospitalization of MI patients was 4.876 days in Vasei hospital. Also, it was found that one year increase in age was related to one day increase in hospitalization of the MI patients. Moreover, the regression models predicted that the average length of hospitalization for female patients was less than male patients, and the average length of hospitalization for the urban residence patients was less than those of rural residence.
Conclusions: In this study, a suitable statistical method for analyzing and modeling of hospitalization days was obtained. Because of differences in hospitalization days in different units of hospitals, use of these advanced statistical models is proposed for another hospitals and cities.