Factors associated with length of stay in hospital among the elderly patients using count regression models

Background: Aging is a major challenge not only for high-income countries but also for middle- and low-income countries. The length of stay (LOS) in hospitals is one of the major concerns of elderly patients, which should be taken into consideration. We aimed to investigate the factors affecting LOS of elderly patients admitted to a referral hospital of northeast of Iran. Methods: A relatively large population of 7130 hospitalized elderly patients (over 65 years old) who referred to Ghaem hospital (Mashhad, Iran) from March 20, 2016 to March 19, 2017 were selected. The demographic and medical records data of patients were extracted from the hospital database. Univariate analyses as well as count regression models, including poisson regression and negative binomial regression, were conducted to assess the influential factors on the LOS and the number of admissions considered for potential confounders using SAS software. In this study α =0.05 was considered as statistically significant. Results: The mean age of participants was 76.57±7.29 years, and 54.8% were male and 45.2% were female. The mean LOS was 8.11±13.97 days and the mean number of admissions 1.5±1.73 times. The negative binomial regression model had better fitness than Poisson's model. Findings indicated that emergency hospitalization (RR: 0.21), admission to the CCU (RR: 0.33), and male gender (RR: 0.92) were statistically reducing factors for LOS among elderly patients, respectively. Discharge status (deceased, RR: 1.50), patients with diagnosis of injuries and poisoning (RR: 1.34), and native residence (RR: 1.10) were factors that statistically increased the length of stay among hospitalized elderly patients. Conclusion: LOS in hospitals is affected by multiple factors and the negative binomial regression model is a better statistical method for estimating the influencing factors.