Background
Determinants of length of stay (LOS) on hospital wards is important in many planning, policy, and decision problems. Furthermore, LOS is an important parameter for cost containment, and health managers maintain a strong focus on monitoring and reducing hospital LOS. In addition to being costly, excess LOS also expose the patient to unnecessary risk of in-hospital complications.
Methods
We analysed a data set of N = 1922 admissions to the stroke unit (SU) at Akershus University Hospital between February 2012 and March 2013, which contains high quality variables pertaining to each stay, including patient characteristics and municipality residency. We explored regression models with (log-)LOS as the dependent variable, economic and demographic characteristics of the patients’ municipalities as the main predictors, controlling for several patient and admission parameters, like sex, age, and time of arrival.
Results
The analyses showed that the municipality variables ‘share of inhabitants below the age of 67 years who are female’ and ‘nurse full time equivalents per 1000 inhabitants’ were negatively associated with LOS.
Conclusions
Although a regression model cannot prove causal relations, a reasonable interpretation is that the given predictors capture some aspects of a municipality’s capacity for home care, which makes it possible for the SU to discharge patients relatively early.