Factors affecting patient length of stay: An assessment in terms of Turkish health system

The increase in the average of life expectancy, differentiations of disease types, new technological developments and the increase in demand for health care services have caused to the increase in costs of health care services in many countries. Curative health care services require higher cost than the other health care services. One of the main component of costs of curative health care services is the length of stay (LOS). LOS can vary according to a wide range of factors, including patient characteristics, health care providers? characteristics and health system characteristics. Although a comprehensive analysis of LOS has important implications in various aspects of health services, it is noticed that LOS has been neglected mostly in both theoratical studies and practice of health care management in Turkey. The main purpose of this study is to identify factors related to LOS in Turkey. A retrospective analysis of 2.255.836 patients admitted to private, university, foundation university and other (municipality, association and foreigner/minority hospitals) hospitals which have an agreement with Social Security Institution (SSI) in Turkey, from January 1, 2010, until the December 31, 2010, was examined. Patient?s data were taken from MEDULA (National Electronic Invoice System) and SPSS 18.0 was used to perform statistical analysis. In this study t-test, one way anova and multinomial logistic regression are used to determine variables that may affect to LOS. The average LOS of patients was 3,93 days (SD = 5,882). LOS showed a statistically significant difference according to all independent variables used in the study (age, gender, type of social security, disease type, type of hospitalization, presence or absence of comorbidity, type and number of surgery, season of hospitalization, hospital ownership/bed capacity/ geographical region/residental area/type of service, patient share). According to the results of the multinomial lojistic regression analysis, LOS was negatively affected in terms of gender, presence or absence of comorbidity, geographical region of hospital and was positively affected in terms of age, season of hospitalization, hospital bed capacity/ownership/type of service/residental area.Anahtar Kelimeler: Health care services, length of stay, multinomial logistic regression