[Analysis on status and determinants of outpatient service utilization of rural floating population in Beijing at different residence time].

OBJECTIVE

To study the status and identify the determinants of outpatient service utilization of rural floating population in Beijing who have different accumulated residence time.

METHODS

The survey data of rural floating population health and health care services in Beijing in 2014 were used, and the migrant population aged 18 years and above were taken as the research object. Whether to use outpatient service within two weeks was taken as dependent variable, gender, age, education level, self-assessment score of socioeconomic status, accumulated residence time in Beijing, health insurance, average household income, suffering from high blood pressure or diabetes as independent variables. Logistic regression model was used to analyze the influencing factors.

RESULTS

The average age of the research object was 36.7 years, with mostly secondary education. The average accumulated residence time in Beijing was 8.4 years. The two-week prevalence rate was 10.3%, the two-week visiting rate calculated by person-time was 6.0%. The Logistic regression model suggested that, socioeconomic status, accumulated residence time and suffering from high blood pressure or diabetes were statistically significant determinants of outpatient service utilization.

CONCLUSION

The research object is a younger and less educated population, their health status is better and outpatient service utilization is lower. It is found that people who have longer accumulated residence time in Beijing have lower outpatient service utilization. This is because people with longer residence time have lower age-adjusted two-week prevalence rate. This is also because people with longer residence time have larger proportion of taking continuous measures under doctor's advice. It does not mean people with longer residence time have lower utilization of medical service. The residence time variable plays the role of proxy variable. It can solve the problem of variables' endoge-neity. At the same time, it can reflect the influence to outpatient services utilization of some determinants, which are not included in the model but varies with residence time.