Objective: By analyzing the gap of hospitalization service among floating population covered by different medical insurance in Jiangsu Province, this paper aimed to understand the current situation of hospitalized health service utilization (HHSU) among floating population, and to provide policy suggestions for improving HHSU of floating population with different health insurance. Methods: The data of this study were obtained from "the National Dynamic Monitoring Survey of Floating Population in 2014". A total of 12,000 samples of floating population in Jiangsu Province were selected. 57.15% for men and 42.85% for women; 46.95% for those under 30 years old, 39.67% for 30 to 45 years old, 13.38% for over the age of forty-five. Using descriptive statistical analysis, chi-square test, exploratory factor analysis, logistic regression and stepwise multiple linear regression, the paper analyzed the difference of HHSU of floating population with different medical insurance in 2014. This study divided basic medical insurance into 3 categories: MIUE (Medical Insurance of Urban Employee), other medical insurances (including new rural cooperative medical system and the medical insurance for urban residents) and no medical insurance. Results: The hospitalization rate of floating population with MIUE (89.95%) was higher than the rate of floating population with other medical insurances (74.76%) and the gap is 15.19%. It was also higher than the rate of floating population with no medical insurance (67.57%) and the gap is 22.38%. (chi-square = 24.958, p = 0.000). 15.34% of floating population with MIUE spent more than 1600 dollars during hospitalization. It was lower than floating population with other medical insurances (16.19%) and no medical insurance (21.62%). The gaps respectively were 0.85 and 6.28% (chi-square = 10.000, p = 0.040). There existed significant differences among hospitalization medical expenses that floating population with different basic medical insurances spent. (chi-square = 225.206, p = 0.000) The type of basic medical insurance had statistical significance on whether the patients were hospitalized (p = 0.003) and whether they were hospitalized (p = 0.014). Logistic regression analysis results showed that "Social structure" (Education, Hukou, Insurance status and Work status) were significantly associated with Should be hospitalized but not and "Education" were significantly associated with Inpatient facilities selection. The stepwise multiple linear regression results presented that "Demography" and "Floating area" influenced In-hospital medical cost and "Social structure" and "Gender" influenced Reimbursement of in-hospital medical cost. Conclusion: Medical insurance type affects the hospitalization health service utilization of floating population, including Should be hospitalized but not and Reimbursement of in-hospital medical cost.