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Table 7 Generalized linear regression analysis of potential factors influence medical costs

From: High admission rates and heavy inpatient service costs of urban tuberculosis patients in eastern China

Variables Total costs Total OOP costs
β SE P-value β SE P-value
Intercept 8.944 0.286 0.000 7.359 0.411 0.000
UEBMI 0.398 0.238 0.094 0.771 0.341 0.024
URBMI 0.350 0.241 0.146 0.924 0.347 0.008
Student 0a    0a   
Male 0.003 0.072 0.972 −0.041 0.103 0.691
Female 0a    0a   
Mental labourer 0.281 0.229 0.220 0.473 0.330 0.151
Manual labourer 0.247 0.125 0.048 0.390 0.180 0.030
Retire 0.219 0.125 0.079 0.069 0.180 0.699
Unknown 0a    0a   
New cases 0.164 0.091 0.069 0.138 0.130 0.288
Previously treated cases 0a    0a   
Native 0.038 0.061 0.531 0.064 0.088 0.468
Migration in China 0a    0a   
Negative cases −0.200 0.061 0.001 −0.064 0.088 0.465
Positive cases 0a    0a   
Age − 0.003 0.002 0.107 −0.008 0.003 0.005
Scale 0.111b 0.013   0.229b 0.027  
  1. Dependent variable:total costs/total OOP costs
  2. Model (intercept): health insurance, gender, occupation, patient category, residence, sputum smear test and age
  3. a Set to zero because this parameter is redundant
  4. b Maximum likelihood estimate