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Table 2 The generalised estimating equation analysis of medical expenses

From: Medical expenditure for patients with hemophilia in urban China: data from medical insurance information system from 2013 to 2015

ParameterBStd.Error95% wald confidence Internalhypothesis test
LowerUpperwald chi-squaredfp-value
intercept5169.0882572.454127.17010,211.0064.03810.044
[region = 1]1289.574979.440− 630.0933209.2411.73410.188
[region = 2]1700.0351349.644− 945.2194345.2881.58710.208
[region = 3]0b      
[gender = 1]− 544.5421937.713− 4342.3893253.3050.07910.779
[gender = 2]0b      
age−400.917651707.808− 1788.195986.3600.32110.571
[types of BMI = 1]360.9771220.132− 2030.4372752.3910.08810.767
[types of BMII = 2]0b      
[grades of medical institution = 0]159.418759.276− 1328.7341647.5710.04410.834
[grades of medica linstitution = 1]9223.120#######−13,906.49032,352.7300.61110.434
[grades of medica linstitution = 2]1986.0241177.259−321.3614293.4102.84610.092
[grades of medical institution = 3]0b      
[types of medical service = 1]− 5085.887772.286− 6599.540− 3572.23343.36910.000
[types of medical service = 2]0b      
reimbursement ratio27.51810.7566.43748.6006.54610.011
scale69,869,737.205