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Table 4 Hierarchy of the linear regression for medical expenses

From: Impacts of the medical arms race on medical expenses: a public hospital-based study in Shenzhen, China, during 2009–2013

Variables

Model 1

Model 2

Model 3

Model 4

Outpatient fee per visit

Inpatient Fee per Capita

Outpatient fee per visit

Inpatient fee per capita

Total amount of medical equipment worth over 1 million yuan

0.200**

(0.001)

0.086*

(0.048)

  

Total cost of medical equipment worth over 1 million yuan

  

0.300***

(0.001)

0.095**

(0.040)

Number of beds

0.000***

(0.000)

0.009

(0.007)

0.000

(0.000)

0.004

(0.008)

Government’s financial investment/total hospital revenue

− 0.012

(0.050)

2.279

(2.914)

− 0.010

(0.049)

2.187

(2.903)

GDP per capita in the district

0.000

(0.000)

0.000

(0.000)

0.000

(0.000)

0.000

(0.000)

Aging rate (over age 60) rate in the district

− 9.221

(9.785)

− 341.840

(574.678)

− 10.288

(9.339)

− 363.529

(561.070)

Healthcare market competition in the district

0.102***

(0.025)

1.307

(1.417)

0.111***

(0.024)

1.539

(1.421)

Hospital type

− 0.339***

(0.128)

9.350

(9.948)

− 0.372***

(0.129)

8.287

(9.858)

Hospital grade

0.260*

(0.137)

23.552**

(10.205)

0.239*

(0.137)

22.689**

(10.102)

Cons

1.448***

(0.348)

35.090*

(20.894)

1.501***

(0.333)

36.434*

(20.426)

Level 3—District

 Cons

− 1.337***

(0.309)

2.403***

(0.543)

− 1.422***

(0.329)

2.345***

(0.579)

Level 2—Hospital

 Cons

− 0.854***

(0.103)

3.548***

(0.099)

− 0.839***

(0.103)

3.540***

(0.099)

Level 1—Year

 Cons

− 1.624***

(0.046)

2.429***

(0.046)

− 1.655***

(0.046)

2.427***

(0.046)

N

300

300

300

300

  1. ***p < 0.001, **p < 0.01, *p < 0.05, +p < 0.1