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Table 5 Panel 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 5

Model 6

Model 7

Model 8

Model 9

Outpatient drug fee per visit

Outpatient examination fee per visit

Inpatient drug fee per capita

Inpatient treatment fee per capita

Inpatient examination fee per capita

Total amount of medical equipment worth over 1 million yuan

0.000

(0.001)

0.000**

(0.000)

0.004

(0.017)

0.008

(0.019)

0.001

(0.001)

Number of beds

0.000

(0.000)

0.000

(0.000)

0.001

(0.002)

− 0.005*

(0.002)

0.000*

(0.000)

Government’s financial investment/total hospital revenue

− 0.001

(0.031)

− 0.026*

(0.016)

1.519

(1.013)

− 0.350

(1.136)

0.003

(0.068)

GDP per capita in the district

0.000

(0.000)

0.000

(0.000)

− 0.000

(0.000)

0.000

(0.000)

0.000

(0.000)

Aging rate (over age 60) in the district

− 4.402

(6.963)

− 2.434

(1.578)

17.065

(158.525)

− 52.389

(151.848)

− 1.996

(6.302)

Healthcare market competition in the district

0.067***

(0.015)

0.009

(0.008)

0.492

(0.501)

0.415

(0.571)

− 0.015

(0.034)

Hospital type

− 0.185

(0.114)

− 0.044*

(0.025)

9.194***

(2.360)

3.014

(2.186)

0.557***

(0.132)

Hospital grade

0.269**

(0.118)

0.014

(0.026)

4.781***

(2.491)

5.159**

(2.319)

0.428***

(0.133)

Cons

0.689***

(0.252)

0.285***

(0.057)

2.552

(5.682)

6.107

(5.423)

0.813***

(0.232)

Level 3—District

 Cons

− 1.905***

(0.457)

− 3.313***

(0.384)

1.348***

(0.364)

1.342***

(0.348)

− 1.536***

(0.276)

Level 2—Hospital

 Cons

− 0.927***

(0.099)

− 2.550***

(0.112)

2.061***

(0.107)

1.954***

(0.108)

− 0.784***

(0.100)

Level 1—Year

 Cons

− 2.118***

(0.046)

− 2.737***

(0.046)

1.393***

(0.046)

1.526***

(0.046)

− 1.294***

(0.046)

N

300

300

300

300

300

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