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Table 5 The influence of IC on output and input variables

From: Can integrated care improve the efficiency of hospitals? Research based on 200 Hospitals in China

Dependent variable

Estimate (Std.Error)

t-value

Pr( >|t|)

95%CI

Output variable

 ND

19,179 (8,766)

2.188

0.034*

[1,511.749, 36,845.56]

 UD

229,088 (86,403)

2.651

0.011*

[54,955.40, 403,221.4]

 NIA

19,246 (8,763)

2.196

0.033*

[1,584.254, 36,906.88]

 NOV

237,400 (153,958)

1.542

0.130

[− 72,882.971, 547,682.4]

 NEV

53,604 (21,171)

2.532

0.015*

[10,936.58, 96,271.92]

 AVFP

− 2,470 (2,300)

− 1.074

0.289

[− 7,105.227, 2,164.915]

 ARH

361,001 (258,554)

1.396

0.170

[− 160,081.04, 882,083.0]

 NS

6,432 (3,689)

1.743

0.088

[− 1,003.135, 13,866.44]

Input variable

 NP

165.70 (71.34)

2.322

0.025*

[21.912, 309.480]

 NAMS

− 1.2416 (1.217)

− 1.020

0.313

[− 3.694, 1.211]

 NN

344.4 (141.4)

2.435

0.019*

[59.401, 629.469]

 NOE

129.34 (64.04)

2.020

0.050*

[0.265, 258.412]

 NB

649.3 (236.4)

2.747

0.009**

[172.932, 1,125.676]

 OO

334,981 (262,901)

1.274

0.209

[− 194,861.68, 864,823.9]

  1. Significance codes: ‘***’ ≤ 0.001; ‘**’ ≤ 0.01; ‘*’ ≤ 0.05