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Table 3 Regression of CRS technical inefficiency scores against exploratory variables

From: Analysis of factors influencing technical efficiency of public district hospitals in KwaZulu-Natal province, South Africa

Variables

Coefficient

Std. Err.

Z

P-value

95% CI

Lower limit

Upper limit

Model 1 (CRSTE)

 Catchment population (ref: "≤100,000")

      100 001–200 000

0.258903

0.144427

1.79

0.087

− 0.04062

0.558426

      > 200 000

0.093021

0.150426

0.62

0.543

− 0.21894

0.404985

 Level of facility (ref: Small "50–150 beds")

      Medium (150–300 beds)

− 0.26425

0.142891

− 1.85

0.078

− 0.56059

0.032083

      Large (300–600 beds)

0.11657

0.177804

0.66

0.519

− 0.48531

0.252173

 Location

0.017687

0.187435

0.09

0.926

− 0.37103

0.406403

 Outpatient/doctor

0.000224

0.000135

1.65

0.113

− 5.7E−05

0.000504

 Inpatient/doctor

− 0.00068

0.000252

− 2.69

0.013*

− 0.0012

− 0.00015

 Ratio of beds to doctor

0.070006

0.045213

1.55

0.136

− 0.02376

0.163772

 Outpatient/nurse

− 0.00981

0.004968

− 1.97

0.061

− 0.02011

0.000493

 Inpatient/nurse

0.008444

0.007086

1.19

0.246

− 0.00625

0.02314

 Ratio of beds to nurse

− 0.8223

1.188997

− 0.69

0.496

− 3.28813

1.643527

 Average length of stay

0.027841

0.040708

0.68

0.501

− 0.05658

0.112263

 Inpatient bed utilization rate

− 0.00191

0.003553

− 0.54

0.596

− 0.00928

0.005457

 Outpatient/inpatient days

0.231625

0.613416

0.38

0.709

− 1.04052

1.503772

 Exp. per PDE

− 0.0003

0.000123

− 2.44

0.023*

− 0.00056

− 4.5E−05

 OPD not referred

− 6.30E−06

5.59E-06

− 1.13

0.272

− 1.8E−05

5.29E−06

 Cons.

2.33511

1.187342

1.97

0.062

− 0.12729

4.797507

 Sigma

0.040635

0.012537

  

0.02143

0.077053

Number of observations = 38

Log likelihood = − 0.8818

Chi-square (χ2) = 48.82

P-value = 0.0001

  1. *significant at P < 0.05