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Table 3 Results of logit models of decision to refer/not refer

From: The association between general practitioner participation in joint teleconsultations and rates of referral: a discrete choice experiment

Variables

Model 1a

Model 1b

Intercept

−1.062***

−13.12***

 

(0.371)

(4.503)

Nevus

5.008***

5.901***

 

(0.474)

(0.737)

Melanoma

5.549***

5.409***

 

(0.598)

(0.680)

Psoriasis

1.746***

1.761***

 

(0.279)

(0.358)

Waiting time

0.000184

0.0000828

 

(0.000938)

(0.00118)

Distance

−0.00403

−0.00286

 

(0.00325)

(0.00411)

Pressure

0.0671

0.219

 

(0.246)

(0.316)

Age

 

0.606**

  

(0.245)

Male

 

−0.186

  

(0.650)

Distance hospital

 

0.0400**

  

(0.0162)

Distance private

 

−0.0293

  

(0.0214)

List size

 

0.0000163

  

(0.0000227)

Telemedicine

 

−1.911***

  

(0.603)

Special interest

 

−1.149**

  

(0.526)

Health status: bad

 

0.423

  

(0.481)

Health status: good

 

−1.698

  

(1.377)

Age-squared

 

−0.00680**

  

(0.00293)

Observations

721

473

AIC

514.1

327.2

Log likelihood

−249.1

−145.6

Chi-squared

152.5***

95.37***

Hosmer & Lemeshow Chi-squared

12.22

13.84*

% pred. correctly

82.25%

86.47%

Area under ROC

0.8763

0.9215

  1. ***significant at 1% level; **significant at 5% level; *significant at 10%. Dependent variable is a dummy variable indicating whether a referral was made. Base categories for explanatory dummy variables: Need – Keratosis; Pressure – No; Telemedicine – No; Special interest – No; Health status – Neither good nor bad; standard errors in parenthesis.