Skip to main content

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.