Table 6 Results of the multivariate regression analysis of the impact of physician dispensing (PD) on physician services
From: Physician drug dispensing in Switzerland: association on health care expenditures and utilization
Target variable | Number of GP visits | Number of specialist visits | Probability of a physician visit | Physician expenditures if > 0 |
|---|---|---|---|---|
Specification | Glm, log link negative binom. fam. | Glm, log link negative binom. fam. | Probit | Glm, log link gamma family |
PD | 1.05 (0.008)*** | 1.065 (0.01)*** | 0.444 (0.014)*** | 1.02 (0.087)* |
Age | 1.002 (0)*** | 0.997 (0)*** | −0.004 (0)*** | 1.003 (0)*** |
Gender = m | 0.955 (0.006)*** | 0.826 (0.008)*** | −0.12 (0.013)*** | 0.95 (0.008)*** |
PPO-contract | 1.043 (0.012)*** | 1.001 (0.017) | 0.072 (0.025)** | 0.989 (0.014) |
Telemedicine contract | 1 (0.011) | 1.055 (0.015)*** | 0.065 (0.02)** | 1.022 (0.013) |
HMO contract | 1.032 (0.008)*** | 0.988 (0.011) | 0.114 (0.016)*** | 0.981 (0.009)* |
High deductible | 0.882 (0.008)*** | 0.864 (0.01)*** | −0.14 (0.015)*** | 0.921 (0.009)*** |
Cost in previous year (log) | 1.06 (0.002)*** | 1.153 (0.003)*** | 0.649 (0.053)*** | 1.447 (0.022)*** |
Nursing home stay | 1.334 (0.016)*** | - | 0.044 (0.003)*** | 1.068 (0.002)*** |
Outpatient hospital vistis 1-5 | 0.889 (0.016)*** | 1.559 (0.026)*** | 0.339 (0.063)*** | 0.777 (0.018)*** |
Outpatient hospital vistis >5 | 1.313 (0.01)*** | 1.365 (0.015)*** | 0.406 (0.021)*** | 1.313 (0.012)*** |
Inpatient stay in hospital | 1.303 (0.021)*** | 1.259 (0.029)*** | 0.314 (0.055)*** | 1.238 (0.026)*** |
Prescriptions psychiatrists | 0.409 (0.03)*** | 4.687 (0.362)*** | 0.238 (0.048)*** | 3.488 (0.091)*** |
Prescriptions cardio-/angiologists | 0.278 (0.006)*** | 4.445 (0.091)*** | −0.017 (0.102) | 2.815 (0.221)*** |
Prescriptions gynaeologists | 0.405 (0.01)*** | 10.156 (0.266)*** | 0.012 (0.029) | 1.707 (0.033)*** |
Prescriptions other specialists | 0.347 (0.004)*** | 5.582 (0.072)*** | 0.211 (0.02)*** | 2.25 (0.027)*** |
Agricultural municipalities | 0.821 (0.198) | 1.45 (0.554) | 0.153 (0.411) | 1.06 (0.309) |
Industrial and tertiary municipalities | 0.921 (0.221) | 1.533 (0.583) | 0.114 (0.075) | 1.011 (0.048) |
Rural commuting municipalities | 0.903 (0.217) | 1.579 (0.601) | 0.071 (0.077) | 1.054 (0.051) |
Touristic municipalities | 0.742 (0.189) | 1.49 (0.587) | 0.094 (0.154) | 1.123 (0.117) |
Affluent municipalities | 0.959 (0.229) | 1.948 (0.739) | 0.228 (0.067)*** | 1.221 (0.052)*** |
Periurban municipalities | 0.893 (0.213) | 1.645 (0.624) | 0.062 (0.066) | 1.091 (0.046)* |
Suburban municipalities | 0.918 (0.219) | 1.733 (0.657) | 0.138 (0.064)* | 1.123 (0.046)** |
Urban centers | 1.011 (0.242) | 1.942 (0.736) | 0.34 (0.064)*** | 1.249 (0.052)*** |
22 pharmaceutical cost groups | all coefficients strongly positive | all coefficients strongly positive | all coefficients strongly positive | all coefficients strongly positive |