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Appendix Table 3.
Full regression results for the effects of multiple cost control methods on the probability of not getting prescription drugs due to cost.
| Variable | Coefficient |
|---|---|
| Intercept | 0.09 |
| State has 2 or 3 cost control methods (compared with 0 or 1) | 0.10** |
| State has 4 or 5 cost control methods (compared with 0 or 1) | 0.18* |
| Age 35-44 | 0.02 |
| Age 45-54 | 0.04 |
| Age 55-64 | -0.05 |
| Female | 0.11* |
| Family income 100-199% of poverty | 0.005 |
| Family income 200-299% of poverty | -0.01 |
| Family income 300-399% of poverty | -0.11* |
| Family income 400% of poverty or higher | -0.12* |
| Black | 0.05 |
| Hispanic | -0.01 |
| Other race | 0.004 |
| Interview not conducted in English | -0.06 |
| Excellent, very good health | -0.11* |
| Good health | -0.05 |
| 1 chronic condition | 0.09* |
| 2 or more chronic conditions | 0.21* |
| Married | 0.03 |
| Children in family | 0.02 |
| Covered by Medicaid only part year | 0.13* |
| Person enrolled in HMO | -0.01 |
| Percent of Medicaid beneficiaries in managed care (state-level) | -0.0002 |
| Number of physicians per 1,000 persons (county) | -0.02* |
| Northeast region | -0.05 |
| Midwest region | -0.02 |
| West region | 0.03 |
| Large MSA residence (greater than 200,000 persons) | -0.03 |
| Small MSA residence (less than 200,000 persons | 0.04 |
* p < .05
** p < .10
Note: Effects of individual cost-control methods are shown in Table 6 (all based on separate regressions). Effects of other independent variables are similar across all regression models.
