TABLE 3—
Adjusted Association of Access to Care and Quality of Care by Insurance Type in 2013 in Arkansas, Kentucky, and Texas
| Private (Ref) |
Medicaid |
Medicare |
Uninsured |
|||||
| Outcome | AOR | PP, % | AOR (95% CI) | PP, % | AOR (95% CI) | PP, % | AOR (95% CI) | PP, % |
| Access to outpatient care | ||||||||
| No personal doctor | 1 | 35.5 | 0.82 (0.52, 1.30) | 31.8 | 0.82 (0.55, 1.24) | 31.7 | 3.07 (2.24, 4.19) | 59.0 |
| Difficulty accessing primary care appointment | 1 | 13.4 | 1.13 (0.65, 1.96) | 14.7 | 0.64 (0.36, 1.16) | 9.3 | 2.11 (1.41, 3.15) | 23.3 |
| Difficulty accessing specialist appointment | 1 | 11.1 | 1.78 (1.00, 3.17) | 17.3 | 1.26 (0.71, 2.24) | 13.3 | 2.01 (1.30, 3.10) | 18.9 |
| ED use | ||||||||
| ED as usual location of care | 1 | 4.4 | 0.43 (0.16, 1.20) | 2.0 | 1.40 (0.57, 3.45) | 5.9 | 4.54 (2.46, 8.40) | 15.9 |
| Use of ED when doctor not available | 1 | 9.4 | 1.53 (0.79, 2.96) | 13.4 | 1.21 (0.67, 2.16) | 11.0 | 2.32 (1.41, 3.81) | 18.4 |
| Affordability and cost of care | ||||||||
| Delayed care because of cost | 1 | 27.7 | 0.87 (0.54, 1.38) | 25.2 | 0.69 (0.45, 1.06) | 21.6 | 3.79 (2.72, 5.28) | 54.9 |
| Delayed medication because of cost | 1 | 30.1 | 1.03 (0.65, 1.64) | 30.7 | 0.73 (0.49, 1.10) | 25.0 | 2.45 (1.76, 3.40) | 46.8 |
| > $500 out-of-pocket spending in past year | 1 | 38.3 | 0.26 (0.16, 0.43) | 15.7 | 0.41 (0.28, 0.60) | 22.1 | 0.81 (0.59, 1.12) | 34.2 |
| > $1000 out-of-pocket spending in past year | 1 | 24.7 | 0.28 (0.16, 0.52) | 9.2 | 0.48 (0.32, 0.73) | 14.3 | 1.04 (0.74, 1.47) | 25.3 |
| Delayed paying bills because of medical costs | 1 | 35.4 | 0.79 (0.52, 1.22) | 31.0 | 0.87 (0.60, 1.26) | 32.7 | 1.90 (1.39, 2.58) | 48.4 |
| Self-reported fair or poor quality of care | 1 | 40.7 | 1.18 (0.79, 1.76) | 44.5 | 0.75 (0.51, 1.10) | 34.5 | 2.28 (1.67, 3.12) | 59.7 |
Note. AOR = adjusted odds ratios from multivariate logistical regression (private insurance was the reference group for all AORs); CI = confidence interval; ED = emergency department; PP = predicted probability, calculated from the logistic regression estimates by using Stata’s MARGINS command with default settings, which holds all covariates at their actual values. The sample size was n = 2765. Models controlled for insurance type, age, gender, marital status, education level, race/ethnicity, income, rural versus urban residence, cell phone use, political affiliation, self-reported fair or poor health, presence of chronic conditions, and state of residence.