Table 5.
Trend test of association between the outpatient visit types and ER or hospital inpatient services utilization among middle-aged and elderly Chinese participants.
| Outpatient Visit Types | ER Visits or Not a n = 7544 |
Hospitalization or Not n = 7544 |
Number of Hospitalizations b n = 1535 |
Length of Hospitalization Days n = 1535 |
||||
|---|---|---|---|---|---|---|---|---|
| Adjusted OR (95% CI) |
Average Marginal Effect (95% CI) |
Adjusted OR (95% CI) |
Average Marginal Effect (95% CI) |
Adjusted IRR (95% CI) |
Average Marginal Effect (95% CI) |
Adjusted IRR (95% CI) |
Average Marginal Effect (95% CI) |
|
| The total number of outpatient visits = 1 | n = 3957 | n = 788 | ||||||
| Ref: Hospital outpatient visits | ||||||||
| Primary care outpatient visits | 0.131 *** (0.084, 0.204) |
−0.065 *** (−0.079, −0.052) |
0.577 *** (0.481, 0.692) |
−0.076 *** (−0.101, −0.051) |
1.096 (0.871, 1.380) |
0.086 (−0.132, 0.305) |
0.828 ** (0.740, 0.927) |
−2.199 ** (−3.503, −0.896) |
| The total number of outpatient visits = 2 | n = 1706 | n = 335 | ||||||
| Ref: Hospital outpatient visits | ||||||||
| Primary care outpatient visits | 0.154 *** (0.073, 0.327) |
−0.048 *** (−0.070, −0.026) |
0.724 * (0.547, 0.958) |
−0.046 *** (−0.086, −0.005) |
0.821 (0.591, 1.140) |
−0.200 (−0.532, 0.132) |
0.967 (0.806, 1.160) |
−0.371 (−2.353, 1.611) |
| The total number of outpatient visits ≥ 3 | n = 1881 | n = 412 | ||||||
| Ref: Hospital outpatient visits | ||||||||
| Primary care outpatient visits | 0.173 *** (0.083, 0.359) |
−0.042 *** (−0.063, −0.020) |
0.684 * (0.506, 0.923) |
−0.059 *** (−0.107, −0.011) |
0.733 (0.511, 1.053) |
−0.263 (−0.595, 0.069) |
0.974 (0.834, 1.137) |
−0.312 (−2.140, 1.515) |
* p < 0.05, ** p < 0.01, *** p < 0.001. a There was a linear trend of a significant increase in the odds of ER visits as the total number of outpatient visits increased by trend test. b There was a linear trend of a significant decrease in the number of hospitalizations as the total number of outpatient visits increased by trend test. All models were adjusted for economic region, PGDP, current residence, self-reported health status, ADL limitations, IADL limitations, depression, age group, sex, marital status, education, work status, smoking, drinking, number of chronic diseases, frequency of social activity, medical insurance status, PCE, number of caregivers, and living arrangement.