Table 4 Model-based point estimates for high-cost healthcare expenditurea using logistic models – multivariate analysis (excluding Malaysia)
Factor | Odds ratio | 95% CI | P value |
|---|---|---|---|
Age, per 10-year increment | 1.10 | 1.05, 1.16 | < 0.0001 |
Sex, male versus female | 1.17 | 1.02, 1.33 | 0.0224 |
Income (versus quintile 5) | < 0.0001 | ||
Quintile 1 | 0.43 | 0.15, 1.19 | |
Quintile 2 | 0.76 | 0.67, 0.86 | |
Quintile 3 | 0.96 | 0.83, 1.11 | |
Quintile 4 | 0.74 | 0.45, 1.23 | |
Health insurance, yes versus no | 1.11 | 0.89, 1.38 | 0.3686 |
Disease history, yes versus no | 1.25 | 1.11, 1.41 | 0.0002 |
Hospitalization in the 3 months prior to index event, yes versus no | 1.48 | 1.23, 1.77 | < 0.0001 |
Dependence degree before index event, none versus some | 1.96 | 1.60, 2.40 | < 0.0001 |
Index event medical management, invasive versus non-invasive | 5.48 | 4.34, 6.92 | < 0.0001 |
Type of hospital (versus UGH) | 0.0016 | ||
Regional/community/rural hospital | 1.74 | 1.25, 2.41 | |
Non-UGH | 1.13 | 0.99, 1.29 | |
Other type of hospital/clinic | 0.97 | 0.79, 1.19 | |
Length of stay | 1.06 | 1.04, 1.06 | < 0.0001 |
Country (versus China) | < 0.0001 | ||
Hong Kong | 1.92 | 1.04, 3.53 | |
India | 2.54 | 1.98, 3.25 | |
Singapore | 1.58 | 0.77, 3.24 | |
South Korea | 1.21 | 0.76, 1.95 | |
Thailand | 1.52 | 1.05, 2.20 | |
Vietnam | 0.90 | 0.57, 1.42 |