Table 3 Model-based point estimates for high-cost healthcare expenditurea using logistic models – univariate analysis (excluding Malaysia)
Factor | Odds ratio | 95% CI | P value |
|---|---|---|---|
Age, per 10-year increment | 1.04 | 0.99, 1.08 | 0.0925 |
Sex, male versus female | 1.18 | 1.06, 1.33 | 0.0038 |
Income (versus quintile 5) | < 0.0001 | ||
Quintile 1 | 0.45 | 0.19, 1.06 | |
Quintile 2 | 0.76 | 0.67, 0.85 | |
Quintile 3 | 0.97 | 0.85, 1.11 | |
Quintile 4 | 0.80 | 0.53, 1.20 | |
Health insurance, yes versus no | 1.02 | 0.90, 1.16 | 0.7074 |
Residence, rural versus non-rural | 1.02 | 0.92, 1.12 | 0.7516 |
Smoker (versus never) | 0.2418 | ||
Current | 0.92 | 0.83, 1.03 | |
Former | 1.02 | 0.89, 1.15 | |
Disease history, yes versus no | 1.15 | 1.04, 1.28 | 0.0068 |
Hospitalization in the 3 months prior to index event, yes versus no | 1.37 | 1.16, 1.62 | 0.0002 |
Dependence degree before index event, none versus some | 1.74 | 1.48, 2.05 | < 0.0001 |
Index event medical management, invasive versus non-invasive | 4.62 | 3.78, 5.64 | < 0.0001 |
Type of hospital (versus UGH) | 0.0030 | ||
Regional/community/rural hospital | 0.92 | 0.72, 1.17 | |
Non-UGH | 1.13 | 1.01, 1.27 | |
Other type of hospital/clinic | 1.24 | 1.09, 1.40 | |
Number of beds | 1.00 | 1.00, 1.00 | 0.5995 |
Length of stay | 1.04 | 1.03, 1.05 | < 0.0001 |
Country (versus China) | 0.8569 | ||
Hong Kong | 1.00 | 0.64, 1.56 | |
India | 1.09 | 0.97, 1.23 | |
Singapore | 0.91 | 0.48, 1.70 | |
South Korea | 1.00 | 0.72, 1.36 | |
Thailand | 1.00 | 0.72, 1.38 | |
Vietnam | 0.96 | 0.65, 1.43 |