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Table 3 Model-based point estimates for high-cost healthcare expenditurea using logistic models – univariate analysis (excluding Malaysia)

From: Predictors of high-cost hospitalization in the treatment of acute coronary syndrome in Asia: findings from EPICOR Asia

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  
  1. UGH University general hospital, CI Confidence interval
  2. ahigh cost defined as the top quintile within a country