Table 5. Importance of variables in multivariable spline regression models.
| Omitted Covariates | Rank | AIC | Difference of AIC | -2(Log Likelihood) | LRT | df | P-value |
|---|---|---|---|---|---|---|---|
| Severe Morbidity Model | |||||||
| Full model | 3207536.0 | 3207442.0 | |||||
| Comorbidity Index | 1 | 3359890.7 | 152354.7 | 3359798.7 | 152356.7 | 1 | <0.0001 |
| Hospital | 2 | 3279247.0 | 71711.0 | 3279157.0 | 71715.0 | 1 | <0.0001 |
| Age | 3 | 3213189.0 | 5653.0 | 3213103.0 | 5661.0 | 4 | <0.0001 |
| Race | 4 | 3209238.9 | 1702.9 | 3209150.9 | 1708.9 | 3 | <0.0001 |
| Insurance status | 5 | 3209068.8 | 1532.8 | 3208984.8 | 1542.8 | 5 | <0.0001 |
| Year | 6 | 3208904.8 | 1368.8 | 3208834.8 | 1392.8 | 12 | <0.0001 |
| Household income | 7 | 3207615.2 | 79.2 | 3207529.2 | 87.2 | 4 | <0.0001 |
| Hospital bed size | 8 | 3207613.0 | 77.0 | 3207523.0 | 81.0 | 2 | <0.0001 |
| Hospital Region | 9 | 3207597.6 | 61.6 | 3207509.6 | 67.6 | 3 | <0.0001 |
| Hospital Ownership | 10 | 3207586.3 | 50.3 | 3207498.3 | 56.3 | 3 | <0.0001 |
| Annualized delivery volume | 11 | 3207583.9 | 47.9 | 3207497.9 | 55.9 | 4 | <0.0001 |
| Hospital Teaching | 12 | 3207551.8 | 15.8 | 3207461.8 | 19.8 | 2 | <0.0001 |
| Hospital Location | 13 | 3207542.0 | 6.0 | 3207450.0 | 8.0 | 1 | 0.005 |
|
| |||||||
| Failure to Rescue Model | |||||||
|
| |||||||
| Full model | 26401.5 | 26307.5 | |||||
| Hospital | 1 | 29990.5 | 3589.0 | 29900.5 | 3593.0 | 1 | <0.0001 |
| Age | 2 | 26512.5 | 111.0 | 26426.5 | 119.0 | 4 | <0.0001 |
| Race | 3 | 26482.8 | 81.3 | 26394.8 | 87.3 | 3 | <0.0001 |
| Year | 4 | 26474.1 | 72.6 | 26404.1 | 96.6 | 12 | <0.0001 |
| Comorbidity Index | 5 | 26459.9 | 58.4 | 26367.9 | 60.4 | 1 | 0.0002 |
| Insurance status | 6 | 26431.0 | 29.5 | 26347.0 | 39.5 | 5 | <0.0001 |
| Household income | 7 | 26420.6 | 19.1 | 26334.6 | 27.1 | 4 | <0.0001 |
| Hospital Teaching | 8 | 26412.1 | 10.6 | 26322.1 | 14.6 | 2 | 0.0007 |
| Hospital bed size | 9 | 26407.3 | 5.8 | 26317.3 | 9.8 | 2 | 0.007 |
| Annualized delivery volume | 10 | 26405.0 | 3.5 | 26319.0 | 11.5 | 4 | 0.02 |
| Hospital Region | 11 | 26404.7 | 3.2 | 26316.7 | 9.2 | 3 | 0.03 |
| Hospital Ownership | 12 | 26401.5 | 0.0 | 26313.5 | 6.0 | 3 | 0.11 |
| Hospital Location | 13 | 26399.5 | -2.0 | 26307.5 | 0.0 | 1 | 1 |
AIC, Alkaike information criterion. LRT, likelihood ratio test. The LRT compares the full model (including all variables) with a reduced model omitting 1 variable at a time. AIC was calculated as minus twice log likelihood plus 2 degrees of freedom. The higher the AIC, the greater importance of the omitted variable.