Table 5.
Variable importance for the predictive models (frequent users 3).
| Variable | LR | GBM | NN | RF1 | RF2 |
|---|---|---|---|---|---|
| Age | |||||
| 18–34 | Ref | Ref | Ref | 562.0 | 271.1 |
| 35–54 | 7.0 | 5.1E−4 | 3.5 | ||
| 55–64 | 9.0 | 1.1E−3 | 2.7 | ||
| 65–74 | 7.5 | 4.4E−4 | 3.6 | ||
| 75–84 | 2.5 | 4.0E−3 | 2.8 | ||
| ≥ 85 | 3.2 | 8.5E−3 | 3.7 | ||
| PPDIP | |||||
| Regular | Ref | Ref | Ref | 465.6 | 226.3 |
| GIS | 13.2 | 7.5E−3 | 4.2 | ||
| Not admissible | 8.5 | 1.1E−2 | 3.9 | ||
| LRFA | 17.0 | 1.4E−2 | 4.7 | ||
| CCI | |||||
| 0 | Ref | Ref | Ref | 882.1 | 439.6 |
| 1–2 | 19.8 | 1.7E−2 | 4.1 | ||
| 3–4 | 21.3 | 1.3E−2 | 5.0 | ||
| ≥ 5 | 24.7 | 1.6E−2 | 4.3 | ||
| PV | |||||
| ≤ 1 | Ref | Ref | Ref | 5255.2 | 2621.2 |
| 2–3 | 74.3 | 0.2 | 3.7 | ||
| 4 | 66.2 | 0.1 | 5.3 | ||
| 5 | 61.7 | 0.1 | 6.0 | ||
| ≥ 6 | 96.4 | 0.3 | 5.3 | ||
| COPD | 24.4 | 2.6E−2 | 5.1 | 475.9 | 234.7 |
| Injury | 5.1 | 2.2E−3 | 3.7 | 205.3 | 98.3 |
| SMD | 5.4 | 2.2E−3 | 4.8 | 182.0 | 88.5 |
| CMD | 12.0 | 1.8E−2 | 2.9 | 266.9 | 130.8 |
| CNCP | 11.6 | 5.7E−3 | 3.3 | 180.1 | 86.7 |
| Alcohol | 4.3 | 2.0E−3 | 5.3 | 164.6 | 79.7 |
| Drugs | 8.1 | 2.9E−3 | 4.8 | 228.4 | 111.2 |
The higher the value, the higher the importance (relative to a model).
LR logistic regression, GBM gradient boosting machine, NN neural network, RF random forests (1: binary outcome, 2: continuous outcome).