From: Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach
 | Sensitivity / Recall | Specificity | Positive Predictive Value / Precision | Negative Predictive Value | Prevalence | Detection Prevalence | Balanced Accuracy |
---|---|---|---|---|---|---|---|
Precision at least 20% | |||||||
 Non-Response | 1.00 | 0.00 | 0.23 | 1.00 | 0.23 | 1.00 | 0.50 |
 Coercive Treatment | 0.73 | 0.78 | 0.20 | 0.97 | 0.07 | 0.26 | 0.76 |
 Long LOS | 0.98 | 0.28 | 0.20 | 0.99 | 0.16 | 0.76 | 0.63 |
 Short LOS | 0.83 | 0.37 | 0.20 | 0.92 | 0.16 | 0.66 | 0.60 |
Precision at least 25% | |||||||
 Non-Response | 0.96 | 0.15 | 0.25 | 0.93 | 0.23 | 0.87 | 0.56 |
 Coercive Treatment | 0.48 | 0.89 | 0.25 | 0.96 | 0.07 | 0.13 | 0.69 |
 Long LOS | 0.94 | 0.48 | 0.25 | 0.98 | 0.16 | 0.58 | 0.71 |
 Short LOS | 0.61 | 0.65 | 0.25 | 0.90 | 0.16 | 0.39 | 0.63 |
Precision at least 33% | |||||||
 Non-Response | 0.52 | 0.69 | 0.33 | 0.83 | 0.23 | 0.36 | 0.61 |
 Coercive Treatment | 0.23 | 0.97 | 0.33 | 0.94 | 0.07 | 0.05 | 0.60 |
 Long LOS | 0.49 | 0.82 | 0.33 | 0.90 | 0.16 | 0.23 | 0.65 |
 Short LOS | 0.41 | 0.84 | 0.33 | 0.88 | 0.16 | 0.20 | 0.62 |