Table 1.
Training and replication/validation data sets used to develop the three models in each of the 3 index conditions.
| Model | Training | Replication/validation | Total | |
| Visual analyticala (cases/controls) | ||||
|
|
Chronic obstructive pulmonary disease (COPD) | 14,508/14,508 | 14,508/14,508 | 29,016/29,016 |
|
|
Congestive heart failure (CHF) | 25,775/25,775 | 25,775/25,775 | 51,550/51,550 |
|
|
Total hip arthroplasty/total knee arthroplasty (THA/TKA) | 8249/8249 | 8249/8249 | 16,498/16,948 |
| Classification (cases) | ||||
|
|
COPD | 10,842 | 3615 | 14,457 |
|
|
CHF | 19,254 | 6418 | 25,672 |
|
|
THA/TKA | 5257 | 1753 | 7010 |
| Prediction (cases/controls) | ||||
|
|
COPD | 21,692/117,839 | 7334/39,176 | 29,026/157,015 |
|
|
CHF | 38,728/183,093 | 12,845/61,095 | 51,573/244,188 |
|
|
THA/TKA | 12,376/255,203 | 41,44/85,049 | 16,520/340,252 |
aThe visual analytical models used 1:1 matched controls for the feature selection, and used only cases for the bipartite networks to analyze heterogeneity in readmission. The numbers shown for the visual analytical models are before removing patients with no comorbidities. The resulting cases-only data sets were used for the classification modelling as shown.