Expenditure patterns and utilisation of high-cost patients
| Spending category | Number of studies |
| (Inpatient) hospital care | 3115–19 22–25 27–30 32–39 60 66–68 73 75 78 79 82 85 |
| Subacute care/postacute care services rehabilitation | 119 15 22 27 30 35 38 39 66 67 75 |
| Hospitalisations/admission/ patient days/length of stay | 1717–19 23 26 35 36 39 60 68 73 74 77–79 81 85 |
| Emergency department | 1219 26 29 35–38 60 73 77 78 85 |
| Outpatient (physician) visits | 1319 27 34–37 39 65 73 77 82 83 85 |
| Long-term care | 1115 16 22 30 39 66 67 70 73 78 83 |
| Mental health | 1017 18 22 36 38 61 67 73 83 85 |
| Physician services | 1315 18 27 35–37 68 73 74 81–83 85 |
| Intensive care unit | 2 78 17 |
| Prescription drugs | 1617 19 23 30 35–37 62 65 67 68 75 77–79 85 |
| Persistency | |
| Subsequent use | 1316 20 21 23 29 31–33 62 67 72 82 83 |
| Prior use | 521 32 58 60 65 |
| Persistent users | 2115 16 20–23 26 29 31–33 37 57 58 60 62 65 67 72 82 83 |
| Prediction of high-cost patients* | 1622 25 58–60 63–65 68–70 77 79 80 83 84 |
*An in-depth discussion of prediction models for high costs is beyond the scope of the article (though individual predictors are used throughout the paper). Generally, diagnosis-based models outperform prior cost models, and combinations accurately predict high-cost patients. Besides, comorbidity indices also accurately predict high-cost patients, and self-reported health data meaningfully improved existing models.