Predicting patients with high risk of becoming high-cost healthcare users in Ontario (Canada).

Literature and original analysis of healthcare costs have shown that a small proportion of patients consume the majority of healthcare resources. A proactive approach is to target interventions towards those patients who are at risk of becoming high-cost users (HCUs). This approach requires identifying high-risk patients accurately before substantial avoidable costs have been incurred and health status has deteriorated further. We developed a predictive model to identify patients at risk of becoming HCUs in Ontario. HCUs were defined as the top 5% of patients incurring the highest costs. Information was collected on various demographic and utilization characteristics. The modelling technique used was logistic regression. If the top 5% of patients at risk of becoming HCUs are followed, the sensitivity is 42.2% and specificity is 97%. Alternatives for implementation of the model include collaboration between different levels of healthcare services for personalized healthcare interventions and interventions addressing needs of patient cohorts with high-cost conditions.

High-cost users of Ontario's healthcare services.

Approximately 1.5% of ontario's population, represented by the top 5% highest cost-incurring users of ontario's hospital and home care services, account for 61% of hospital and home care costs. Similar studies from other jurisdictions also show that a relatively small number of people use a high proportion of health system resources. Understanding these high-cost users (hcus) can inform local healthcare planners in their efforts to improve the quality of care and reduce burden on patients and the healthcare system. To facilitate this understanding, we created a profile of hcus using demographic and clinical characteristics. The profile provides detailed information on hcus by care type, geography, age, sex and top clinical conditions.