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- W2037842918 abstract "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." @default.
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- W2037842918 date "2014-02-26" @default.
- W2037842918 modified "2023-10-13" @default.
- W2037842918 title "Predicting Patients with High Risk of Becoming High-Cost Healthcare Users in Ontario(Canada)" @default.
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- W2037842918 doi "https://doi.org/10.12927/hcpol.2014.23710" @default.
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