Predictive risk models to identify people with chronic conditions at risk of hospitalisation
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A disproportionately large percentage of health care costs and utilisation is spent on a small fraction of the population with complex and chronic conditions (Panattoni et al., 2011). It is widely agreed that effective and accessible primary health care (PHC) is central to reducing potentially avoidable hospitalisations (PAHs) associated with chronic disease. Predictive risk modelling is one method that is used to identify individuals who may be at risk of a hospitalisation event. The Predictive Risk Model (PRM) is a tool for identifying at-risk patients, so that appropriate preventive care can be provided, to avoid both exacerbation and complications of existing conditions, and acute events that may lead to hospitalisation. This Policy Issue Review identifies a selection of currently available PRMs, focusing on those applied in a PHC setting; and examines evidence of reliability in targeting patients with complex and chronic conditions.