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Longitudinal patterns of spending enhance the ability to predict costly patients: a novel approach to identify patients for cost containment

With rising health spending, predicting costs is essential to identify patients for interventions. We used group-based trajectory modeling to classify patients by their spending patterns over a 1-year period and to assess the ability of models to predict patients in the highest spending trajectory and the top 5% of annual spending using prior-year predictors. We identified all fully insured adult members enrolled in a large US nationwide insurer and used medical and prescription data from 2009 to 2011. Among 998,651 patients, in the best-performing model, prediction was strong for patients in the highest trajectory group. Trajectory modeling may be a useful way to predict costly patients that could be implementable by payers to improve cost-containment efforts.

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