Predicting high healthcare resource utilization in a single-payer public healthcare system: development and validation of the High Resource User Population Risk Tool (HRUPoRT)

Background — A large proportion of healthcare spending is incurred by a small proportion of the population. Population-based health planning tools that consider both the clinical and upstream determinants of high resource users (HRU) of the health system are lacking.

Objective — To develop and validate the High Resource User Population Risk Tool (HRUPoRT), a predictive model of adults that will become the top 5% of healthcare users over a 5-year period, based on self-reported clinical, sociodemographic, and health behavioral predictors in population survey data.

Research Design — The HRUPoRT model was developed in a prospective cohort design using the combined 2005 and 2007/2008 Canadian Community Health Surveys (CCHS) (N=58,617), and validated using the external 2009/2010 CCHS cohort (N=28,721). Healthcare utilization for each of the 5 years following CCHS interview date were determined by applying a person-centered costing algorithm to the linked health administrative databases. Discrimination and calibration of the model were assessed using c-statistic and Hosmer-Lemeshow (HL) χ statistic.

Results — The best prediction model for 5-year transition to HRU status included 12 predictors and had good discrimination (c-statistic=0.8213) and calibration (HL χ=18.71) in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.8171; HL χ=19.95). The strongest predictors in the HRUPoRT model were age, perceived general health, and body mass index.

Conclusions — HRUPoRT can accurately project the proportion of individuals in the population that will become a HRU over 5 years. HRUPoRT can be applied to inform health resource planning and prevention strategies at the community level.