External Validation of a Population-Based Prediction Model for High Healthcare Resource Use in Adults.

Abstract

Predicting high healthcare resource users is important for informing prevention strategies and healthcare decision-making. We aimed to cross-provincially validate the High Resource User Population Risk Tool (HRUPoRT), a predictive model that uses population survey data to estimate 5 year risk of becoming a high healthcare resource user. The model, originally derived and validated in Ontario, Canada, was applied to an external validation cohort. HRUPoRT model predictors included chronic conditions, socio-demographics, and health behavioural risk factors. The cohort consisted of 10,504 adults (≥18 years old) from the Canadian Community Health Survey in Manitoba, Canada (cycles 2007/08 and 2009/10). A person-centred costing algorithm was applied to linked health administrative databases to determine respondents’ healthcare utilization over 5 years. Model fit was assessed using the c-statistic for discrimination and calibration plots. In the external validation cohort, HRUPoRT demonstrated strong discrimination (c statistic = 0.83) and was well calibrated across the range of risk. HRUPoRT performed well in an external validation cohort, demonstrating transportability of the model in other jurisdictions. HRUPoRT’s use of population survey data enables a health equity focus to assist with decision-making on prevention of high healthcare resource use.