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

机译:基于人口的群体预测模型对成人高医疗资源使用的外部验证

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摘要

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.
机译:预测高医疗资源用户对预防策略和医疗保健决策非常重要。我们旨在通过跨越省验证高资源用户人口风险工具(HRUPORT),这是一种预测模型,它使用人口调查数据来估计成为高医疗资源用户的5年风险。在加拿大安大略省派生和验证的模型应用于外部验证队列。 Hruport Model预测因子包括慢性病,社会人口统计学和健康行为风险因素。队列由加拿大曼尼托巴的加拿大社区健康调查组成10,504名成人(≥18岁)(2007/08和2009/10周期)。以人为本的成本计算算法应用于联系的健康管理数据库,以确定受访者的医疗保健利用率超过5年。使用C型统计数据进行评估模型拟合,用于辨别和校准图。在外部验证队列中,HRUPORT展示了强烈的歧视(C统计= 0.83),并在风险范围内校准。 HRUPORT在外部验证队列中表现良好,展示了其他司法管辖区的模型的可运输性。 Hruport对人口调查数据的使用使健康股权重点能够协助预防高医疗资源使用的决策。

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