Estimating the population size of persons contending with homelessness using electronic health records

G. Dong, Kenneth Moselle, Stanley Robertson, Patrick E. Brown, Laura L E Cowen
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Abstract

The majority of attempts to enumerate the homeless population rely on point-in-time or shelter counts, which can be costly and inaccurate. As an alternative, we use electronic health records from the Vancouver Island Health Authority, British Columbia, Canada from 2013 to 2022 to identify adults contending with homelessness based on their self-reported housing status. We estimate the annual population size of this population using a flexible open-population capture–recapture model that takes into account (1) the age and gender structure of the population, including aging across detection occasions, (2) annual recruitment into the population, (3) behavioural-response, and (4) apparent survival in the population, including emigration and incorporating known deaths. With this model, we demonstrate how to perform model selection for the inclusion of covariates. We then compare our estimates of annual population size with reported point-in-time counts of homeless populations on Vancouver Island over the same time period, and find that using data extracts from electronic health records gives comparable estimates. We find similarly comparable results using only a subset of interaction data, when using only ER interactions, suggesting that even if cross-continuum data is not available, reasonable estimates of population size can still be found using our method.
利用电子健康记录估算无家可归者的人口数量
对无家可归者进行统计的大多数尝试都依赖于时间点统计或收容所统计,这可能成本高昂且不准确。作为一种替代方法,我们使用加拿大不列颠哥伦比亚省温哥华岛卫生局 2013 年至 2022 年的电子健康记录,根据他们自我报告的住房状况来识别无家可归的成年人。我们使用灵活的开放式人口捕获-再捕获模型估算该人口的年度人口规模,该模型考虑到:(1)人口的年龄和性别结构,包括不同检测场合的老龄化;(2)人口的年度招募;(3)行为反应;(4)人口的表面存活率,包括人口迁出和已知死亡人数。利用该模型,我们演示了如何进行模型选择以纳入协变量。然后,我们将对年度人口数量的估计与同期温哥华岛无家可归人口的时点统计进行比较,发现使用电子健康记录中的数据提取可以得出相似的估计结果。我们还发现,如果只使用 ER 交互数据的子集,也能得出类似的可比结果,这表明即使无法获得跨连续数据,使用我们的方法也能找到合理的人口规模估算值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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