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Studies of the health of prisoners have proliferated in the past decade. However, relatively few studies have examined health outcomes after release from custody. As such, although >30 million people are released from prison globally each year, the health and health service experiences of this population remain poorly understood. Objectives and ApproachWell-powered longitudinal studies are essential for answering these questions but are expensive and difficult to conduct. Internationally, few such studies have been undertaken, and most suffer from either substantial and biased attrition, or recruitment bias. Cross-sectoral linkage of health and justice data circumvents some of these problems but presents its own ethical and methodological challenges. Large longitudinal studies, combining rich survey and clinical data with prospective data linkage, provide unique opportunities to examine and understand health outcomes for these highly marginalised individuals. ResultsThis presentation will describe the process and challenges of establishing the world’s largest (N=2,702) prospective study of adults released from prison: the Health After Release from Prison (HARP) cohort study. The cohort spans two Australian states and includes 538 women and 1,002 Indigenous Australians. An overview of the data collected through face-to-face surveys, medical record review, and prospective linkage with State-based health and correctional records, national Medicare and pharmaceutical records, and the National Death Index, will be provided. Some examples of how these data have been used to answer novel public health questions will be presented. The strengths and limitations of the cohort, and the applicability of this research design for other inclusion health populations, will be discussed. Conclusion/ImplicationsGiven their extreme vulnerability, understanding the health of people who cycle through prisons is important to addressing health inequalities at the population level. Novel research designs that combine prospective data linkage with other data sources provide new opportunities to examine the health of socially excluded populations.

international journal of population data science

Combining cross-sectoral, prospective data linkage with other data sources to examine health outcomes for socially excluded populations: A case study from Australia