Predictors and Consequences of Homelessness: Protocol for a Cohort Study Design Using Linked Routine Data

Abstract

Background: Homelessness is a global burden, estimated to impact more than 100 million people worldwide. Individuals and families experiencing homelessness are more likely to have poorer physical and mental health than the general population. Administrative data is being increasingly used in homelessness research. Objective: The objective of this study is to combine administrative health care data and social housing data to better understand the consequences and predictors associated with being homeless. Methods: We will be linking health and social care administrative databases from Northern Ireland, United Kingdom. We will conduct descriptive analyses to examine trends in homelessness and investigate risk factors for key outcomes. Results: The results of our analyses will be shared with stakeholders, reported at conferences and in academic journals, and summarized in policy briefing notes for policymakers. Conclusions: This study will aim to identify predictors and consequences of homelessness in Northern Ireland using linked housing, health, and social care data. The findings of this study will examine trends and outcomes in this vulnerable population using routinely collected health and social care administrative data.