Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Research Protocols

Date Submitted: Sep 2, 2022
Date Accepted: Apr 5, 2023

The final, peer-reviewed published version of this preprint can be found here:

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

Mitchell E, O’Reilly D, O’Donovan D, Bradley D

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

JMIR Res Protoc 2023;12:e42404

DOI: 10.2196/42404

PMID: 37498664

PMCID: 10415948

Predictors and consequences of homelessness: cohort study design using linked routine data

  • Eileen Mitchell; 
  • Dermot O’Reilly; 
  • Diarmuid O’Donovan; 
  • Declan Bradley

ABSTRACT

Background:

Homelessness is believed to cause serious health and social consequences, yet there are practical and methodological challenges for service providers and policy-makers who wish to quantify these effects. This protocol outlines our approach to a planned study that combines administrative healthcare data and social housing data to characterize health and social care-related consequences and predictors of homelessness in Northern Ireland.

Objective:

This study will aim to identify predictors and consequences of homelessness in Northern Ireland using linked housing and health and social care data.

Methods:

This retrospective cohort study will use a nested matched cohort design to (a) identify predictors of experiencing homelessness and (b) to compare health outcomes among people who were registered as homeless to those who have not been registered as homeless. We will use anonymized social housing and healthcare data in the regional trusted research environment in Northern Ireland, United Kingdom. We will conduct descriptive analyses to inspect trends in homelessness, and investigate risk factors for key outcomes. To create control groups for our primary analysis, we will use propensity score matching of controls to cases. As a sensitivity analysis, we will also conduct self-controlled case series analysis.

Results:

n/a

Conclusions:

This study will aim to identify predictors and consequences of homelessness in Northern Ireland using linked housing and health and social care data. The ability to identify this population in administrative data is critical in the assessment and management of the health and social care needs, and monitoring the progress of such efforts. Clinical Trial: n/a


 Citation

Please cite as:

Mitchell E, O’Reilly D, O’Donovan D, Bradley D

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

JMIR Res Protoc 2023;12:e42404

DOI: 10.2196/42404

PMID: 37498664

PMCID: 10415948

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.