Systematic review of record linkage studies of mortality in ex-prisoners: why (good) methods matter
Correspondence to: Stuart A. Kinner, Melbourne School of Population Health, The University of Melbourne, Level 4, 207 Bouverie Street, Carlton VIC 3010 Australia. E-mail: firstname.lastname@example.org
World-wide, more than 30 million people move through prisons annually. Record linkage studies have identified an increased risk of death in ex-prisoners. In order to inform preventive interventions it is necessary to understand who is most at risk, when and why. Limitations of existing studies have rendered synthesis and interpretation of this literature difficult. The aim of this study was to describe methodological characteristics of existing studies and make recommendations for the design, analysis and reporting of future studies.
Systematic review of studies using record linkage to explore mortality in ex-prisoners. Based on analysis of these studies we illustrate how methodological limitations and heterogeneity of design, analysis and reporting both hamper data synthesis and create potential for misinterpretation of findings. Using data from a recent Australian study involving 42 015 ex-prisoners and 2329 observed deaths, we quantify the variation in findings associated with various approaches.
We identified 29 publications based on 25 separate studies published 1998–2011, mainly from the United Kingdom, United States and Australia. Mortality estimates varied systematically according to features of study design and data analysis. A number of common, avoidable and significant methodological limitations were identified. Substantial heterogeneity in study design, methods of data analysis and reporting of findings was observed.
Record linkage studies examining mortality in ex-prisoners show widely varying estimates that are influenced substantially by avoidable methodological limitations and reducible heterogeneity. Future studies should adopt best practice methods and more consistent methods of analysis and reporting, to maximize policy relevance and impact.