ViewpointUse of data linkage to measure the population health effect of non-health-care interventions
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Cited by (51)
A systematic review and meta-analysis of data linkage between motor vehicle crash and hospital-based datasets
2024, Accident Analysis and PreventionRecord linkage and big data—enhancing information and improving design
2022, Journal of Clinical EpidemiologyCitation Excerpt :Expanding the number of variables available for each person makes it possible to include important covariates and outcomes not present in the original data set. Such “wide” databases are particularly relevant for integrating social and behavioral variables (for investigating the determinants of health and other outcomes) and ‘medical’ variables such as diagnoses [15]. Linkage adds value by providing missing data or correcting errors in existing data, by generating significant covariates, and by using family information to control for unmeasured variables and expand research opportunities.
Premature mortality in people affected by co-occurring homelessness, justice involvement, opioid dependence, and psychosis: a retrospective cohort study using linked administrative data
2022, The Lancet Public HealthCitation Excerpt :Administrative data typically provide extensive (or even complete) population coverage; are of low cost to obtain; and have high external validity and policy relevance. Record linkage between such datasets across different sectors can be uniquely powerful in helping understand the social and structural determinants of health and identify opportunities for intervention on cross-cutting policy issues.13 This method is especially valuable in understanding the experiences and needs of marginalised populations who might be poorly represented in primary research, for instance due to ascertainment difficulties or participation burdens that affect recruitment and retention, but who often have high levels of need for and use of public services.