Enablers of Cross-Sectoral Data Linkage

Main Article Content

Usha Salagame
Elizabeth Wilson
Tinny Hon
Katie Irvine


Linkage of cross-sectoral data can add value to health research but it can also present unique challenges and sensitivities.

Objectives and Approach
A case series of cross-sectoral data linkage projects supported by a population data linkage centre from 2009 to 2019 were assessed for factors that may impede or delay data sharing and linkage. Each project was assessed against these factors - classified as technical, motivational, economic, political, legal, or ethical following a systematic review by Van Panhuis et al, 2019 and jurisdictional solutions over time were documented. A multivariable regression analysis was conducted to identify predictors of overall project timeframes.

The use of linked cross-sectoral data has increasing substantially over time. A progressive decrease in identified barriers to cross-sectoral data linkage was observed. Projects early in the case series were more likely to be accompanied by ethical, political or motivational barriers and in some cases significant delay. Later projects have tended to have shorter timeframes, be characterised by more extensive longitudinal cross-sectoral linked data from a larger number of datasets, and encounter, fewer delays associated with these barriers.

Conclusion / Implications
Based on the findings of the qualitative analysis we have mapped the improvements and changes which are enablers of successful cross sectoral data linkages.

Article Details

How to Cite
Salagame, U., Wilson, E., Hon, T. and Irvine, K. (2020) “Enablers of Cross-Sectoral Data Linkage”, International Journal of Population Data Science, 5(5). Available at: https://ijpds.org/article/view/1601 (Accessed: 24 July 2024).

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