An Experience-Driven Framework for Overcoming Challenges in Cross-Agency Data Linkage

This work was presented at the International Population Data Linkage Network Conference 2026 - 16 July 2026 in Rotterdam

Cross-agency data sharing collaborations have proven [BS1.1]crucial to ensure the most effective usage of often limited funding resources. Through, delivering these resources to the right people in the right circumstances at the right time. Despite the cumbersome and often time-consuming process of setting those collaborations up. The data linkage part of those collaborations does not need to be time consuming. If it is well planned ahead of time.

Here we present two vastly different data linkage experiences [BS2.1]and lessons learned, from our Trusted Research Environment, supporting cross-agency social housing and health projects. Collaborations between health board and local authorities or charities, that set out to improve the health and well-being of vulnerable groups while simultaneously reducing the pressure on the local health system. Both projects required data linkage between the collaboration partners datasets, an identified group of vulnerable people and a variety of property details and metrics. Those datasets are inherently not homogenised nor set up for cross-sector data linkage.
One project required a time intensive multi-stage mixed method linkage approach, that combined direct match linkage across multiple variable fields with fuzzy matching techniques and manual verification. Where the other project was able to utilize a unique property identifier, that only recently had been introduced into the data from the national health care provider.
Whilst we recognise, that a single unifying unique identifier is not always available for data linkage across different agencies. We will provide a framework of recommendations that should be considered prior to the data sharing that can facilitate a smooth data linkage process.