A case study of the Secure Anonymous Information Linkage (SAIL) Gateway: a privacy-protecting remote access system for health-related research and evaluation.

With the current expansion of data linkage research, the challenge is to find the balance between preserving the privacy of person-level data whilst making these data accessible for use to their full potential. We describe a privacy-protecting safe haven and secure remote access system, referred to as the Secure Anonymised Information Linkage (SAIL) Gateway. The Gateway provides data users with a familiar Windows interface and their usual toolsets to access approved anonymously-linked datasets for research and evaluation. We outline the principles and operating model of the Gateway, the features provided to users within the secure environment, and how we are approaching the challenges of making data safely accessible to increasing numbers of research users. The Gateway represents a powerful analytical environment and has been designed to be scalable and adaptable to meet the needs of the rapidly growing data linkage community.

Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health.

BACKGROUND: The necessity of aggregating health data over areas can impede our understanding of health determinants. METHODS: We demonstrate the possibility of creating anonymous links between individual residences and the local environment using digital map data and a data linkage system. RESULTS: Digital map data were used successfully to anonymously link 1.3 million addresses to the local environment. The data linkage system allows detailed environment data surrounding each residence to be linked both to each resident therein and to their medical records. CONCLUSIONS: Local environment data specific to each house can be effectively and anonymously linked to the population registered with the National Health Service. Our integrated approach potentially enables flexible fine-scale, large-area observational studies of communities and health.

Protecting health data privacy while using residence-based environment and demographic data.

Spatial analyses of environment and health data are often made using point address data, despite the risk of identity disclosure. We describe how geospatial environment and non-spatial health data can be linked anonymously, thereby maintaining geoprivacy. High resolution environment data and population density were calculated specific to each residence. Population density and environment data were anonymously linked to individual-level demographic data using a split file method and residential anonymous linking fields. Access to the nearest park or playground was calculated for each residence; children in deprived areas have increased access compared to those in affluent areas. This method has the potential to be used to evaluate natural experiments and complex environmental health interventions.