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. 2022 Mar 9;24(3):e31684.
doi: 10.2196/31684.

A National Network of Safe Havens: Scottish Perspective

Chuang Gao  1 , Mark McGilchrist  1 , Shahzad Mumtaz  1 , Christopher Hall  1 , Lesley Ann Anderson  2 , John Zurowski  3 , Sharon Gordon  4 , Joanne Lumsden  4 , Vicky Munro  4 , Artur Wozniak  4 , Michael Sibley  5 , Christopher Banks  5 , Chris Duncan  6 , Pamela Linksted  6 , Alastair Hume  7 , Catherine L Stables  8 , Charlie Mayor  9 , Jacqueline Caldwell  5 , Katie Wilde  4 , Christian Cole  1 , Emily Jefferson  1
Affiliations

A National Network of Safe Havens: Scottish Perspective

Chuang Gao et al. J Med Internet Res. .

Abstract

For over a decade, Scotland has implemented and operationalized a system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk of unauthorized reidentification. In this paper, a perspective is provided on the state-of-the-art Scottish Safe Haven network, including its evolution, to define the key activities required to scale the Scottish Safe Haven network's capability to facilitate research and health care improvement initiatives. A set of processes related to EHR data and their delivery in Scotland have been discussed. An interview with each Safe Haven was conducted to understand their services in detail, as well as their commonalities. The results show how Safe Havens in Scotland have protected privacy while facilitating the reuse of the EHR data. This study provides a common definition of a Safe Haven and promotes a consistent understanding among the Scottish Safe Haven network and the clinical and academic research community. We conclude by identifying areas where efficiencies across the network can be made to meet the needs of population-level studies at scale.

Keywords: Safe Haven; data governance; electronic health records.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Model of Scottish Safe Havens. Researchers have access to the Safe Haven application process after data governance approvals. Safe Haven staff link and deidentify data and make them available in the analytic platform for researchers to analyze. ETL: extract, transform, and load.
Figure 2
Figure 2
The Safe Haven project workflow describes the stages a Safe Haven takes to support a typical project. (1) Data discovery and research feasibility—users will initialize the application on the data governance aspects; (2) (optionally) index and link a research data set or administrative or clinical data set for hosting at a given analytic platform; (3) cohort building the selected or agreed data from Safe Haven data sets; (4) the transfer of extracted data to an analytic platform after the data governance has been checked; a user analyzes analytic platform data set. The project data set is archived at the end of the project.
Figure 3
Figure 3
Data indexing and linking services in Scotland. CHI: community health index; COPD: chronic obstructive pulmonary disease; NHS: National Health Service.
Figure 4
Figure 4
Safe Haven data repository networks. Upper row from left to right: electronic Data Research and Innovation Service, Health Informatics Center, and Glasgow Safe Haven. The lower row from left to right: Lothian, DataLoch, and Grampian Data Safe Haven Safe Haven. BI: Business Intelligence and Informatics; DaSH: Grampian Data Safe Haven; eDRIS: electronic Data Research and Innovation Service; HIC: Health Informatics Center; NHS: National Health Service; PHS: Public Health Scotland; RDMP: Research Data Management Platform; SH: Safe Haven.
See this image and copyright information in PMC

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