A blinded evaluation of privacy preserving record linkage with Bloom filters.

BACKGROUND: Privacy preserving record linkage (PPRL) methods using Bloom filters have shown promise for use in operational linkage settings. However real-world evaluations are required to confirm their suitability in practice. METHODS: An extract of records from the Western Australian (WA) Hospital Morbidity Data Collection 2011-2015 and WA Death Registrations 2011-2015 were encoded to Bloom filters, and then linked using privacy-preserving methods. Results were compared to a traditional, un-encoded linkage of the same datasets using the same blocking criteria to enable direct investigation of the comparison step. The encoded linkage was carried out in a blinded setting, where there was no access to un-encoded data or a 'truth set'. RESULTS: The PPRL method using Bloom filters provided similar linkage quality to the traditional un-encoded linkage, with 99.3% of 'groupings' identical between privacy preserving and clear-text linkage. CONCLUSION: The Bloom filter method appears suitable for use in situations where clear-text identifiers cannot be provided for linkage.

Using data linkage to monitor COVID-19 vaccination: development of a vaccination linked data repository.

The COVID-19 Vaccination Linked Data Repository (CVLDR) was established in 2021 to assist with the implementation and management of the COVID-19 vaccination program in the State of Western Australia (WA). The CVLDR contains a number of datasets including the Australian Immunisation Register, hospital admissions, emergency department attendances, notifiable infectious disease, and laboratory data. Datasets in the CVLDR are linked using a probabilistic method at the WA Department of Health. Quality assurance mechanisms have been established to identify and mitigate potential errors in the linkage. Each of the datasets has varying degrees of data quality and completeness, however most are of high standard, underpinned by legislation. The linking of the datasets within the CVLDR has allowed for increased public health utility in the immunisation program including the areas of vaccine safety, effectiveness, and coverage.

Fit for purpose - developing a software platform to support the modern challenges of data linkage in Western Australia.

The Western Australia Data Linkage System (WADLS) is maintained and operated by the WA Data Linkage Branch (DLB) at the Western Australian Department of Health. DLB has pioneered a number of data linkage innovations, including the facilitation of genealogical research via the Family Connections system and streamlined data delivery via the Custodian Administered Research Extract Server. DLB's latest innovation is a new data linkage system called "DLS3", which improves DLB's capability and capacity to handle the increasing volume and complexity of its routine operations. DLS3 was built entirely in-house and customised to meet the specific challenges that DLB has encountered throughout over twenty years of experience with a wide variety of linkages. This article describes the development and rollout of DLS3, including its design, architecture, benefits and limitations.

The custodian administered research extract server: "improving the pipeline" in linked data delivery systems.

BACKGROUND: At Western Australia's Data Linkage Branch (DLB) the extraction of linked data has become increasingly complex over the past decade and classical methods of data delivery are unsuited to the larger extractions which have become the norm. The Custodian Administered Research Extract Server (CARES) is a fast, accurate and predictable approach to linked data extraction. METHODS: The Data Linkage Branch (DLB) creates linkage keys within and between datasets. To comply with the separation principal, these keys are sent to applicable data collection agencies for extraction. Routing requests through multiple channels is inefficient and makes it hard to monitor work and predict delivery times. CARES was developed to address these shortcomings and involved ongoing consultation with the Custodians and staff of collections, plus challenges of hardware, programming, governance and security. RESULTS: The introduction of CARES has reduced the workload burden of linked data extractions, while improving the efficiency, stability and predictability of turnaround times. CONCLUSIONS: As the scope of a linkage system broadens, challenges in data delivery are inevitable. CARES overcomes multiple obstacles with no sacrifice to the integrity, confidentiality or security of data. CARES is a valuable component of linkage infrastructure that is operable at any scale and adaptable to many data environments.