Addressing the challenges of cross‐jurisdictional data linkage between a national clinical quality registry and government‐held health data

Abstract

Objective: To describe the challenges of obtaining state and nationally held data for linkage to a non-government national clinical registry. Methods:We reviewed processes negotiated to achieve linkage between the Australian Stroke Clinical Registry (AuSCR), the National Death Index, and state held hospital data. Minutes from working group meetings, national workshop meetings, and documented communications with health department staff were reviewed and summarised.Results: Time from first application to receipt of data was more than two years for most state data-sets. Several challenges were unique to linkages involving identifiable data from a nongovernment clinical registry. Concerns about consent, the re-identification of data, duality of data custodian roles and data ownership were raised. Requirements involved the development of data flow methods, separating roles and multiple governance and ethics approvals. Approval to link death data presented the fewest barriers.

Use of data linkage to improve communicable disease surveillance and control in Australia: existing practices, barriers and enablers

“…Barriers associated with cross‐jurisdictional linkage identified by others include issues with timely data access, project governance and administration, as well as data security, privacy, infrastructure and capability 10,14,48–50 . We identified additional barriers including a lack of perceived need, system factors and resources.…”

“…Barriers associated with cross-jurisdictional linkage identified by others include issues with timely data access, project governance and administration, as well as data security, privacy, infrastructure and capability. 10,14,[48][49][50] We identified additional barriers including a lack of perceived need, system factors and resources. Jurisdictions with small populations reported regularly using unlinked disparate data to fill surveillance gaps, which precluded a need for data linkage methodologies to be used for data cleansing purposes.…”

Protocol for evaluation of enhanced models of primary care in the management of stroke and other chronic disease (PRECISE)

“…GP: General Practitioner overall reliability and quality of the recorded data, including diagnostic information. Nevertheless a few variables are consistent across datasets and these datasets provide a reliable indication of the number of ED presentations and the primary diagnosis [19].…”

“…While the depth of information collected varies between states, all states comply with requirements for the Admitted Patient National Minimum Data Set, enabling crossjurisdictional comparisons of hospitalisation data [18]. Coding of information by trained clinical coders using standardised International Statistical Classification of Diseases and Related Health Problems, Australian Modification (ICD-AM) and Australian Classification of Health Interventions (ACHI) codes and coding rules also ensures consistency [19].…”

case study in distributed team science in research using electronic health records

“…Challenges arising from using data from multiple jurisdictions, i.e. legal issues, organisation capacity, financial cost, separation of roles and data ownership have been partially addressed in the US, Australia and other European countries (13,14,15,16). An infrastructure in Australia was proposed for cross-jurisdictional health data linkage research across states to improve the quality of population research data (17).…”