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Closing the Gap in Kidney Disease: Validating the Reporting of Aboriginal And/or Torres Strait Islander Identification in a Clinical Quality Registry Using Linked Data

Overview
Journal Med J Aust
Specialty General Medicine
Date 2025 Mar 16
PMID 40089918
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Abstract

Objective: To examine the accuracy of the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA), the population-based clinical quality registry for people with kidney failure, in identifying Aboriginal and/or Torres Strait Islander people.

Design: Population-based cohort study of reporting accuracy.

Setting: New South Wales, 2006-2020.

Participants: Incident kidney failure patients.

Main Outcome Measures: Sensitivity and specificity of identification of Aboriginal and/or Torres Strait Islander people in ANZDATA compared with identification with Enhanced Reporting of Aboriginality (ERA) methods using linked health datasets.

Results: Of 11 708 patients, 693 (5.9%) were identified as Aboriginal and/or Torres Strait Islander people using ERA methods, with 484 recognised in ANZDATA. Overall ANZDATA sensitivity was 67.0% (95% CI, 63.3-70.5%), with high specificity (99.8%; 95% CI, 99.7-99.9%). Sensitivity was lowest for males (63.8%; 95% CI, 58.7-68.6), people aged under 18 years (45.0%; 95% CI, 23.1-68.5%) or over 65 years (61.7%; 95% CI, 53.8-69.2%), and those with greater socio-economic advantage (56.6%; 95% CI, 46.6-66.2%), living in major cities (53.8%; 95% CI, 48.0-59.5%) and with no comorbidities (47.7%; 95% CI, 37.0-58.6%). Aboriginal and/or Torres Strait Islander people identified in ANZDATA had lower rates of waitlisting for kidney transplantation (17.8% v 25.3%; P = 0.016) and receiving a kidney transplant (12.2% v 23.1%; P < 0.001) and a higher rate of death (56.0% v 44.5%; P = 0.004) compared with those not recognised in ANZDATA.

Conclusion: Aboriginal and/or Torres Strait Islander people were under-reported in ANZDATA. There were multiple biases in characteristics and outcomes for people identified in ANZDATA compared with those identified by ERA using linked data. This highlights the importance of data integration as a quality improvement mechanism and identifying barriers to disclosure.