Matthew Page1, Emma H Wyeth2, Ari Samaranayaka3, Bronwen McNoe4, Rachael Walker5, John Schollum6, Mark Marshall7, Robert Walker6, Sarah Derrett8. 1. Medical Student, Ngāi Tahu Māori Health Research Unit, Department of Preventive and Social Medicine, University of Otago, Dunedin. 2. Senior Lecturer-Māori Health and Director, Ngāi Tahu Māori Health Research Unit, Department of Preventive and Social Medicine, University of Otago, Dunedin. 3. Senior Research Fellow, Department of Preventive and Social Medicine, University of Otago, Dunedin. 4. Research Fellow, Department of Preventive and Social Medicine, University of Otago, Dunedin. 5. Nurse Practitioner, Hawke's Bay District Health Board, Hawke's Bay and PhD candidate, University of Sydney, Sydney, Australia. 6. Nephrologist, Department of Medicine, University of Otago, Dunedin. 7. Nephrologist, Department of Renal Medicine, Middlemore Hospital, Auckland, and School of Medicine, University of Auckland, Auckland. 8. Associate Professor and Director, Injury Prevention Research Unit, Department of Preventive and Social Medicine, University of Otago, Dunedin.
Abstract
AIM: Sustained health inequities are experienced by indigenous and minority populations. Accurate ethnicity data are fundamental to healthcare planning and provision and monitoring of health outcomes to address such inequities. This study investigated the accuracy of ethnicity data in a large clinical registry of end-stage kidney disease patients (the Australia and New Zealand Dialysis and Transplant Registry; ANZDATA) and hospital-based patient clinical records compared with self-reported ethnicity data collected in the 'Dialysis Outcomes in those aged ≥65 years' (DOS65+) study. METHODS: Self-reported ethnicity data were collected, as per national guidelines, from DOS65+ participants and compared with ethnicity data recorded for these participants in ANZDATA and hospital-based patient clinical records. Ethnicities were first prioritised and then grouped into one of the following: European, Māori, Pacific, Asian and Other. Cohen's Kappa statistics were calculated to determine overall non-random agreement. Concordances for ethnic group categories were calculated. RESULTS: There was high concordance between self-reported ethnicity and ethnicity recorded in both the ANZDATA (κ=0.95) and hospital-based patient clinical records (κ=0.93). Concordances for ethnic group categories between datasets ranged from 86% to 100%. CONCLUSION: Our findings show a high level of agreement for ethnicity recorded for end-stage kidney disease patients between the three datasets, suggesting robust data to support health planning and research. Despite this, alignment of ethnicity data collection methods, as per national guidelines, should occur for all databases used for research and clinical practice in New Zealand.
AIM: Sustained health inequities are experienced by indigenous and minority populations. Accurate ethnicity data are fundamental to healthcare planning and provision and monitoring of health outcomes to address such inequities. This study investigated the accuracy of ethnicity data in a large clinical registry of end-stage kidney diseasepatients (the Australia and New Zealand Dialysis and Transplant Registry; ANZDATA) and hospital-based patient clinical records compared with self-reported ethnicity data collected in the 'Dialysis Outcomes in those aged ≥65 years' (DOS65+) study. METHODS: Self-reported ethnicity data were collected, as per national guidelines, from DOS65+ participants and compared with ethnicity data recorded for these participants in ANZDATA and hospital-based patient clinical records. Ethnicities were first prioritised and then grouped into one of the following: European, Māori, Pacific, Asian and Other. Cohen's Kappa statistics were calculated to determine overall non-random agreement. Concordances for ethnic group categories were calculated. RESULTS: There was high concordance between self-reported ethnicity and ethnicity recorded in both the ANZDATA (κ=0.95) and hospital-based patient clinical records (κ=0.93). Concordances for ethnic group categories between datasets ranged from 86% to 100%. CONCLUSION: Our findings show a high level of agreement for ethnicity recorded for end-stage kidney diseasepatients between the three datasets, suggesting robust data to support health planning and research. Despite this, alignment of ethnicity data collection methods, as per national guidelines, should occur for all databases used for research and clinical practice in New Zealand.
Authors: Bronwen McNoe; John B W Schollum; Sarah Derrett; Mark R Marshall; Andrew Henderson; Ari Samaranayaka; Robert J Walker Journal: BMC Nephrol Date: 2019-04-23 Impact factor: 2.388
Authors: Elizabeth Butcher; Robert Walker; Emma Wyeth; Ari Samaranayaka; John Schollum; Sarah Derrett Journal: Can J Kidney Health Dis Date: 2022-04-26
Authors: Reshma Shettigar; Ari Samaranayaka; John B W Schollum; Emma H Wyeth; Sarah Derrett; Robert J Walker Journal: Can J Kidney Health Dis Date: 2021-06-13