title: Data quality of the Australia and New Zealand Dialysis and Transplant Registry: a pilot audit.
abstract: OBJECTIVE
  Most clinical registries in Australia, including the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA), do not audit submitted data. Inaccurate data can bias registry analysis. This study aimed to audit data submitted to ANZDATA from a single region.
  
  
  METHODS
  A retrospective audit of individual haemodialysis patient data recorded by ANZDATA at 31 December 2009 was completed by nephrologists in a blinded fashion. Original data were recorded by nursing staff. Patients received treatment at a public hospital, two affiliated satellite haemodialysis units, and three private haemodialysis units.
  
  
  RESULTS
  Fifty-one audits were completed of a total 175 patients (29.1%) undertaking haemodialysis in 2009. Primary renal disease was correct in 86.3% (95%CI: 74.3-93.2), although errors in type of glomerulonephritis were common. Date of first dialysis (± 1-month error margin) was correct for 93.6%. Creatinine at first dialysis (± 10% error margin) was correct in 74.4%. Baseline comorbidity accuracy included: peripheral vascular disease (sensitivity 36.4% (95%CI: 24.6-50.1), specificity 82.8% (95%CI: 70.2-90.7)), ischaemic heart disease (sensitivity 69.2% (95%CI: 55.6-80.2), specificity 88.0% (95%CI: 76.3-94.3)), chronic lung disease (sensitivity 25.0% (95%CI: 15.2-38.3), specificity 93.6% (95%CI: 83.4-97.7)), diabetes (sensitivity 86.4% (95%CI: 74.4-93.2), specificity 96.6% (95%CI: 87.5-99.1)), cerebrovascular disease (sensitivity 75.0% (95%CI: 61.7-84.8), specificity 95.3% (95%CI: 85.8-98.6)), and ever smoked (sensitivity 83.3% (95%CI: 70.3-91.4), specificity 71.4% (95%CI: 57.3-82.3)). Non-melanoma skin cancer was under-reported and inaccurate.
  
  
  CONCLUSIONS
  Data accuracy was favourable compared with other renal registry validation studies. Data accuracy may be improved by education and training of collectors. A larger audit is necessary to validate ANZDATA.
authors.affiliation: Department of Renal Medicine, Nambour General Hospital, Nambour, Queensland, Australia; The University of Queensland, Sunshine Coast Clinical School, Nambour General Hospital, Nambour, Queensland, Australia.
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Gray
authors.forename: Kumar
authors.initials: K
authors.lastname: Mahadevan
authors.forename: Victoria K
authors.initials: VK
authors.lastname: Campbell
authors.forename: Euan P
authors.initials: EP
authors.lastname: Noble
authors.forename: Chris M
authors.initials: CM
authors.lastname: Anstey
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001315:Australia / Q000453:epidemiology; D015897:Comorbidity; D005260:Female; D006779:Hospitals, Public / Q000592:standards; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy*; D016030:Kidney Transplantation / Q000592:standards*; D008297:Male; D008485:Medical Audit; D008875:Middle Aged; D009520:New Zealand / Q000453:epidemiology; D010865:Pilot Projects; D011331:Private Practice / Q000592:standards; D011786:Quality Control; D012042:Registries / Q000592:standards*; D006435:Renal Dialysis / Q000592:standards*; D015203:Reproducibility of Results; D012189:Retrospective Studies
keywords: ANZDATA; audit; data quality; dialysis; kidney; registry