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How well do NSW hospital data identify cases of heart failure?

Jane Robertson, Sallie-Anne Pearson and John R Attia
Med J Aust 2014; 200 (1): . || doi: 10.5694/mja13.10207
Published online: 20 January 2014

To the Editor: Large administrative datasets are increasingly being used for health research; validation studies are critical to understanding data quality, in particular that coding accurately reflects the clinical condition under study. We compared heart failure coding and the associated comorbidity burden using the New South Wales Admitted Patient Data Collection (APDC) with the clinical data in patient medical records (the “gold standard”). The APDC contains about 26 million records generated since 2000 of all public and private hospital admissions, with reasons for admission and clinical diagnosis.


  • 1 University of Newcastle, Newcastle, NSW.
  • 2 Faculty of Pharmacy, University of Sydney, NSW.



Competing interests:

No relevant disclosures.

  • 1. Robertson J, McElduff P, Pearson SA, et al. The health services burden of heart failure: an analysis using linked population health data-sets. BMC Health Serv Res 2012; 12: 103.
  • 2. Lee DS, Donovan L, Austin PC, et al. Comparison of coding of heart failure and comorbidities in administrative and clinical data for use in outcomes research. Med Care 2005; 43: 182-188.
  • 3. Teng TH, Finn J, Hung J, et al. A validation study: how effective is the Hospital Morbidity Data as a surveillance tool for heart failure in Western Australia? Aust N Z J Public Health 2008; 32: 405-407.
  • 4. Sundararajan V, Henderson T, Perry C, et al. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol 2004; 57: 1288-1294.
  • 5. Powell H, Lim LL, Heller RF. Accuracy of administrative data to assess comorbidity in patients with heart disease: an Australian perspective. J Clin Epidemiol 2001; 54: 687-693.

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