A population-based approach to the estimation of diabetes prevalence and health resource utilisation.

AIM

This study estimated diabetes prevalence and utilisation of healthcare services in Counties Manukau using routinely collected administrative data and compared estimates with findings for three other district health boards (DHBs) in close geographic proximity.

METHOD

Records of subsidy claims for pharmaceuticals and laboratory investigations were linked to records in a national hospital admissions database to 'reconstruct' populations of four DHBs--Counties Manukau, Northland, Waitemata and Auckland. Individuals were included in reconstructed populations if they had health events recorded between January 2006 and December 2007. Diabetes cases were identified using an algorithm based on claims for monitoring tests and pharmaceuticals, as well as clinical codes for diabetes in hospital admissions.

RESULTS

Reconstructed populations were only 6% lower than census population counts indicating that the vast majority of the population use health services in a two year period. The age- and sex-standardised prevalence of diabetes was 7.1% in Counties Manukau and 5.2% in the other three DHBs combined. Prevalence of diabetes was highest amongst Māori (10.6% in women and 12.2% in men) and Pacific peoples (15.0% for women and 13.5% for men). Maori diabetes cases had the highest hospital discharge rate of any ethnic group. Community pharmaceutical prescribing patterns and laboratory test frequency were similar between diabetes cases by ethnicity and deprivation.

CONCLUSION

Estimates of diabetes prevalence using linkage of routinely collected administrative data were consistent with epidemiological surveys, suggesting that linkage of pharmaceutical and laboratory subsidy databases with hospital admissions data can be used as an alternative to traditional surveys for estimating the prevalence of some long-term conditions. This study demonstrated substantial differences in the prevalence of diabetes and in hospitalisation rates by ethnicity, but measures of community diabetes care were similar by ethnicity and deprivation.