Abstract
In recent years publications have called for increased use of administrative data for research; predicted that use would rise; and discussed possible ethical parameters for that use. This paper describes the novel combination of three administrative datasets to create a population cohort for environmental health research, and investigates the potential use of a national health register as a total population denominator.
We matched a national health register (the New Zealand national health index or NHI) to Quotable Value New Zealand Ltd (QV) nationwide residential dwelling data, and to hospital admissions data, to create a national matched cohort with health outcomes for the period 2000 - 2006. We then compared population distribution and hospitalisation rates by gender, age, ethnic group and Census Area Unit-based socio-economic deprivation index across the Census, NHI and matched cohort populations.
The NHI population was 23% larger than the Census. Differences between the NHI and Census were most marked in those aged over 90 years; with ethnicity unknown or an unassigned Census area unit; and in Asian Peoples aged under 30 years. The match rate between QV and NHI data was 70%. There were further differences between the NHI and matched cohort populations, particularly for rural areas and older age groups. Compared to Census-based rates, NHI and cohort-based hospitalisation rates were higher in those aged 75 and over, differed by ethnicity, and had less socio-economic gradient.
The NHI was larger than the Census due to record duplication and entries for people residing overseas remaining on file under New Zealand addresses. NHI and QV matching was incomplete due to NHI address data being poor quality or not suitable for matching. To better approximate true hospitalisation rates, studies using the NHI as a cohort should exclude those aged over 90 years; or with ethnic group or Census area unit unknown. Cohort hospitalisation rates should also be adjusted for differences from the Census, particularly the lower hospitalisation rates for those aged 75 and over, and other differences by age, ethnic group and socio-economic deprivation.