Applying algorithms to national administrative data sets provides a readily available method for estimating the prevalence of a chronic condition such as gout, where diagnosis and drug treatment are relatively specific for this disease. We have demonstrated high gout prevalence in the entire Aotearoa New Zealand population, particularly among Māori and Pacific people.

Acute rheumatic fever (ARF) and its sequela, rheumatic heart disease (RHD), have largely disappeared from high-income countries. However, in New Zealand (NZ), rates remain unacceptably high in indigenous Māori and Pacific populations. The goal of this study is to identify potentially modifiable risk factors for ARF to support effective disease prevention policies and programmes. A case-control design is used. Cases are those meeting the standard NZ case-definition for ARF, recruited within four weeks of hospitalisation for a first episode of ARF, aged less than 20 years, and residing in the North Island of NZ. This study aims to recruit at least 120 cases and 360 controls matched by age, ethnicity, gender, deprivation, district, and time period. For data collection, a comprehensive pre-tested questionnaire focussed on exposures during the four weeks prior to illness or interview will be used. Linked data include previous hospitalisations, dental records, and school characteristics. Specimen collection includes a throat swab (Group A Streptococcus), a nasal swab (Staphylococcus aureus), blood (vitamin D, ferritin, DNA for genetic testing, immune-profiling), and head hair (nicotine). A major strength of this study is its comprehensive focus covering organism, host and environmental factors. Having closely matched controls enables the examination of a wide range of specific environmental risk factors.

The amount of variability in clinical activity that can definitively be linked to the practitioner in primary care is similar to that recorded in studies of the secondary sector. With primary care doctors increasingly being grouped into larger professional organisations, we can expect application of multi-level techniques to the analysis of clinical activity in primary care at different levels of organisational complexity.

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