Variation in the use of medicines by ethnicity during 2006/07 in New Zealand: a preliminary analysis

Aim To describe variations in dispensing of specific medication groups by ethnicity in New Zealand, adjusting for health need. Method Preliminary linkage of dispensings of prescription medicines in 2006/07 to age/disease burden proxies of health need for Maori, Pacific peoples (Pasifika)-who are mostly of Samoan, Tongan, Niuean, or Cook Islands descent-in New Zealand, and non-Maori/non-Pasifika. These disease burden proxies combine differences in prevalence, age, morbidity, and mortality. Variations were disaggregated by patients being first dispensed medicines ('access') versus subsequent dispensings ('persistence'). Results Initially, overall age-adjusted incidence of 'scripts' (prescriptions dispensed) to Maori was similar to that of non-Maori. There were differences in therapeutic coverage between Maori and Pasifika, for example greater use of asthma medicines in Maori. However, further adjustments linking with disease burden showed marked variance for a number of diseases. Differences in dispensing included areas of high health need such as heart disease, infections, diabetes, mental health and respiratory disease. Maori had 19-37% lower dispensings overall than non-Maori, with a net difference of nearly 1 million scripts. Maori were both less likely to access medicines, and then after first dispensing had fewer subsequent scripts. Patterns for Pasifika appeared similar, although needsadjusted analysis is awaited for this population. Conclusions Once adjusting for need, there was variable but sizeable differences in medicines dispensed to Maori compared with non-Maori, and likely differences for Pasifika populations. There are however important limitations to this preliminary analysis. Crude and age-standardised metrics may be poor predictors of needs-adjusted gaps in medicines use. In this analysis, solely age-standardised rates tended to underestimate differences once adjusting for burden of disease; future analyses of prescribing patterns should consider better adjusting for disease burden.