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Background: Researching access to health services, and ways to improve equity, frequently requires researchers to recruit people facing social disadvantage. Recruitment can be challenging, and there is limited high quality evidence to guide researchers. This paper describes experiences of recruiting 1068 participants facing social disadvantage for a randomised controlled trial of prescription charges, and provides evidence on the advantages and disadvantages of recruitment methods. Methods: Those living in areas of higher social deprivation, taking medicines for diabetes, taking anti-psychotic medicines, or with COPD were eligible to participate in the study. Several strategies were trialled to meet recruitment targets. We initially attempted to recruit participants in person, and then switched to a phone-based system, eventually utilising a market research company to deal with incoming calls. We used a range of strategies to publicise the study, including pamphlets in pharmacies and medical centres, media (especially local newspapers) and social media. Results: Enrolling people on the phone was cheaper on average than recruiting in person, but as we refined our approach over time, the cost of the latter dropped significantly. In person recruitment had many advantages, such as enhancing our understanding of potential participants' concerns. Forty-nine percent of our participants are Māori, which we attribute to having Māori researchers on the team, recruiting in areas of high Māori population, team members' existing links with Māori health providers, and engaging and working with Māori providers. Conclusions: Recruiting people facing social disadvantage requires careful planning and flexible recruitment strategies. Support from organisations trusted by potential participants is essential. Registration: The Free Meds study is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12618001486213). [ABSTRACT FROM AUTHOR]

Background A critical first step toward incorporating equity into cost-effectiveness analyses is to appropriately model interventions by population subgroups. In this paper we use a standardized treatment intervention to examine the impact of using ethnic-specific (Māori and non-Māori) data in cost-utility analyses for three cancers. Methods We estimate gains in health-adjusted life years (HALYs) for a simple intervention (20% reduction in excess cancer mortality) for lung, female breast, and colon cancers, using Markov modeling. Base models include ethnic-specific cancer incidence with other parameters either turned off or set to non-Māori levels for both groups. Subsequent models add ethnic-specific cancer survival, morbidity, and life expectancy. Costs include intervention and downstream health system costs. Results For the three cancers, including existing inequalities in background parameters (population mortality and comorbidities) for Māori attributes less value to a year of life saved compared to non-Māori and lowers the relative health gains for Māori. In contrast, ethnic inequalities in cancer parameters have less predictable effects. Despite Māori having higher excess mortality from all three cancers, modeled health gains for Māori were less from the lung cancer intervention than for non-Māori but higher for the breast and colon interventions. Conclusions Cost-effectiveness modeling is a useful tool in the prioritization of health services. But there are important (and sometimes counterintuitive) implications of including ethnic-specific background and disease parameters. In order to avoid perpetuating existing ethnic inequalities in health, such analyses should be undertaken with care. [ABSTRACT FROM AUTHOR]

Background: Health professional racial/ethnic bias may impact on clinical decision-making and contribute to subsequent ethnic health inequities. However, limited research has been undertaken among medical students. This paper presents findings from the Bias and Decision-Making in Medicine (BDMM) study, which sought to examine ethnic bias (Māori (indigenous peoples) compared with New Zealand European) among medical students and associations with clinical decision-making. Methods: All final year New Zealand (NZ) medical students in 2014 and 2015 (n = 888) were invited to participate in a cross-sectional online study. Key components included: two chronic disease vignettes (cardiovascular disease (CVD) and depression) with randomized patient ethnicity (Māori or NZ European) and questions on patient management; implicit bias measures (an ethnicity preference Implicit Association Test (IAT) and an ethnicity and compliant patient IAT); and, explicit ethnic bias questions. Associations between ethnic bias and clinical decision-making responses to vignettes were tested using linear regression. Results: Three hundred and two students participated (34% response rate). Implicit and explicit ethnic bias favoring NZ Europeans was apparent among medical students. In the CVD vignette, no significant differences in clinical decisionmaking by patient ethnicity were observed. There were also no differential associations by patient ethnicity between any measures of ethnic bias (implicit or explicit) and patient management responses in the CVD vignette. In the depression vignette, some differences in the ranking of recommended treatment options were observed by patient ethnicity and explicit preference for NZ Europeans was associated with increased reporting that NZ European patients would benefit from treatment but not Māori (slope difference 0.34, 95% CI 0.08, 0.60; p = 0. 011), although this was the only significant finding in these analyses. Conclusions: NZ medical students demonstrated ethnic bias, although overall this was not associated with clinical decision-making. This study both adds to the small body of literature internationally on racial/ethnic bias among medical students and provides relevant and important information for medical education on indigenous health and ethnic health inequities in New Zealand. [ABSTRACT FROM AUTHOR]

Background: The history of infant mortality inequities among Māori in New Zealand provides a remarkable case study for understanding the shortcomings of policy which fails to consider the differential risks associated with disadvantaged groups. Specifically, the failure of the initial 1991 reform in addressing Māori infant health, followed by the relative success of post-1994 policy, demonstrate that disadvantaged populations carry differential social risks which require adjusting policy accordingly. Literature on these policies show that differential risks may include disparities in representation, access to resources, socioeconomic status, and racism. The consideration of differential risks is important in analyzing the underlying causes of inequities and social policy deficiencies. Aim: To describe and illustrate the need for policy addressing inequities to consider the differential risks associated with disadvantaged groups through an analysis of New Zealand's Māori infant mortality policy progression. Methods: The article is a commentary on a series of policies aimed at reducing infant mortality in New Zealand. It analyses three policies and how their differences are linked to the corresponding trends in equity between Māori and non-Māori populations. Findings: The progression of Māori infant mortality policy clearly demonstrates that equitable social policy must be culturally sensitive and inclusive towards disadvantaged groups, as well as willing to adapt to changing circumstances and shortcomings of current policy. Prior to 1994, health policy which did not account for the differential risks of Māori populations caused inequities in infant mortality to increase, despite infant mortality decreasing on a national level. After policy was adjusted to account for Māori-specific risks in 1994, infant mortality inequities significantly declined. A comprehensive analysis of these policies shows that the consideration of differential risks is highly related to a decrease in corresponding inequities. Conclusions: As New Zealand, and other countries facing inequities such as the United States and Australia, move forward in constructing policy, they would do well to consider the lessons of how New Zealand policy changed the frequency of infant mortality in Māori populations. The study shows that the consideration of differential risks associated with disadvantaged groups is necessary for policy to successfully address inequities. [ABSTRACT FROM AUTHOR]

Background: The health status of Indigenous populations of Australia and New Zealand (NZ) Māori manifests as life expectancies substantially lower than the total population. Accurate assessment of time trends in mortality and life expectancy allows evaluation of progress in reduction of health inequalities compared to the national or non-Indigenous population. Methods: Age-specific mortality and life expectancy (at birth) (LE) for Indigenous populations (Australia from 1990 and NZ from 1950); and all Australia and non-Māori NZ (from 1890), males (M) and females (F), were obtained from published sources and national statistical agency reports. Period trends were assessed for credible estimates of Indigenous LE, and the LE gap compared to the total population for Australia, and non-Māori for NZ. Period trends in premature adult mortality, as cumulative probability of dying over 15-59 years, were assessed similarly. The relative contribution of differences in age-specific mortality to the LE gap between Indigenous and the all-Australia population, and the non-Māori NZ, was estimated for each country by sex for the most recent period: 2010-2012 for Australia, 2012-2014 for NZ. Results: LE increased for all populations, although LE gaps between Indigenous and all Australia showed little change over time. LE gaps between NZ Māori and non-Māori increased significantly from the early 1980s to the mid-1990s, and since then have fallen again. Recent LE gaps in Australia (M 12.5; F 12.0 years in 2010-2012) were larger than in NZ (M 7.3; F 6.8 years in 2012-2014). Premature adult mortality (15-59 years) improved for all populations, but mortality ratios show little change since 2000, with Indigenous at 3½-4 times that of all Australians, and Māori 2-3 times that of non-Māori. Using decomposition analysis, the age interval contributing most strongly to differences in LE between Indigenous and all Australia was 35-59 years, but between Māori and non-Māori it was 60-74 years. Conclusion: In Australia and NZ, Indigenous LE and adult mortality are improving in absolute terms, but not relative to the entire or non-Indigenous populations, causing gaps in life expectancy to persist. [ABSTRACT FROM AUTHOR]

Background: Internationally, ethnic inequalities in mortality within countries are increasingly recognized as a public health concern. But few countries have data to monitor such inequalities. We aimed to provide a detailed description of ethnic inequalities (Maori [indigenous], Pacific, and European/Other) in mortality for a country with high quality ethnicity data, using both standard and novel visualization methods. Methods: Cohort studies of the entire New Zealand population were conducted, using probabilistically-linked Census and mortality data from 1981 to 2011 (68.9 million person years). Absolute (standardized rate difference) and relative (standardized rate ratio) inequalities were calculated, in 1-74-year-olds, for Maori and Pacific peoples in comparison to European/Other. Results: All-cause mortality rates were highest for Maori, followed by Pacific peoples then European/Other, and declined in all three ethnic groups over time. Pacific peoples experienced the slowest annual percentage fall in mortality rates, then Maori, with European/Other having the highest percentage falls - resulting in widening relative inequalities. Absolute inequalities, however, for both Maori and Pacific males compared to European/Other have been falling since 1996. But for females, only Maori absolute inequalities (compared with European/Other) have been falling. Regarding cause of death, cancer is becoming a more important contributor than cardiovascular disease (CVD) to absolute inequalities, especially for Maori females. Conclusions: We found declines in all-cause mortality rates, over time, for each ethnic group of interest. Ethnic mortality inequalities are generally stable or even falling in absolute terms, but have increased on a relative scale. The drivers of these inequalities in mortality are transitioning over time, away from CVD to cancer and diabetes; such transitions are likely in other countries, and warrant further research. To address these inequalities, policymakers need to enhance prevention activities and health care delivery, but also support wider improvements in educational achievement and socioeconomic position for highest need populations. [ABSTRACT FROM AUTHOR]

Background: Comorbidity has an adverse impact on cancer survival partly through its negative impact on receipt of curative treatment. Comorbidity is unevenly distributed within populations, with some ethnic and socioeconomic groups having considerably higher burden. The aim of this study was to investigate the inter-relationships between comorbidity, ethnicity, receipt of treatment, and cancer survival among patients with stomach and liver cancer in New Zealand. Methods: Using the New Zealand Cancer Registry, Māori patients diagnosed with stomach and liver cancers were identified (n = 269), and compared with a randomly selected group of non-Māori patients (n = 255). Clinical and outcome data were collected from medical records, and the administrative hospitalisation and mortality databases. Logistic and Cox regression modelling with multivariable adjustment were used to examine the impacts of ethnicity and comorbidity on receipt of treatment, and the impact of these variables on all-cause and cancer specific survival. Results: More than 70% of patients had died by two years post-diagnosis. As comorbidity burden increased among those with Stage I-III disease, the likelihood that the patient would receive curative surgery decreased (e.g. C3 Index score 6 vs 0, adjusted OR: 0.32, 95% CI 0.13-0.78) and risk of mortality increased (e.g. C3 Index score 6 vs 0, adjusted all-cause HR: 1.44, 95% CI 0.93-2.23). Receipt of curative surgery reduced this excess mortality, in some cases substantially; but the extent to which this occurred varied by level of comorbidity. Māori patients had somewhat higher levels of comorbidity (34% in highest comorbidity category compared with 23% for non-Māori) and poorer survival that was not explained by age, sex, site, stage, comorbidity or receipt of curative surgery (adjusted cancer-specific HR: 1.36, 95% CI 0.97-1.90; adjusted all-cause HR: 1.33, 95% CI 0.97-1.82). Access to healthcare factors accounted for 25-36% of this survival difference. Conclusions: Patients with comorbidity were substantially less likely to receive curative surgery and more likely to die than those without comorbidity. Receipt of curative surgery markedly reduced their excess mortality. Despite no discernible difference in likelihood of curative treatment receipt, Māori remained more likely to die than non-Māori even after adjusting for confounding and mediating variables. [ABSTRACT FROM AUTHOR]

Background: In New Zealand, there are significant and long-standing inequalities in a range of health outcomes, risk factors and healthcare measures between Māori (indigenous peoples) and Pākehā (European). This study expands our understanding of racism as a determinant of such inequalities to examine the concept of socially-assigned ethnicity (how an individual is classified by others ethnically/racially) and its relationship to health and racism for Māori. There is some evidence internationally that being socially-assigned as the dominant ethnic group (in this case European) offers health advantage. Methods: We analysed data from the 2006/07 New Zealand Health Survey for adult participants who self-identified their ethnicity as Māori (n = 3160). The association between socially-assigned ethnicity and individual experience of racial discrimination, and socially-assigned ethnicity and health (self-rated health, psychological distress [Kessler 10-item scale]) was assessed using logistic and linear regression analyses, respectively. Results: Māori who were socially-assigned as European-only had significantly lower experience of racial discrimination (adjusted odds ratio [OR] = 0.58, 95% confidence interval [CI] = 0.44, 0.78) than Māori who were socially-assigned as non-European. Being socially-assigned as European-only was also associated with health advantage compared to being socially-assigned non-European: more likely to respond with self-rated very good/excellent health (age, sex adjusted OR = 1.39, 95% CI = 1.10, 1.74), and lower Kessler 10 scores (age, sex adjusted mean difference = -0.66, 95% C I = -1.22, -0.10). These results were attenuated following adjustment for socioeconomic measures and experience of racial discrimination. Conclusions: Results suggest that, in a race conscious society, the way people's ethnicities are viewed by others is associated with tangible health risk or advantage, and this is consistent with an understanding of racism as a health determinant. [ABSTRACT FROM AUTHOR]