There have been many calls to reduce inequities in the health of New Zealand children [3
]. In addition to social justice and ethical rationale for health equity, the economic costs that we bear through continued health inequities are important to consider. Assigning a monetary value to life or health remains antithetical to some. However, economic evaluation is commonly accepted as a consideration in decision-making, for example in allocation of government spending, and we believe this scoping study is an important initial step in developing more appropriate methods for examining the true costs of inequity.
While a preliminary attempt is described here, the costings that result can be considered highly conservative and an under-estimation of the full costs of inequity. Firstly, we have not assumed that all “avoidable” deaths and hospitalisations can be eliminated, but used a conservative counterfactual, estimating the number of potentially avoidable deaths/admissions/consultations that would have occurred if Māori children had the same rate as non-Māori in each age group.
Secondly, if non-Māori, non-Pacific children (i.e. predominantly New Zealand European) are used as the comparator group, greater inequities become apparent, given the high rates of illness and mortality experienced by Pacific children in New Zealand. 99 fewer deaths per year (nearly 77 of them Māori) and just under 10,000 hospital admissions would be prevented if Māori and Pacific children had the same rates of death and illness as non-Māori, non-Pacific children [data not shown].
In addition, we have not attempted to cost many of the childhood “diseases of inequity” such as rheumatic fever and bronchiectasis, which have lifelong impacts. We acknowledge that many of the significant social and intangible costs to children and families are not captured, including grief and suffering, missed educational opportunities, and employment and productivity losses for family, caregivers and for the child into the future.
The key findings, however, are important. Firstly, these estimates give an indication of the significant societal cost of inequities in health. As might be expected from similar economic analyses and other cost of illness studies, the human cost of the inequity in premature mortality is the greatest cost to society, rather than direct health system costs.
Secondly, health sector expenditure appears skewed towards non-Māori children. Our analysis suggests that it costs the health sector less to admit acutely sick Māori children, than to prevent severe illness through ensuring equitable primary care access or effective population-based interventions. Therefore a Ministry of Health concerned only with containing health sector spending has no incentive to reduce inequities in primary care access.
Lower utilisation of primary care and higher rates of potentially avoidable hospitalisations for Māori children are not new findings, despite persisting evidence of unmet need for primary care-amenable conditions [3
]. Although primary care utilisation for all ethnic groups has increased since the introduction of the NZ Primary Health Care Strategy (2001) with additional funding to PHOs to improve financial access, the largest increase in utilisation has been by less deprived populations, where Māori are under-represented compared with non-Māori [48
]. The reasons for poorer access to primary care are likely to be multi-factorial, including socio-economic factors. As primary care utilisation drives access to most other health services, including specialist outpatient services, addressing access barriers and attaining equitable utilisation of primary care services by Māori children has the potential to reduce the unacceptable disparities in avoidable hospitalisations and mortality seen here, and produce economic benefits that offset the costs of service delivery. Further intervention research in this area is crucial to understanding and addressing this inequity.
There are evident limitations in this study, and some unresolved challenges. Kaupapa Māori is a research methodology that utilises various research tools (in this case economic methods) to examine and contextualise Māori lived realities, to inform Māori development. Part of the spectrum of a Kaupapa Māori approach parallels Critical Theory and seeks to reveal inequity and challenge injustice. A major concern therefore in valuing child health and inequities relates to the values and assumptions of current economic approaches, and the appropriateness of the costing methods derived from these. The theoretical basis of “welfare economics”, which is the conventional neo-classical economic approach to social goods, is essentially utilitarian [27
]. This assumes that the welfare output is maximised and is a function of individual preferences, where everyone is thought to maximise their own “utility” (i.e. the benefits they gain from their preferred choice of “goods”). This could be seen as antithetical to Māori values and concepts of reciprocity. It also presupposes that individuals are fully informed to make decisions in a free market, which is not an assumption easily applied to child health.
Further critique of this conventional welfare economics approach includes its indifference to the distribution
of “utilities” (in this case, health states) across individuals and thus to concepts of equity, including intergenerational equity, which is important to consider in valuing child health [26
]. Despite these limitations, it remains the conceptual basis for economic evaluation in the health sector.
Cost of illness methodology is descriptive, valuing in dollar terms the costs of a particular health problem, which then enables the economic burden of the problem to be estimated. Cost of illness studies are not considered full economic evaluations because they do not assess cost effectiveness or the cost-benefits of comparable interventions, and are critiqued by many welfare economists as not being sufficiently grounded in welfare economics theory. Other critique relates to the use of the human capital approach to evaluate the value of life. Despite these limitations, they can call attention to the importance of specific health issues, as demonstrated here [37
A further area of debate in economic studies is how to value the loss of a life, as well as non-fatal outcomes such as the loss of function and lifetime sequelae of illness, especially for children [24
]. There is some evidence that people may value a young person’s life more than an older person’s one [54
]. Assigning a monetary value to life and health remains controversial, and there is considerable variation in “value of life” values obtained in empirical “willingness-to-pay” studies. We have used what is now regarded as a very conservative VoSL figure [35
Discounting is another particular challenge in valuing child health. Discounting implies we value something more if we have utility from it today than in the future. For example, preventing the death of one infant achieves a gain of over 80 life-years, but this amounts to only 12 life years discounted at 8% (Treasury’s default rate in New Zealand [57
]). There is considerable controversy about applying “market” discount rates to health, and ongoing debate about the assumptions underlying different discount rates [36
]. Some argue that the discount rate should vary over time, rather than be applied at a constant rate, and it is not clear how sensible time preferences can really be for events over fifty years into the future [59
]. It is unlikely that we would prefer to deny crucial preventive interventions for children, simply because the potential costs in terms of ill health would only be borne far into the future.
Data quality is another area of potential uncertainty. Although ethnicity coding in New Zealand has become more complete and accurate over the last decade, mis-classification and under-counting of Māori is still reported across the health sector [60
]. In our data, there does not appear to be any net undercount of Māori in birth and mortality datasets [61
]. Hospital numerator undercounting is estimated to be relatively small for young children, so we did not adjust for this [61
]. For the laboratory, pharmaceutical, outpatient and ACC datasets there were small numbers of missing ethnicity values (<3%). In primary care, undercounting and misclassification of Māori persists [60
], and is borne out in this study when enrolment data is compared with population estimates. Undercounting in the Census is described, especially of Māori and youth [64
]; we used the Statistics New Zealand population estimates that are based on adjusted Census data, using post-census enumerator surveys to estimate the extent of undercount. Overall, ethnicity misclassification and undercounting of Māori is unlikely to have significantly altered the overall findings.