Results
Table
1 summarises the results for avoidable hospitalisations and healthcare costs of differential utilisation by Māori and non-Māori children. The estimate of the health sector costs of inequity in childhood illness and injuries is a cost saving to the health sector of $24,737,408 per annum.
Table 1
Māori: non-Māori Rate Ratios and Estimates of the Cost to the Health Sector of Inequity in Illness and Injury ($NZ)
Avoidable hospital admissions (2003–7)
|
1.27 (95% CI 1.26–1.28) | 3075 fewer Māori admissions/year |
$ 5,671,057
|
Outpatient consultations (2006–2008)
|
0.864 (95% CI 0.862–0.867) | 23,373 more consultations/year |
[−]$ 8,022,315
|
Mental health consultations (20007–8)
|
0.719 (95% CI 0.714–0.723) | 5740 more consultations/year |
[−]$ 1,970,140
|
ACC claims (2003–7)
|
0.680 (95% CI 0.678–0.683) | 26,442 more claims/year |
[−]$ 1,499,765
|
Primary care (2007–2008)
|
0.919 (95%CI 0.916–0.921) GP visits | 40,041 more GP consultations/year |
[−]$ 1,079,906
|
1.677 (95%CI 1.665–1.689) nursing visits | 17,194 fewer nursing consultations |
$ 400,803
|
Pharmaceutical claims (2007–8)
|
0.849
| 198,108 more claims/year |
[−]$ 10,447,348
|
Laboratory claims (2006–8)
|
0.454 (95%CI 0.452–0.455) | 101,922 more claims/year |
[−]$ 7,789, 795
|
SUB TOTAL HEALTH SECTOR COSTS/[SAVINGS] PER ANNUM
|
[−]$ 24,737,408
|
Inequity in potentially avoidable hospital admissions
There were a total of 871,094 hospital admissions for children <15 years in the period 2003–2007. The crude rate ratio for total Māori:non-Māori admissions was 0.98 (95% CI 0.975–0.984). 36% of hospitalisations of children in this age group were classified as “potentially avoidable”. Māori:non-Māori rate ratios for potentially avoidable hospitalisation rates were significantly greater than one in all age groups. Respiratory diseases made the greatest contribution to the “excess”, with diseases of the ear, digestive system and skin, and injuries also being important. In children aged 5–15years the highest rate ratio was for circulatory diseases (including rheumatic heart disease), where the Māori:non-Māori rate ratio was 3.33 (95% CI 2.93–3.79). Overall, summing the “excess” avoidable hospitalisations, there were a total of 15,376 “excess” Māori avoidable admissions during 2003–7 or 3,075 each year.
Inequity in hospital general outpatient and mental health outpatient consultations (2006–2008)
Hospital outpatient utilisation rates for Māori children were consistently lower than for non-Māori children for all age groups in the period July 2006-December 2008 (Table
1). The overall Māori:non-Māori rate ratio was 0.864 (95% CI 0.862–0.867). If Māori children had the same outpatient consultation rate as non-Māori there would have been 23,373 more consultations by Māori children annually. Māori children were nearly 30% less likely than non-Māori to attend outpatient mental health services. If Māori had the same consultation rate as non-Māori there would have been 5740 more consultations by Māori children per year in mental health services.
Inequity in Accident Compensation Corporation (ACC) accident and injury consultations (2003–2007)
There were 291,502 Māori and 1,322,560 non-Māori ACC claims for children < 15years during the 2003–2007 period. Māori rates were significantly lower than non-Māori, with an overall rate ratio of 0.680 (95% CI 0.678–0.683). There were 26,442 fewer claims per year by Māori children in the period than if claims had been made at the non-Māori rate.
Inequity in primary care (2007–2008)
A mean number of 353,734 Māori and 1,374,972 non-Māori children were enrolled in Primary Health Organisations (PHOs) during 2007–8; fewer in total than the SNZ population estimates for the same period, and a significantly lower proportion of Māori children than in official population estimates. If Māori children had consulted GPs at the same rate as non-Māori, there would have been 40,041 more GP consultations annually. Nursing consultations showed the inverse; although total nursing consultations were much fewer than GP consultations, Māori utilisation rates were 1.68 times greater than non-Māori, resulting in 17,194 consultations more than expected if Māori utilisation had been equivalent to the non-Māori rate.
Inequity in pharmaceutical claims (2007–2008)
There were over 7.9 million pharmaceutical claims for children <15 years during 2007–8; only 21.7% of these were for Māori <15years. Māori rates of claims were significantly lower than non-Māori, representing an “under-utilisation” of 198,108 claims per year.
Inequity in laboratory utilisation (2007–2008)
In 2007–8 there were 1.28 million laboratory claims for children <15years; 12.9% of these were recorded as being for Māori children. The overall Māori:non-Māori rate ratio was 0.454 (95% CI 0.452–0.455); rate ratios in children <1years were even lower. There would have been 101,922 more claims by Māori children each year if Māori had the same rate of laboratory use as non-Māori.
Inequity in avoidable mortality
In the period 2003–7 there were 299,421 live births and 2,345 deaths in children aged 0- < 15yrs. 85% of these deaths were “potentially avoidable”. If Māori avoidable mortality rates had equalled non-Māori rates for each age group in the period, there would have been 333 fewer Māori deaths (nearly 67 deaths per year); 56% of these would be in the 28 day- <1year age group (Table
2).
Table 2
Avoidable Deaths by Ethnicity and Age Group, 2003–7
0- < 28days
| 260 | 300.65 | 593 | 278.48 | 1.08 (0.93–1.25) | 240.8 |
19.17
|
28days- <1 year
| 302 | 349.22 | 279 | 131.02 | 2.67 (2.27–3.14) | 113.3 |
188.69
|
1 year- < 5years
| 98 | 33.62 | 139 | 16.43 | 2.05 (1.58–2.65) | 47.9 |
50.09
|
5years- < 15yrs
| 132 | 18.53 | 184 | 7.98 | 2.32 (1.86–2.90) | 56.8 |
75.17
|
Total
| 792 | 72.62 | 1195 | 35.50 | 2.05 (1.87–2.24) | n.a. |
333.12
|
Māori avoidable mortality rates were significantly higher than non-Māori in all age groups except for the first month of life. The biggest contributor to mortality in this age group was deaths related to perinatal conditions (mainly resulting from prematurity), where Māori infant mortality rates were non-significantly higher than non-Māori.
In the age group 28days-<1year, 41.5% of the avoidable deaths were assigned “Sudden Unexpected Death in Infancy” (SUDI) codes. SUDI rates were significantly higher for Māori and especially Māori males in this age group; respiratory diseases (J00-99 codes) were the other main contributor to Māori infant deaths under one year.
There were significantly higher rates in Māori for “external causes” (accident, injury and assault codes V01-Y98) in all age groups, with the highest rates and rate ratios seen in infants 28 days - <1year. In girls 1–5years, the Māori:non-Māori rate ratio for injury/external causes was 3.35 (95% CI 2.00–5.62), and this accounted for nearly all the excess deaths. In 5–15year-old girls, nearly two thirds of the “excess” mortality was injury-related. In 5–15year-old males, injury/external causes again contributed to the majority of “excess” deaths, although the highest Māori:non-Māori rate ratios were for the ICD-10AM “A–B” and “E” codes (infectious and parasitic diseases, and endocrine, nutritional and metabolic diseases).
Estimation of years of life lost from premature mortality
The years of life lost (YLL) to excess avoidable mortality in each age/sex group was computed, based on the difference between the midpoint of age of death in each age group and the non-Māori life expectancy for their same sex counterpart. The total value was 5210 life years lost per year. We examined the data using a range of discount values, based on those used in recent NZ cost of illness studies [
33‐
37,
42‐
44]. Applying a discount rate of 3% reduces the life years lost to 38% of their present value; if it is increased to 8%, it is only 16% of present value (831 life years) (Table
3).
Table 3
Years of Life Lost (YLL) from Avoidable Māori Child Deaths by Age Group and Gender, at Varying Discount Rates
0–1yr female | 7279 | 2680 | 1726 | 1095 |
1–5yr female | 1825 | 689 | 446 | 283 |
5–15yr female | 2926 | 1182 | 776 | 497 |
Total Female
|
12030
|
4551
|
2948
|
1875
|
0–1yr male | 9480 | 3626 | 2353 | 1498 |
1–5yr male | 2091 | 820 | 535 | 341 |
5–15yr male | 2450 | 1029 | 683 | 439 |
Total Male
|
14021
|
5475
|
3571
|
2278
|
Total 2003–7
|
26051
|
10026
|
6518
|
4153
|
Annual YLL
|
5210
|
2005
|
1304
|
831
|
Equivalent “Statistical Lives”*
|
66.8
|
25.7
|
16.7
|
10.6
|
Cost of years of life lost
The Method 1 “base case” scenario assumes a mean life expectancy at birth of 78 years, YLL discounted at 3%, and uses the New Zealand Ministry of Transport VoSL at June 2008 prices ($3,352,000) [
36,
42]. The YLL at 3% discounting are equivalent to the value of 25.7 “Statistical Lives” annually, computing to a cost of $NZ86.18 million annually at present value.
Method 2 results in similar values to Method 1 at zero discounting ($NZ223.3million per year), but as the VoSLY increases in Method 2 with increases in the discount rate, at 3% this computes to $NZ224 million per annum.
Costs to society and family
The cost of work days lost by caregivers is based on the median length of stay for avoidable hospital admissions. This computes to $269 for each of the 3075 annual “excess” avoidable admissions, a total cost of $827,175 per year. Māori caregivers “out of pocket” payments for primary care were estimated to be $245,523 less than expected, primarily due to lower GP consultation rates for tamariki Māori.
Table
4 shows the total annualised cost estimate for each method.
Table 4
Comparison of Annualised Costs of the “Base Case” Scenario at 3% Discount Rate using Alternative Methods
Health sector costs | −$24,737,408 |
Loss of wages | $827,175 |
Out of Pocket Costs (Primary Care) | −$245,523 |
Sub-total
| −$24,155,756 |
Method 1: Years of Life Lost | $86,181,425 |
Method 2 Years of Life Lost | $224,035,436 |
TOTAL COST
|
Method 1
|
$62,025,669
|
Method 2
|
$199,879,680
|
Sensitivity analysis
We examined the impact of different discount rates, using both methods. Method 1 results in a rapid decrease in present value as the discount rate increases. However using O’Dea & Tucker’s method there is little variability in the total value at differing discount rates (Table
5).
Table 5
Cost of Years of Life Lost (YLL) by Age group and Gender at Varying Discount Rates (Method 2) ($NZ)
0–1yr female | $294,130,013 | $294,947,777 | $294,391,755 | $294,180,462 |
1–5yr female | $76,163,022 | $76,394,291 | $76,240,799 | $76,179,257 |
5–15yr female | $133,695,626 | $134,198,138 | $133,878,164 | $133,730,682 |
0–1yr male | $402,528,431 | $403,786,759 | $402,944,243 | $402,597,057 |
1–5yr male | $91,790,026 | $92,102,235 | $91,897,812 | $91,809,104 |
5–15yr male | $118,240,841 | $118,747,980 | $118,437,538 | $118,282,829 |
Total
|
$1,116,547,960
|
$1,120,177,180
|
$1,117,790,309
|
$1,116,779,391
|
Annual
|
$223,309,592
|
$224,035,436
|
$223,558,062
|
$223,355,878
|
We also varied the “value of a statistical life year” (using values derived from previous studies [
34‐
37]); predictably this has a significant impact on the final result, as the cost of “excess” avoidable mortality is a large proportion of the total costs (Table
6). The final range of estimates shows the total cost is highly sensitive to the method used, and the discount rate and VoSL applied.
Table 6
Value of YLL from Childhood Inequities, varying VoSL Values and Discount Rates ($NZ)
$2.212m (Fire Safety, 2007 [ 43]) | $147,797,553 | $147,384,352 | $56,879,748 | $147,863,409 | $36,981,626 | $147,548,342 | $23,563,447 | $147,414,901 |
$3.352m (Transport 1991 [ 42]) | $223,935,654 | $223,309,592 | $86,181,425 | $224,035,436 | $56,032,759 | $223,558,062 | $35,702,187 | $223,355,878 |
$5.676m (Transport 1998 [ 36]) | $379,192,367 | $378,132,251 | $145,931,824 | $379,361,329 | $94,880,802 | $378,552,987 | $60,454,853 | $378,210,627 |
Discussion
There have been many calls to reduce inequities in the health of New Zealand children [
3,
45‐
47]. 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,
24,
47]. 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,
36,
49,
50]. 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,
28,
30]. 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,
51].
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,
32,
52‐
54]. There is some evidence that people may value a young person’s life more than an older person’s one [
54,
55]. 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,
56].
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,
58]). There is considerable controversy about applying “market” discount rates to health, and ongoing debate about the assumptions underlying different discount rates [
36,
58]. 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,
62,
63], 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.
Competing interests
The authors declare they have no competing interests.
Authors’ contributions
All authors contributed to the study conception and design. CM led analysis of study data and drafted the manuscript. All authors read, revised and approved the final manuscript.