The UN Human Rights Council’s Universal Periodic Review (UPR) operates a five-year cycle for all countries to demonstrate compliance with all human rights obligations – not just those arising from treaties that the country has ratified. It is therefore quite a departure from individual treaties’ UN Monitoring Committees, giving rise to a more cohesive, comprehensive overview of a country’s human rights performance. This coherence reflects the UPR’s principle of promoting the universality, interdependence, indivisibility and inter-relatedness of all human rights. While the UPR has been well received generally by states, civil society and human rights institutions, and it promotes a collegial, ‘judgement by peers’ approach to human rights reporting, it is not yet clear whether it is “changing human rights on the ground” (J. McGregor, S. Bell, and M. Wilson, “Human Rights in New Zealand – Emerging Fault Lines” 2016). UPR recommendations are not specific; they ask States to take varying types or degrees of action, but they do not quantify the results expected.
In an effort to gain clarity about its effect ‘on the ground’, this research project is examining the impact of UPR recommendations made to New Zealand at the conclusion of its second reporting cycle, ending in 2014. The New Zealand Human Rights Commission developed a comprehensive online monitoring tool of UPR recommendations that lists all 155 recommendations. The 121 accepted recommendations have been categorised by the Commission, in consultation with the government agencies, into issues, government actions, population group, or UN Treaty Bodies that the recommendations relate to (Fig 1).
There were seven UPR recommendations relating to Pacific people. These combined into several government actions, including Government Action 30: “Improve access to timely and effective maternity and child health services for Pacific Peoples”. The Ministry of Health proferred seven measures (indicators) to monitor the achievement of the UPR recommendations on Pacific Healthwhich are included in the tool.
Our research explores two of these seven measures: increase percentage of Pacific infants who are enrolled with a general practice by three months; increase in percentage of Pacific children who receive B4 School Checks (B4SC) – a nationwide programme offering a free health and development check for 4-year-olds.
We are using the term Big Data to refer to government administrative datasets and an area-based deprivation tool called the New Zealand Index of Multiple Deprivation (IMD). Statistics New Zealand collects and manages government agency data in the Integrated Data Infrastructure (IDI)—a microdata repository of anonymised, individual-level information from many ministries, including health, education, inland revenue, housing, immigration, police, and justice, that is updated quarterly. The IMD combines 28 indicators of deprivation, grouped into seven ‘domains’(employment, income, crime, health, housing, education, access) that can be used individually or combined, to provide comprehensive, robust and accurate measure of deprivation circumstances among small areas with an average population of 712.
We linked de-identified data sources within the IDI, containing information on Pacific or ‘European’ ethnicity, mothers’ education and language, housing ownership, number of people living in the home, and welfare support, and further analysed these results by neighbourhood deprivation quintiles using the IMD. This analysis provided insight into the characteristics and circumstances of people whose children participate in the free B4SC.
Enrolment of infants in a general practice
The enrolment of Pacific infants in a general practice by the age of three months increased from 90.5% in 2014 to 92% in 2016. European infants (non Maori, non Pacific, non Asian) enrolment increased from 93.5% to 94.4%. The level of deprivation in the neighbourhoods where parents lived had little impact on the rate of enrolment. Enrolment of infants in a general practice is able to be completed at birthing units and confers the benefit of free health care on the infant, hence the high uptake regardless of parents’ circumstances. This suggests that the health rights entitlement to accessible healthcare, and information about healthcare, is improving for all families in New Zealand, with only a small deficit remaining between Pacific and European groups.
Completion of B4 School Checks
The B4SC includes vision and hearing tests (VHT); ‘nurse checks’ which cover growth, dental checks, immunisation, a parents’ evaluation of developmental status and strengths and difficulties questionnaire completed by parent with the nurse; and another strengths and difficulties questionnaire completed by a teacher (SDQT), which cannot be completed unless the child is enrolled in an early childhood education facility, which is not compulsory. The B4SC were introduced in 2008, when they achieved 79% coverage (but not completion of all tests) of all four-year old children, and by 2015-16 this had increased to 92%. These tests are time consuming and require a parent or caregiver to take the child to different facilities. This can be difficult for working parents or those without transport, and uptake also depends on knowledge of the availability of the tests. As can be seen in the results (Table 1), the more deprived an area in which a Pacific child lives (Quintile 5), the lower the rate of completion of the nurse and SQDT tests, which are the most time consuming and least understood. Vision and hearing tests have higher completion rates by all children.
Table 1: B4SC component completion rates 2013-2015
|VHT % complete||Nurse check % complete||SQDT % complete|
|Euro (Quintile 1*)||91.8||93.1||84.8||88.9||66.1||71.7|
|Pacific (Quintile 1)||83.8||84.9||80.0||81.0||58.1||56.3|
|Euro (Quintile 5**)||90.0||93.3||84.9||89.5||64.9||70.6|
|Pacific (Quintile 5)||80.8||88.0||74.6||83.3||32.3||31.0|
* Quintile 1 = least deprived
** Quintile 5 = most deprived
The analysis of all the other data sets consistently showed that the more hardship (or deprivation) a family experiences, including overcrowded rental homes, lacking educational qualifications, being dependent on welfare support, not speaking English, the less likely it is that the child will complete all aspects of the B4SC. For example, only 82.7% of Pacific children whose mother has no educational qualification complete the VHT, 76.1% complete the Nurses check, and 38.4% complete the SQDT, compared to 87.3%, 82.5% and 37% respectively overall for Pacific children.
If the trends identified in the 2013-2015 period hold to the end of 2018, the New Zealand government could report that it has improved Pacific child health according to two of its own measures (indicators). A higher percentage of Pacific infants are enroled in primary health care now than in 2013, and overall, a bigger percentage of Pacific children is completing the B4SC. However, the use of Big Data provides a far more detailed analysis which shows that families suffering the most deprivation are least likely to take up a complex but free health service. Here there is a widening gap between Pacific and European children – and there is even less uptake by Pacific families now than two years ago. Therefore, at this mid point in the research this research has identified one measure suggestive of human rights retrogression: the SDQT completion rate by the most deprived Pacific children which has slipped from 32.3% to 31%, while at the same time the European rate improved from 64.5% to 70%.
The purpose of this research is to demonstrate that Big Data can help identify whether health policies are promoting health rights. We have identified some characteristics of families, and areas of deprivations, that can make it more difficult to claim entitlements to health rights, and we have also shown that in some areas health inequalities are reducing. This provides an opportunity for policy makers to assess what promotes improvements in health care for people who have multiple deprivations, and how can these factors be applied to other services where uptake is slipping away. Ease of access appears to be an important factor.
Big Data’s use in UPR monitoring can promote more transparency and accuracy around the uptake of health services, and assist countries to put policies and programmes in place that will help improve equality and reduce the impact of historic and ongoing discrimination.
Disclaimer: The views expressed herein are the author(s) alone