Some individuals have more than their fair share of health problems. This goes for groups of people too. As a first step in trying to make things fairer, it is important to measure the size of the differences in health and health care.
The Equity Explorer provides information on how health and health care varies between groups of people, and between district health board (DHB) areas of Aotearoa New Zealand (NZ).
Two types of group are compared: ethnic groups and groups based on socioeconomic status (deprivation).
The health conditions compared are diabetes, asthma and gout. For each condition, three indicators are presented.
The Equity Explorer information tells us things like this:
- There are differences in health care between different ethnic groups, different socioeconomic groups and different DHB areas for many of the indicators we measured.
- There are few differences in diabetes HbA1c blood testing.
- Some differences are inequitable, for example, children’s hospital admissions for asthma. Rates were 1.5–3 times higher for Māori and Pacific children, and children from more deprived areas, in many DHB areas.
Equity Explorer
Equity is ‘the absence of avoidable differences among groups of people, whether these groups are defined socially, economically, demographically or geographically’ (World Health Organization).
Health depends on many things, and ‘equal’ health is hard to achieve. Health providers try to provide quality services to all people in their care. However, factors such as age, poverty (deprivation), ethnicity, housing, health care service designs and government policies can all influence health. Within the health care system, factors that affect health include how easy it is to access services, the cost of services, staffing levels, available technology and medicines, and whether services meet the social and cultural needs of their populations.
The World Health Organization believes health equity is about fairness and human rights. Health care equity can include measures around several themes including accessing health care, patient safety, person-centered care, treatment received, quality of care, outcomes of care and underlying determinants of health.
Health equity is different from health equality. Health equality is ‘sameness’. Health equity better recognises that people differ in their ability to attain or maintain health. Consequently, equitable health outcomes may require different (ie, unequal) inputs to achieve the same result (New Zealand Medical Association).
It is important to measure the variation in health, health care and health outcomes because it helps us know whether services are meeting the population’s needs. Sometimes variation is expected or can be explained: children have fewer hip fractures than elderly people, for example. However, we know a lot of variation is unwarranted and unwanted: this is inequity. We also know inequity can be reduced by careful attention and service changes – but only if we know what things we need to adjust.
This Equity Explorer extends our work on the Atlas of Healthcare Variation. Our 16 existing Atlas domains measure variation across many different conditions, but the equity (or inequity) between different population groups is not easily seen. The aim of the Equity Explorer is to test different methods for showing inequity more clearly.
The benefits of the Equity Explorer are:
- the numbers look specifically at the size of the differences between population groups, rather than purely presenting different numbers for different groups
- socioeconomic variation is presented
- data is age-standardised, to allow more robust comparisons between ethnic groups
- testing of the ‘Explorer’ concept means indicators may be extended in the future.
This version of the Equity Explorer was designed to test the new approach, so we have concentrated on information that is most useful to our priority users: DHBs, primary health organisations, health professional groups and health-focused non-governmental organisations.
We used process measures rather than outcome measures because they are more amenable to change by our priority groups.
Questions that might be prompted by this information include the following:
- Why are there differences in health outcomes for different groups of people?
- Does everyone in the DHB have the same access to health care? Within my DHB area, which indicators have the biggest differences? Why?
- Which DHBs seem to be doing better in reducing health inequity and why might that be?
- Are there patterns across indicators, within my DHB?
- Download the Equity Explorer file, which will open in Microsoft Excel.
- Click on the tabs near the bottom of the screen to move between different worksheets in the file. Each worksheet gives a different picture of equity. Use the ‘Contents’ and ‘Help’ worksheets to find your way around.
- In the two ‘Equity within DHB’ worksheets, select the indicators, DHB(s) and years of interest from drop-down menus. The tables and graphs change according to the selection.
- In the ‘Ethnic equity by DHBs’ worksheet, select the ethnic group of interest from the drop-down menu. The tables change according to the selection.
The Explorer can be viewed in conjunction with our diabetes, asthma and gout Atlas domains for useful background information. Note the Atlas numbers are not directly comparable with the Equity Explorer numbers, because we used different methods.
It is also useful to look at the patterns across indicators for a particular area, or over time (where data exists). This avoids a ‘silo’ approach of just looking at one service or indicator at a point in time.
The Equity Explorer is not a DHB competition or league table. It is about quality improvement.
The development work was governed by an expert advisory group of 11 people (including consumers and Māori and Pacific health experts), and feedback was invited from relevant health sector organisations.
The Equity Explorer indicators are presented in an interactive Excel file, rather than using the Instant Atlas map-based platform. The Equity Explorer also uses methods of analysis that are more suited to comparing populations: for example, age-standardisation and total response ethnicity classification.
We selected indicators based on a number of criteria, including data availability and suitability, comparability to published Atlas domains, and relevance for health sector providers’ actions.
Further information on our data sources and analytical methodology is available in the technical appendix within the Excel file.
For diabetes:
- HbA1c testing showed little inequity between ethnic or socioeconomic groups.
- Some DHBs have inequity in angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) medicine dispensing between ethnic and deprivation groups.
- Māori, Pacific and Asian people with diabetes occupied comparatively more days in hospital compared with European people with diabetes. Likewise, socioeconomically deprived people with diabetes occupied comparatively more days in hospital than socioeconomically advantaged people with diabetes.
- Read more about the diabetes equity indicators.
For asthma:
- Māori, Pacific and socioeconomically deprived children are disproportionately more likely to be admitted to hospital for asthma.
- Asthma reliever inhalers were slightly more likely to be dispensed to Māori and Pacific peoples.
- There was wide variation in the dispensing of asthma preventer medicine between socioeconomic groups in some DHB areas.
- Read more about the asthma equity indicators.
For gout:
- Inequity in allopurinol dispensing for Māori and Pacific peoples persists with age standardised analyses.
- For most DHBs, there was no significant inequity in the rate of non-steroidal anti-inflammatory drug dispensing without allopurinol.
- Māori, Pacific and Asian people with gout received disproportionately more uric acid testing.
- Read more about the gout equity indicators.
An ideal equity assessment would need numerous indicators to examine the whole health system. We have focused on process indicators because these are most useful for our priority users. However, this means the focus is on ‘health care’ rather than ‘health outcomes’. An indicator that shows equal health care does not necessarily show health equity. For example, the equality in HbA1c testing between most population groups does not mean diabetes is equitably distributed in our population. In time, we would like to expand our indicator set to illustrate the full health equity landscape.
The Equity Explorer presents data obtained from routine national data sets. Data has been aggregated into relevant population groups for analyses and presentation. At times, the numbers in these groups are too small to calculate age-standardised rates. This has particularly affected Pacific peoples and Asian ethnic groups for non-urban DHBs.
We were not able to look at data outside a national collection, even when it may be collected across the country. For example, we could not include blood test results; we can only include whether a blood test was completed. Agencies such as primary health organisations may find it useful to use the Equity Explorer as a prompt to search their own data (such as blood test results).
In this initial version of the Equity Explorer, we have presented socioeconomic deprivation analyses that show results for each ethnic group, as well as showing results across all ethnicities. This is important because we know different ethnic groups are not evenly spread across the socioeconomic gradient; ethnicity is a confounder of the relationship between socioeconomic variation and health.
The test-of-concept approach to the Equity Explorer means we have learned that not all indicators are ideally suited to equity measurement. In particular, three of the indicators do not have a ‘gold standard’ number, which makes it difficult to state whether a higher ratio is better or worse. These indicators are the diabetic medical/surgical bed-days indicator, the asthma reliever indicator and the asthma preventer indicator. We have included these indicators in the final selection because the numbers are still useful, and because we believe the appropriate quality improvement approach is to share rather than hide this learning.
Finally, the different analytical methods used in the Equity Explorer mean that data is not directly comparable with the Atlas domains, even though the base data set is the same in most cases.
Below is a video about how to use the Equity Explorer, including a case study example from Northland DHB.
What is health equity?
Equity is ‘the absence of avoidable differences among groups of people, whether these groups are defined socially, economically, demographically or geographically’ (World Health Organization).
Health depends on many things, and ‘equal’ health is hard to achieve. Health providers try to provide quality services to all people in their care. However, factors such as age, poverty (deprivation), ethnicity, housing, health care service designs and government policies can all influence health. Within the health care system, factors that affect health include how easy it is to access services, the cost of services, staffing levels, available technology and medicines, and whether services meet the social and cultural needs of their populations.
The World Health Organization believes health equity is about fairness and human rights. Health care equity can include measures around several themes including accessing health care, patient safety, person-centered care, treatment received, quality of care, outcomes of care and underlying determinants of health.
Health equity is different from health equality. Health equality is ‘sameness’. Health equity better recognises that people differ in their ability to attain or maintain health. Consequently, equitable health outcomes may require different (ie, unequal) inputs to achieve the same result (New Zealand Medical Association).
Why has an Equity Explorer been developed?
It is important to measure the variation in health, health care and health outcomes because it helps us know whether services are meeting the population’s needs. Sometimes variation is expected or can be explained: children have fewer hip fractures than elderly people, for example. However, we know a lot of variation is unwarranted and unwanted: this is inequity. We also know inequity can be reduced by careful attention and service changes – but only if we know what things we need to adjust.
This Equity Explorer extends our work on the Atlas of Healthcare Variation. Our 16 existing Atlas domains measure variation across many different conditions, but the equity (or inequity) between different population groups is not easily seen. The aim of the Equity Explorer is to test different methods for showing inequity more clearly.
What are the benefits of the Equity Explorer?
The benefits of the Equity Explorer are:
- the numbers look specifically at the size of the differences between population groups, rather than purely presenting different numbers for different groups
- socioeconomic variation is presented
- data is age-standardised, to allow more robust comparisons between ethnic groups
- testing of the ‘Explorer’ concept means indicators may be extended in the future.
This version of the Equity Explorer was designed to test the new approach, so we have concentrated on information that is most useful to our priority users: DHBs, primary health organisations, health professional groups and health-focused non-governmental organisations.
We used process measures rather than outcome measures because they are more amenable to change by our priority groups.
Questions that might be prompted by this information include the following:
- Why are there differences in health outcomes for different groups of people?
- Does everyone in the DHB have the same access to health care? Within my DHB area, which indicators have the biggest differences? Why?
- Which DHBs seem to be doing better in reducing health inequity and why might that be?
- Are there patterns across indicators, within my DHB?
How to use the Equity Explorer
- Download the Equity Explorer file, which will open in Microsoft Excel.
- Click on the tabs near the bottom of the screen to move between different worksheets in the file. Each worksheet gives a different picture of equity. Use the ‘Contents’ and ‘Help’ worksheets to find your way around.
- In the two ‘Equity within DHB’ worksheets, select the indicators, DHB(s) and years of interest from drop-down menus. The tables and graphs change according to the selection.
- In the ‘Ethnic equity by DHBs’ worksheet, select the ethnic group of interest from the drop-down menu. The tables change according to the selection.
The Explorer can be viewed in conjunction with our diabetes, asthma and gout Atlas domains for useful background information. Note the Atlas numbers are not directly comparable with the Equity Explorer numbers, because we used different methods.
It is also useful to look at the patterns across indicators for a particular area, or over time (where data exists). This avoids a ‘silo’ approach of just looking at one service or indicator at a point in time.
The Equity Explorer is not a DHB competition or league table. It is about quality improvement.
How was the Equity Explorer developed?
The development work was governed by an expert advisory group of 11 people (including consumers and Māori and Pacific health experts), and feedback was invited from relevant health sector organisations.
The Equity Explorer indicators are presented in an interactive Excel file, rather than using the Instant Atlas map-based platform. The Equity Explorer also uses methods of analysis that are more suited to comparing populations: for example, age-standardisation and total response ethnicity classification.
We selected indicators based on a number of criteria, including data availability and suitability, comparability to published Atlas domains, and relevance for health sector providers’ actions.
Further information on our data sources and analytical methodology is available in the technical appendix within the Excel file.
Key findings
For diabetes:
- HbA1c testing showed little inequity between ethnic or socioeconomic groups.
- Some DHBs have inequity in angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) medicine dispensing between ethnic and deprivation groups.
- Māori, Pacific and Asian people with diabetes occupied comparatively more days in hospital compared with European people with diabetes. Likewise, socioeconomically deprived people with diabetes occupied comparatively more days in hospital than socioeconomically advantaged people with diabetes.
- Read more about the diabetes equity indicators.
For asthma:
- Māori, Pacific and socioeconomically deprived children are disproportionately more likely to be admitted to hospital for asthma.
- Asthma reliever inhalers were slightly more likely to be dispensed to Māori and Pacific peoples.
- There was wide variation in the dispensing of asthma preventer medicine between socioeconomic groups in some DHB areas.
- Read more about the asthma equity indicators.
For gout:
- Inequity in allopurinol dispensing for Māori and Pacific peoples persists with age standardised analyses.
- For most DHBs, there was no significant inequity in the rate of non-steroidal anti-inflammatory drug dispensing without allopurinol.
- Māori, Pacific and Asian people with gout received disproportionately more uric acid testing.
- Read more about the gout equity indicators.
Limitations
An ideal equity assessment would need numerous indicators to examine the whole health system. We have focused on process indicators because these are most useful for our priority users. However, this means the focus is on ‘health care’ rather than ‘health outcomes’. An indicator that shows equal health care does not necessarily show health equity. For example, the equality in HbA1c testing between most population groups does not mean diabetes is equitably distributed in our population. In time, we would like to expand our indicator set to illustrate the full health equity landscape.
The Equity Explorer presents data obtained from routine national data sets. Data has been aggregated into relevant population groups for analyses and presentation. At times, the numbers in these groups are too small to calculate age-standardised rates. This has particularly affected Pacific peoples and Asian ethnic groups for non-urban DHBs.
We were not able to look at data outside a national collection, even when it may be collected across the country. For example, we could not include blood test results; we can only include whether a blood test was completed. Agencies such as primary health organisations may find it useful to use the Equity Explorer as a prompt to search their own data (such as blood test results).
In this initial version of the Equity Explorer, we have presented socioeconomic deprivation analyses that show results for each ethnic group, as well as showing results across all ethnicities. This is important because we know different ethnic groups are not evenly spread across the socioeconomic gradient; ethnicity is a confounder of the relationship between socioeconomic variation and health.
The test-of-concept approach to the Equity Explorer means we have learned that not all indicators are ideally suited to equity measurement. In particular, three of the indicators do not have a ‘gold standard’ number, which makes it difficult to state whether a higher ratio is better or worse. These indicators are the diabetic medical/surgical bed-days indicator, the asthma reliever indicator and the asthma preventer indicator. We have included these indicators in the final selection because the numbers are still useful, and because we believe the appropriate quality improvement approach is to share rather than hide this learning.
Finally, the different analytical methods used in the Equity Explorer mean that data is not directly comparable with the Atlas domains, even though the base data set is the same in most cases.
How to use the Equity Explorer
Below is a video about how to use the Equity Explorer, including a case study example from Northland DHB.
Further information
Further technical information, including confidence intervals, is available on request.
Additional resources
- EPiC dashboard: Eight data themes and 29 data stories describing use of medicines by deprivation, ethnicity, gender and age in New Zealand, published by He Ako Hiringa. Data current to last three months. Updated quarterly. Practitioner, practice, and national data: https://epic.akohiringa.co.nz
References
- New Zealand Medical Association. Health Equity Position Statement. Wellington: New Zealand Medical Association. URL:
https://assets-global.website-files.com/5e332a62c703f653182faf47/5e332a62c703f614c82fc548_Health-equity-2011.pdf (accessed 16 May 2016).
- World Health Organization. Equity [webpage]. Geneva: World Health Organization. URL: https://www.who.int/health-topics/health-equity#tab=tab_1 (accessed 21 October 2015).
Published: 29 Oct 2021
Modified: 16 Jan 2024
