Diabetes single map PHO analysis Consumer summary (160KB, pdf)

The goal of this Atlas of Healthcare Variation domain is to investigate the quality of care provided to people with diabetes. The data is not intended to form the basis for judgement or definitive statements of quality, rather they are intended to raise questions about potential areas for quality improvement. The indicators were developed with the assistance of an expert advisory group.

2017 revision of Virtual Diabetes Register (VDR)

In 2016 the Ministry of Health worked with a range of experts to update and improve the VDR algorithm to estimate diabetes prevalence more accurately.[1] The revised VDR algorithm, based on a detailed comparison with diagnostic laboratory data, appears to have a specificity of around 97 percent and sensitivity of around 87 percent. The revised VDR gives estimates around 10 percent lower than the old version, and figures based on the latter should no longer be used. More information is available at: www.health.govt.nz/our-work/diseases-and-conditions/diabetes/about-diabetes/virtual-diabetes-register-vdr.

In order to keep a consistent time series, historical versions of the VDR have thus been re-extracted using the updated algorithm. For further information, or if you want updated VDR data please email data-enquiries@moh.govt.nz.

Update to include 2017 data

(Data updated September 2018)

This Atlas domain has been updated using data from the updated VDR for 2015–17.

Key messages

  • The new algorithm estimates around 236,000 people had diabetes in 2015, 241,000 in 2016 and 246,000 in 2017. The previous VDR estimated 260,050 people with diabetes in 2015 (see above for further information about the VDR update).
  • In 2017, age-specific rates of diabetes prevalence varied more than two-fold by DHB, from between 10 percent and 25 percent of a DHB population aged 65–74. Prevalence varies by ethnicity, with Pacific peoples of all ages experiencing the highest prevalence.
  • The regular use of medicines for glycaemic control (insulin or metformin) varied 1.4-fold by DHB, from between 47 percent and 68 percent of those with diabetes regularly receiving insulin and/or metformin in 2017.
  • The percentage of bed-days occupied by people with diabetes increased with age, peaking in the 65–74 age group. In this age group the differences between ethnicities are highlighted, for example, Pacific peoples at 51 percent compared with European/other at 19 percent.

Key findings

Diabetes prevalence is markedly higher in some population subgroups than in others

The prevalence of diabetes increased significantly with age, from a mean of 0.3 percent in those aged 0–24 years to 17 percent in people aged 75 years and older.

Pacific peoples had a significantly higher prevalence of diabetes than all other ethnic groups, while those identifying as European/other had significantly lower rates of diabetes. People of Indo-Asian ethnicity are not presented separately here; however, rates of diabetes in these populations are close to those observed in Pacific peoples.

Good glycaemic control and cardiovascular risk factor management are important for outcomes

If HbA1c does not meet an agreed target with dietary and lifestyle changes, drug therapy is recommended. Insulin and metformin are well proven. Evidence suggests good glycaemic control benefits microvascular outcomes.[2] The provision of comprehensive cardiovascular risk management for people with diabetes (such as blood pressure and lipid management) has been shown to improve macrovascular outcomes substantially while good glycaemic control has a smaller and very delayed effect. 

Insulin and metformin use varied

Given both the lack of available data on clinical parameters and the inability to split by the type of diabetes, these indicators of medication use are not intended to suggest an ‘ideal’ rate of use, rather they provide a high-level view.

Wide variation may raise questions such as do DHBs with lower than average rates of medication use have lower or higher rates of diabetes complications?

Without Hba1c results available, nationally, 61 percent of people with diabetes aged 25 years and over regularly received insulin and/or metformin, with use highest in those aged 65–74. This varied 1.4-fold by DHB for all ages, ranging from 47 percent to 68 percent.
Metformin remains the standard initial drug treatment for type 2 diabetes. As expected, use increased with age. On average, 28 percent of people with diabetes aged 25–44 regularly received metformin compared with 58 percent of those aged 65–74.

On average, 22 percent of people with diabetes regularly received insulin. As might be expected, insulin use was highest in the 0–24-year age group with diabetes, with 63 percent of these regularly dispensed insulin.

Intensive management of high blood pressure and microalbuminuria

On average, 48 percent of people with diabetes received angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB) medicines. This varied 1.2-fold by DHB, ranging from 43 percent to 56 percent. Intensive management of blood pressure and microalbuminuria is recommended to prevent progression of renal disease in diabetes. ACEI and ARB are first-line treatments for raised blood pressure and/or microalbuminuria.

The younger the age at diagnosis, the greater the impact of diabetes on life expectancy, highlighting the importance of glycaemic control, blood pressure management and prevention of kidney disease in younger people with diabetes.

Māori and Pacific peoples have a higher rate of ACEI or ARB use at a younger age, however some data also shows that Māori and Pacific peoples have significantly higher rates of end-stage renal disease. A recent publication found Māori and Pacific peoples have a relative risk of 6.48 for developing end-stage renal disease due to type 2 diabetes compared with other New Zealanders.[3]

Complications – admissions for diabetic ketoacidosis and hypoglycaemia varied by age

Note data from 2011 is presented for these indicators because it was not affected by the update to the VDR.

Nationally, the rate of admissions to hospital for diabetic ketoacidosis were 10-fold higher in those aged 0–24 years than all other age groups. Whilst the count of admissions for hypoglycaemia were highest in those aged 65 years and over, the rate was highest in the youngest age group. The numbers in each age group were too low to report by DHB.

Complications – lower-limb amputations increase with age

Lower-limb amputation rates increased significantly with age, with 95 percent of amputations occurring in those aged 45 years and over. This rare complication affected only 0.21 percent of the diabetes population in a year.

Note that this indicator counts people with diabetes who had one amputation or more in a year. The VDR is a register so people who died during the year are excluded. This means that people who had an amputation during the year and died are not included here. The data is available on request: data-enquiries@moh.govt.nz.

People with diabetes occupied more bed-days for any reason

The number of medical and surgical bed-days occupied by people with diabetes was compared with the total occupied medical and surgical bed-days. Age had a significant effect on occupied bed-days. In 2017, age-specific rates varied over two-fold. For example, people with diabetes aged 45–64 years occupied 22 percent of total bed-days, compared with a population prevalence of 8.2 percent of people with diabetes in this age group.

On an unadjusted basis, people with diabetes occupied 17.8 percent of total bed-days, despite a population prevalence of diabetes of 5.3 percent. However, some of the differences here are partially explained by the fact that increasing age is strongly associated with bed-day use and the age structure of people with diabetes is older than the general population. However, the extent of the bed occupancy remains large.

People of Māori, Pacific and Asian ethnicities with diabetes occupied significantly more bed-days than those in the European/other ethnic group – 25 percent on average compared with 15 percent.

Regular laboratory testing was lowest for screening renal disease (ACR)

People with diabetes who received one or more laboratory tests in a year for haemoglobin A1c (HbA1c), albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) was analysed. On average, 87 percent received an HbA1c test, 66 percent an ACR test and 84 percent an eGFR test.

Rates differed by ethnicity for certain tests. This was evident in ACR testing, with European/other and Māori receiving 63 percent on average compared with Asian and Pacific who received 74 percent on average.

Table 1 shows the percent of people with diabetes receiving all three tests by age and ethnic group (2017).

Table 1: Percentage of people with diabetes receiving all three tests by age and ethnic group, New Zealand, 2017

  Age group (%)
Ethnic group 25–44 45–64 65–74 75+ Total
Māori 48.8 63.4 68.0 62.0 60.7
Pacific peoples 61.0 75.3 78.3 69.4 72.4
Asian 56.8 75.9 76.5 69.6 72.0
European/other 46.2 60.9 66.7 59.0 60.0
Total 51.6 66.3 69.5 60.8 63.5

Questions raised:

  • How many of these results can be explained by the predominant type of diabetes?
  • Are rates for specific indicators lower or higher than might be expected?
  • Is there room for improvement in any of these indicators?
  • Do results reflect local differences in care?

Method and data source

This domain draws on data contained in the VDR, which was developed by the Ministry of Health to estimate and track the number of people diagnosed with diabetes. The registry combines and filters various sources of health information, including the National Minimum Dataset, the National Non-admitted Patients Collection (outpatients), the Pharmaceutical Collection, the Laboratory Claims Collection and the Primary Health Organisation Enrolment Collection. The registry was used to estimate the prevalence of diabetes. The data is based on health service utilisation data that is consistent with diabetes care rather than formal clinical diagnosis or laboratory results, so should be interpreted with some caution. The Atlas does not use any patient-identifiable data.

The methodology is available here (154KB, PDF)


The Pharmaceutical Collection contains claim and payment information from community pharmacists for subsidised dispensing. This collection does not indicate whether a medicine was taken or whether the dose was effective. Over-the-counter medicines are not included.

In selecting indicators for oral hypoglycaemic medication use, the group decided to focus only on metformin, as the first-line agent for people with type 2 diabetes and insulin as the key medication for people with type 1 diabetes. There is no ideal rate of medicine use in people with diabetes because it depends on clinical need, however, wide variation between DHBs or ethnic groups raises questions as to why the rate of medicine use varies.

The Laboratory Collection includes tests performed in the community. The exclusion of hospital and point-of-care tests will under-count testing and may affect results more in some DHBs than in others.

Analysis does not split by type of diabetes

There were some limitations as to what measures could be presented. It was not possible to reliably split people by type of diabetes; hence the indicators represent a combination of those with type 1 and type 2 diabetes. Generally, most people with diabetes aged 0–24 years will have type 1 diabetes, while around 90+ percent of those aged 25 years and over are expected to have type 2 diabetes.

The method used in the VDR to identify people with diabetes is less accurate at identifying children than adults with diabetes. A recently published survey highlights that local DHB data may be a better source for identifying prevalence in children.[4] Additional work is in hand.

Some important outcome indicators could not be included

Limitations of currently available data mean it was not possible to explore certain outcome indicators, including screening for diabetic retinopathy, retinopathy rates and end-stage renal failure. Outcome indicators, including myocardial infarction rates, stroke and other cardiovascular outcomes, are not included in this iteration of the diabetes Atlas, but are likely to be included in future updates. Users are warmly encouraged to investigate local data in relation to these outcomes to promote improvement and equity initiatives at PHO and practice level.

Relationship to other Ministry of Health activities

The diabetes Atlas links with the current (2015–20) strategy for diabetes, Living Well with Diabetes,[5] which provides an overall package of measures to improve care for people with diabetes in New Zealand. This includes work towards each DHB meeting the 20 Quality Standards published in 2014 (with an accompanying toolkit).[6] The standards link with many of the measures presented in the diabetes Atlas so the two are complementary.


  1. Chan W, Papaconstantinou D, Lee M, et al. 2018. Can administrative health utilisation data provide an accurate diabetes prevalence estimate for a geographical region?  Diabetes Research and Clinical Practice 139: 59–71.
  2. Ministry of Health. 2018. Cardiovascular Disease Risk Assessment and Management for Primary Care. Wellington: Ministry of Health.
  3. Hill K, Ward P, Grace BS, et al. 2017. Social disparities in the prevalence of diabetes in Australia and in the development of end stage renal disease due to diabetes for Aboriginal and Torres Strait Islanders in Australia and Maori and Pacific Islanders in New Zealand. BMC Public Health 17(1): 802.
  4. Jefferies C, Owens N, Wiltshire E for the Clinical Network for Children with Diabetes in New Zealand, on behalf of the Paediatric Society of New Zealand diabetes clinical network. 2015. Care for children and adolescents with diabetes in New Zealand District Health Boards: Is the clinical resourcing ready for the challenge?  NZMJ 128 (1424) 20–7.
  5. Ministry of Health. 2015. Living Well with Diabetes: A plan for people at high risk of or living with diabetes 2015–2020. Wellington: Ministry of Health.
  6. Ministry of Health. 2014. Quality Standards for Diabetes Care Toolkit. Wellington: Ministry of Health.

Recommended reading/suggested links

Last updated 11/10/2019