The development and validation of a “Virtual

Diabetes Register” (VDR) for monitoring

diabetes prevalence and the quality of

diabetes care in New Zealand

• Emmanuel Jo1, Paul Drury2,

• 1.New Zealand Ministry of Health,

2.Auckland Diabetes Centre and New Zealand Society for the

Study of Diabetes

What is Diabetes Mellitus (DM)

• DM defines a condition of a person having too

much glucose (sugar) in the blood.

• This is because the pancreas cannot make

enough insulin.

• Simply, the body can not control glucose level

Importance of DM patient care

• DM patient care is very important as DM

can cause further complications, leading to

more health expenditure

Picture source: http://scientopia.org, http://diabetes.webmd.com, http://healthlineinfo.com

Complications of diabetes

• Eyes - blindness

• Kidneys - dialysis

• Amputation of feet

• Men's sexual health

• Women's sexual health

• Diabetes-specific skin conditions

• General skin conditions

• Gum, mouth and teeth problems

• Nerve damage (neuropathy)

• Heart and blood vessel problems

• Thyroid

What we knew about DM prevalence

prior to 2008/09

• About 100,000~300,000 DM patients in New

Zealand (depends on which survey)

• Maori/Pacific are about 10 years earlier to have

diabetes than others in New Zealand

What MOH does for DM?

• Ministry of Health (MOH) set targets for each

local *District Health Board (DHB).

• The percentage of free annual diabetes checks

is defined to be a measure of access to good

quality care for Diabetes Mellitus (DM) patients.

• It monitors the level of glycosylated hemoglobin

(HbA1c; a measure of diabetes management)

and fasting lipid test (a measure of

Cardiovascular Disease (CVD) risk)

How to measure?

Rate(DHB)% DM100patientDM ofNumber

checkedpatient DM ofNumber

Health Survey

How the result of the survey used

National DM Rate

(by age and ethnicity)

x Local DHB Population

(by age and ethnicity)

Estimated Local DM population

=

Maori Pacific Other

DHB1 57 32 146

DHB2 64 36 106

DHB3 80 41 126

DHB4 73 42 112

DHB5 50 43 189

DHB6 37 39 126

0%

20%

40%

60%

80%

100%

120%

140%

Ge

t C

hec

ke

d a

s a

% o

f e

sti

ma

ted

nu

mb

er

w

ith

kn

ow

n d

iab

ete

s

DHB

Diabetes Get Checked Rate by DHB 2007/08

Pacific

Over 100% ?

What MOH wanted

• New Zealand wished to establish a

database where individuals can be located

so that it can reveal specific data from the

pool of data set

Searching for data

• National Minimum Data Sets (Inpatient)

• National Non-Admitted Patient Collection

(Outpatient)

• Primary Health Organisation Enrolment

Collection (PHO Enrolment)

• National Health Identifier (NHI)

• Pharmaceutical Collection (PHARM)

• Laboratory Claims Collection (LAB) • PHARM and LAB data accessed via SAS access to Oracle module

VDR methodology

• Regards as having diabetes if:

Admission coded as diabetes

Hospital OP visit for diabetes or diabetes education,

Retinal screening performed

On insulin, metformin, sulfonylureas (at least 2 scrips)

Exclude women age 12 and 45 taking metformin but no other medication (PCOS)

At least 4 HbA1c in past 2 years (must have ACR as well if that only evidence)

• Cut off is data up to 31 Dec, thus available about mid-March/April for

previous year

• Criteria on validation appear ca 95% specific but probably ca 90%

sensitive

The VDR concept diagram

Hospital

admissions with

DM

National Health Index

(Demographic information)

Primary Health

Organisation

(PHO)

enrollment

Virtual Diabetes Registry (VDR)

NHI Duplication Checks

DM patient selection filter

Outpatient

medical DM

Outpatient

nursing DM

education/mana

gement

Outpatient DM

retinal screening

Pharmaceutical

metformin only

Pharmaceutical

non-metformin

DM medication

Pathology tests

claims

HbA1c>=4 for

last 2years

Pathology tests

claims

ACR test >=1 for

last 2years

Result

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

00-0

4

05-0

9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85+

Pre

va

len

ce

ra

te

Age

New Zealand Diabetes Prevalence Rates1 January 2010: PHO enrolled population

New Zealand

Diabetes Prevalence Rates

1 January 2010: PHO enrolled population

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

00

-04

05

-09

10

-14

15

-19

20

-24

25

-29

30

-34

35

-39

40

-44

45

-49

50

-54

55

-59

60

-64

65

-69

70

-74

75

-79

80

-84

85+

Age

Pre

vale

nce r

ate

European/Other

Mäori

Pacific people

Indian

20+ years

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Rate

(B

ase=

Pra

cti

ce e

nro

lled

po

pu

lati

on

)

Age group

New Zealand Diabetes Prevalence Rate as of 31 Dec 2011

European/Other Mäori Pacific people Indian

Unpublished data (Drury & Jo)

Direct same-scale comparison of prevalence 2005 & 2011

Unpublished data (Drury & Jo)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

00

-04

05

-09

10

-14

15

-19

20

-24

25

-29

30

-34

35

-39

40

-44

45

-49

50

-54

55

-59

60

-64

65

-69

70

-74

75

-79

80

-84

85

+

Age group

New Zealand Diabetes Prevalence Rate as of 31 Dec

2005

European/Other

Mäori

Pacific people

Indian

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

00

-04

05

-09

10

-14

15

-19

20

-24

25

-29

30

-34

35

-39

40

-44

45

-49

50

-54

55

-59

60

-64

65

-69

70

-74

75

-79

80

-84

85

+

Age group

New Zealand Diabetes Prevalence Rate as of 31 Dec

2011

European/Other

Mäori

Pacific people

Indian

New Zealand Virtual Diabetes Register end-2005 to end-2011

Increase is in both genders,

also across all ethnicities

Unpublished data (Drury & Jo)

0%

1%

2%

3%

4%

5%

6%

7%

8%

No

rthlan

d

Waite

mata

Au

ckland

Co

un

ties

Man

ukau

Waikato

Lakes

Bay o

f Ple

nty

Tairawh

iti

Haw

kes Bay

Taranaki

Mid

Ce

ntral

Wh

angan

ui

Cap

ital and

Co

ast

Hu

tt

Wairarap

a

Ne

lson

Marlb

oro

ugh

West C

oast

Can

terb

ury

Sou

thC

ante

rbu

ry

Sou

thern

Diabetes prevalence rates by DHB of domicile

VDR Dec 2011 VDR Dec 2009 VDR Dec 2007 VDR Dec 2005

Unpublished data (Drury & Jo)

Diabetes prevalence rates

by Deprivation

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

1 2 3 4 5 6 7 8 9 10

Deprivation

Dia

bete

s p

revale

nce r

ate

• An example of VDR application

5.0 4.0 3.0 2.0 1.0 0.0 1.0 2.0 3.0 4.0 5.0

00-14

15-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

Risk ratio

Ag

e g

rou

p

Mortality Risk Ratio (DM/non DM)

Mortality Risk Ratio - Male Mortality

An example of VDR application

ACS admission rate for people in VDR vs not in VDR

in 2008/09 for age 35-84

0.000%

0.200%

0.400%

0.600%

0.800%

1.000%

1.200%

1.400%

1.600%

1.800%

Conditional Probability: P(ACS patients/non VDR PHO population)

Conditional Probability: P(ACS patients/VDR PHO population)

4.1x more chance to have one

or more ACS admissions than

those who not exist in the VDR

An example of VDR application

30 days mortality rate after the last hospital discharge

in 2007/08

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

20.00%

00-0

4

05-0

9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85+

Age

1 y

ear

mo

rta

lity

ra

te

Patients exist in the VDR

Patients not exist in the VDR

How the VDR is used

• The VDR is recognised as the official diabetes

prevalence for New Zealand by NZSSD and

MOH

• Use SAS and SAS Add on for Microsoft Office

(AMO) to share the data within MOH in a data

cube form

• The patient level VDR return to their DHB for

monitoring patient’s DM care in PHO level

• We are thinking about sharing VDR cube with

DHB via SAS AMO in the future

SAS AMO for VDR

Conclusions

• Superior method involves the whole diabetes population in comparison to sampling used in other national surveys

• The central authority monitors and local primary care organizations can monitor

• Very accurate and robust: reveal the true representation

• The VDR is the best option to monitor diabetes prevalence unless the national diabetes registry is established.

• The VDR is invaluable for monitoring national prevalence and supporting clinical quality improvements.

• The VDR is readily applicable to other areas to investigate the correlation between the two or amongst many other factors

• SAS has been the key tool to develop and share the VDR in very effective way