Approaching the immunisation target: Insights into ‘Partially immunised’ and ‘Declined’

Sarah Radke Research Fellow - Epidemiologist Lynn Taylor National Manager Research &

InnovationUniversity of Auckland

IMAC Conference 2015, Hamilton

Introduction

93% fully immunised at 8 months of age Approx.. 3.5% are ‘not fully immunised’ Approx.. 3.5% are coded as ‘decline’

Extension of “Translating best practice research to reduce equity gaps in mmunisation” Part 1: Analysis of NIR data – partial immunisation Part 2: Practice interviews – decline Part 3: GeoMapping exercise (not presented

today)Funded by Health Research Council of NZ

Objectives – part 1rtial immunisatione data from the National Immunisation Register (NIR) to ntify and compare children with records indicating:

• Selective immunisation by opting out of specific vaccines

• Incomplete immunisation by not completing all doses

tterns of decline e data from the National Immunisation Register (NIR) to antify children with vaccination status=‘declined’se this information to enable development of better understanding of

Objectives – part 2cus on decline immunisationserview selected practices to gain an understanding of what ds to a child being coded as ‘decline’ in the electronic PMS:

• The challenges of the local population

• The common systematic approaches taken at the general practices

se this information to enable development of better vaccination strategies

CHARACTERISING PARTIAL MMUNISATION IN NEW

ZEALAND

arah Radke

Methods

udy population– all children who were less than two years old

between 01 January 2010 and 31 December 2013; and

– were enrolled on the NIR

Exclusions• children whose parents ever elected to have their

information opted off the NIR• children who died prior to their second birthday • children with a record of any vaccine given overseas• children with inexplicable or erroneous information

Methods

ta sources– NIR records through 31 December 2013

• If status field=“completed” we considered corresponding vaccine injection to be received

• Otherwise we considered corresponding vaccine injection not to be received

– If status field=“declined” we considered vaccine injection actively declined versus simply not being received

– National Health Index (NHI) database

I numbers were encrypted and used to link the two data t th i di id l l l

MethodsNational Immunisation Schedule

Infanrix‐hexaPCV

Infanrix‐hexaPCV

Infanrix‐hexaPCV

MMRHibPCV

6 doses by 5 months of age

MethodsPartially immunised

Received some but not all age‐appropriate 

doses

UnimmunisedReceived no doses

Fully immunisedReceived all age‐appropriate doses

DeclinedAt least one record 

with status of ‘declined’

No records of immunisation

Selectively immunisedeceived no doses for at least one vaccine but received at 

least one dose for the remaining vaccines

completely immunisedeived at least one dose for ach vaccine but did not mplete all vaccine series

Methods

alysis– We compared demographic characteristics between

groups• Pearson’s chi-square test for categorical variables • Wilcoxon two-sample test for continuous variables. • All tests for assessing statistical significance were two-sided with

α=0.05.

– We identified independent predictors• multivariable log-linear binomial regression• backwards elimination, removing covariables from the model in order

of p-value magnitude• final predictive model based on a p-value of less than 0.05.

– 3 age cut-offs

Results

Immunisation status (%) 2010 2011 2012 2013

Total (N) 62,610 61,892 60,059 60,053

Unimmunised 4.78 4.20 3.76 3.21Partially immunised 11.77 10.61 9.34 6.30Fully immunised 83.45 85.19 86.89 90.49

mmunisation status by year of 8 completed months of age

Results

Immunisation status, 2013

not receive…fanrix‐hexa (n=28)CV (n=224)

Resultsdependent predictors of incomplete immunisationeristic (%)

Selectively immunised

Incompletely immunised

RR (95% CI) P‐value

ypean  76.19 31.24 1.00 <0.001ri 15.87 41.65 1.13 (1.10, 1.16)ic 2.78 14.86 1.13 (1.11, 1.17)n 3.97 10.53 1.13 (1.10, 1.16)er 1.19 1.61 1.11 (1.05, 1.17)of residencehern 28.17 45.98and 29.76 25.69ral 18.25 13.87hern 23.81 14.09rivation Index

17.93 9.07 1.00 0.01123.51 11.59 1.05 (1.01, 1.08)

Results

‘decline’ records 2010 2011 2012 2013

Total 2,993 2,601 2,261 1,926

None 51.75 47.37 41.97 27.731‐8 doses 26.56 28.10 30.08 36.609 doses 16.61 16.57 19.55 22.90>9 records 5.08 7.96 8.40 12.77

‘Decline’ records among unimmunized children, by year of eight completed months of age

Conclusion

Down to small numbers each vaccine dose delivered requires more resources compared to when coverage was lower

To continue making progress towards and above 95% argets, more information is needed about those not ully immunised

That information should be timely – 2013 info too old to be useful now MoH should incorporate breakdowns nto their quarterly coverage reports – Additional data could be incorporated (e.g. eligibility for

outreach services, immigration data, etc.)

That information should be used to inform strategy

THE CHALLENGES AND NSIGHTS INTO “DECLINE”

ynn Taylor

MethodsNIR reports 

(12 month reporting to 30 Nov 2014)Exclude if < 10 eligible children

Rank top 40 HIGH decline rate  (2 x national average) for milestone ages of 6m, 8, 12m 

24m)

Exclude those in known ‘anti‐immunisation’ areasFinal list approved by Ministry of Health

HIGH decline practices invited to participateLOW decline practices ‘matched’ by DHB and PHO 

f d i i

NTIFY

VITE

LECT

ANK

Recruitment

HIGH(Target 20)

30 invited

21   Interviewed5   Declined 5 No response

LOW(Target 20)

20 invited

14   Interviewed5   Declined 1 No response

No LOW comparator for 7 practices

HIGH decline ratePractice ID code

LOW decline rateReason no comparator practice was matched

7 and 8 No comparator practices identified with LOW decline rates

17 Two potential comparator practices identified ‐ Declined to participate

18  and 20 One potential comparator practice identified – No  response to follow up

19 and 21 One potential comparator practice identified – Declined to participate

Findings – Local population

efs• Natural lifestyles• Religious persuasion• Lobbyists• Misinformation and own ‘research’

xiety• Fear • Influence of family / friends

ctical challenges• Earthquake• Living remotely• Transient life

Findings – Influencers

ommunity:• Midwives

• Early learning centres, childcare centres

• Coffee groups

ocial media:• Facebook

• You Tube

Findings – Doctors and Nurses

erience• In many “LOW” decline practices, Doctors been in practice many

years• Nurses were mothers themselves• Relationship important• Sharing knowledge about diseases

dical contra-indications• Not common in any practice (LOW or HIGH)• Generally only delay if fever > 37.5C

Findings – Practice systems & processes

ecline policy of practice:• Use of decline form• Process for informed discussion• Open door• Use of OIS• Process for coding decline in PMS

rly enrolment All “accept” nomination if family knownf not known would “reject” or leave in inbox

Would not code as “Decline”

Conclusions

Some people are very firm in their decision to ‘Decline’ due to firmly entrenched beliefs

Some people are influenced by peers in their community and their own “research”

Practice staff “relationship” with the parent is important

Practice systems and processes are

Overall summary & recommendations

NZ has a wealth of data – let’s use it!

nvesting our time and resources wiselyCreate public awareness before new vaccines are launchedUse social media as that is where the parents are looking for their info!

Questions?AcknowledgementsNikki Turner Director (IMAC, UoA)Lynn Taylor National Manager – Research & Innovation (UoA)Sarah Radke Research Fellow – Epidemiologist (UoA)Angela Chong Project Manager (UoA)Barbara Horrell Contract researcherNadia Charania Lecturer Dept Public Health (AUT)Dr Janine Paynter Data Manager (UoA)Dudley Gentles Data Manager (UoA)Dr Dan Exeter Senior Lecturer in Epidemiology (UoA)Jinfeng Zhao Research Fellow in Geographic Information Science (UoA)Joanna Stewart Senior Research Fellow in Epidemiology & BioStatistics (UoA)Suryaprakash Mishra Senior Advisor - Epidemiology, National Immunisation ProgrammeDr Pat Tuohy Chief Advisor - Child & Youth Health (MoH)Rachel Webber Senior Advisor Immunisation - Infant Immunisation (MoH)Interview participants General practices