The South Australia

Early Childhood Data Project (SA ECDP)

John Lynch

Professor of Epidemiology and Public Health

University of Adelaide

Adult social and health

disadvantage

Labour market and income

disadvantage

Child health disadvantage

birth

Developmentaldisadvantage

0-2

Early learning disadvantage

3-5

Educationaldisadvantage

6-17

Adult social and health

disadvantage

Inter-generational social and health inequality

Early Childhood Systems

Health Education

- 9 months 0 1 2 3 4 5 6 …

Healthy BirthHealthy ChildImmunization

Maternal Health

HealthyPregnancy

Feeding, GrowthSleeping, Settling, Attachment

Child careLanguage

Reading

PreschoolSelf regulation

Play

LiteracyNumeracy

Cognitive abilitySocioemotional development

HearingVision

Child Development

The Early Childhood Government ‘System’

Child Protection

Child Protection

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EMPOWER CREHealth systems, disadvantage and child well-being

CIA Lynch Epidemiology Public HealthCIB Sawyer Child psychiatry Robinson Research InstCIC Mol OBGYN Robinson Research InstCID Roberts Placental physiology Robinson Research Inst CIE Dekker OBGYN Robinson Research Inst CIF Stocks GP MedicineCIG Schurer Economics U SydneyCIH Gurrin Biostatstics U MelbourneCII Dwyer CE, SA Women’s and Children’s Health NetworkCIJ Director, SA Child and Family Health Service

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Interventional Epidemiology

Platform 2: Follow-up & Scale-upWhole-of-population linked data for

children in SA and NTN~ 300,000

Platform 1: Pragmatic RCTs and Natural Experimentsin pregnancy, postnatal and community-based care

Platform 4: Methodology CoreRisk Stratification

Simulation of RCTs in observational dataCausal mediation analysis

Human capability production functionCost:Benefit analysis

Platform 3: Cohort Simulation of RCTs & Risk StratificationCohorts include - SCOPE; LSAC; LSIC; HILDA (Aus)

ALSPAC, MCS (UK)

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Platform 2

Data Linkage

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SA Early Childhood Data Project

• Every complete birth cohort

• Born 1999-2014

• N = ~ 300,000 children

• N = ~ 12,000 Aboriginal children

• Over 7 million records

• ~ 20 different government sources

• Public good resource - ~ 20 approved

researchers including within government

SA PoliceDASSACAMHS

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Perinatal Epidemiology

Potentially Preventable

HospitalisationsService Change

One Platform Multiple purposes

Less More “translational”

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Standard Epidemiological Research Outputs

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Anemia in Pregnancy and AEDI Vulnerability (N = 13,654 imputed)

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

UnadjustedAdjusted*

* Adjusted for twin, maternal age, smoking in pregnancy, no. antenatal visits, parity, inter-pregnancy interval, maternal occupation, paternal occupation, Aboriginal or Torres Strait Islander status, remoteness, SEIFA-IRSD.

Smithers et al. Pediatric and Perinatal Epidemiology (2014)

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Gestational Age (weeks) and AEDI vulnerability at age 5 (N = 12,601)

0.8

1

1.2

1.4

1.6

1.8

2

2.2

37 38 39 40 41 42-45

CommunicationEmotionalLanguagePhysicalSocialOne or more

Weeks of gestation

Adju

sted

ORs

37 weeks: 7%38 weeks: 20%39 weeks: 23%

40 weeks: 37%41 weeks: 13%42-45 weeks: 0.7%

Smithers et al. BJOG (2015)

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More “Translational” Research Outputs

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Infographic that accompanied release of the Nyland Commission Report

BetterStart Research Report March 2017

AGE

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

age 0 1 2 3 4 5 6 7 8 9 10

Cumulative Incidence of Child Protection Contact Types (1999 – 2015)Denominator = Total Population of SA Children (~128,000)

1 in 4 childrenby age 10

Notification

Screened in

Investigation

Substantiation

Out-of-Home-Care

2% or 1 in 50 children by

age 10

What does this look like for the rest of Australia?

2010

“…slightly more than 1 in 4 (26.7%) of all NSW children and young people under the age of 18 were ever reported to Community Services by the end of 2008/09.”

“…two in 100 NSW children and young people currently under the age of 18 had ever lived in OOHC by the end of 30 June 2009.”

2012

“The likelihood that a child born in 2011 will notified by the time they are aged 18, is 23.5% - slightly less than 1 in 4…”

2013

The number of children known to Child Safety Services… 1 in 4.2 of all Queensland Children and 1 in 1.6 Aboriginal and Torres Strait Islander children”

2016

“By 11 years of age, 7.8% of Aboriginal children had entered out-of-home-care compared to 0.96% of non-Aboriginal children”

1.4% of all children will have experienced OOHC by age 10

2008

By age 16, 22.5% of children born in 1991 were subject to at least one child protection notification

BetterStart Child Health and Development Research Group | http://health.adelaide.edu.au/betterstart/

UK1.8% of all children born 2001-2003 experienced OOHC by age 10 (Mc Grath-Lone, 2016)

France1.9% of all children experienced OOHC by 2011( Seraphin, 2017)

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The cumulative incidence of contact with the child protection system in South Australia by age 10

What’s happened over time?

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0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Cum

ulat

ive

inci

denc

e (%

)

Age (years)

Cumulative incidence of notifications to the child protection system by age and year of birth, 1999-2005

1999

2000

2001

21

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Cum

ulat

ive

inci

denc

e (%

)

Age (years)

Cumulative incidence of notifications to the child protection system by age and year of birth, 1999-2005

1999

2000

2001

2002

2003

2004

22

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Cum

ulat

ive

inci

denc

e (%

)

Age (years)

Cumulative incidence of notifications to the child protection system by age and year of birth, 1999-2005

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

23

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Cum

ulat

ive

inci

denc

e (%

)

Age (years)

Cumulative incidence of notifications to the child protection system by age and year of birth, 1999-2005

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

1999: 3% <1

2013: 8% <1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

age 0 1 2 3 4 5 6 7 8 9 10

Notification Screened in notification Investigation Substantiation Out of home care

Cumulative Incidence of Child Protection Contact Types (1999 – 2015)Denominator = Number of Children Notified to Child Protection (n=33,235)

First 1400 days 44%

46%

56%

51%

62%

16% < 1

No contact with Child Protection

1+ contact, not screened-in

1+ screened-in contact, no

investigation

1+ investigation,

no substantiation

1+ substantiation,

no out of home care

1+ out of home care

episodeTotal

N (column %) N (column %) N (column %) N (column %) N (column %) N (column %) N (column %)Physical health and wellbeing

Not vulnerable 12,578 (92.8) 782 (82.7) 846 (80.6) 349 (75.7) 254 (67.9) 121 (68.0) 14,930 (90.2)

Vulnerable 975 (7.2) 164 (17.3) 203 (19.4) 112 (24.3) 120 (32.1) 57 (32.0) 1,631 (9.8)

Social competence

Not vulnerable 12,524 (92.4) 774 (81.9) 840 (80.1) 340 (73.7) 284 (75.9) 116 (64.8) 14,878 (89.9)

Vulnerable 1026 (7.6) 171 (18.1) 209 (19.9) 121 (26.3) 90 (24.1) 63 (35.2) 1,680 (10.1)

Emotional maturity

Not vulnerable 12,413 (92.0) 774 (82.3) 845 (81.0) 346 (75.2) 290 (78.4) 116 (65.9) 14,784 (89.7)

Vulnerable 1076 (8.0) 166 (17.7) 198 (19.0) 114 (24.8) 80 (21.6) 60 (34.1) 1,694 (10.3)

Communication and general knowledge

Not vulnerable 12,698 (93.7) 821 (86.8) 898 (85.6) 385 (83.7) 295 (78.7) 144 (80.9) 15,241 (92.0)

Vulnerable 853 (6.3) 125 (13.2) 151 (14.4) 75 (16.3) 80 (21.3) 34 (19.1) 1,318 (8.0)

Language and cognitive skills

Not vulnerable 12,931 (95.6) 841 (89.3) 918 (87.8) 376 (81.7) 281 (75.7) 142 (79.3) 15,489 (93.7)

Vulnerable 601 (4.4) 101 (10.7) 128 (12.2) 84 (18.3) 90 (24.3) 37 (20.7) 1,041 (6.3)

Total* 13,532 (100.0) 942 (100.0) 1,046 (100.0) 460 (100.0) 371 (100.0) 179 (100.0) 16,530 (100.0)

Developmental vulnerability at age 5 on the Australian Early Development Census- All children

*Total numbers vary across domains due to differing response rates

~ 3 times higher vulnerability

~ 2 times higher vulnerability

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0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Other Govt Anonymous Child Care FSAFamily/Friend/Neighbour Family Law system Health Non-GovtOther Police School/preschool Self report/Unknown

Pattern of reporters to child protection system by age of the child

40%

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A Public Health Approach

To Early Intervention

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1,364 childrennot screened in

1,649 childrennot investigated

829 childrennot substantiated

4,700 children in every birth cohort~25% of children

At least 1Notification

SA Population by age 10

(20,000 births per year)

3,842 children per birth cohort (~80%)no further action by

child protection agency

3,336 children in every birth cohort~19% of children

Screened inNotification

1,687 children in every birth cohort~10% of children

Investigated

858 children in every birth cohort~5% of children

Substantiated

Out-of-home Care

355 children in every birth cohort~1.8% of children

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Whole-of-Population Data Linkage – South Australia(Health, Welfare, Justice, Child Protection, Education…)

Service Delivery – Evaluationsincluding services offered by Government and NGOs

Federal Government Data(AEDC, Centrelink, PBS, MBS … Census)

Pragmatic RCTs - Innovations

SA Early Childhood Data Project – Information, Evaluation, and Innovation

Integrated research information system + government ‘business intelligence’ system –

combines linked administrative data, cohorts, service delivery evaluations and RCTs

Enriched phenotypes from cohorts, special collections and

genetic data

Info

rmat

ion

Syst

ems

Eval

uatio

n an

d In

nova

tion

SCOPE GuthrieCardsPrems

data

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Use linked administrative data to routinely and cost effectively evaluate programs

and service delivery innovations

• using RCTs for medium term follow-up in school

• propensity score matched comparison groups

• regression discontinuity designs

• instrumental variables

Data Linkage and Routine Evaluation Studies

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• IF we knew who was in and not in the systems – coverage in the population

• IF we knew which services children and parents accessed

• and IF we were able to regularly, routinely collect relevant outcomes like child development, mental health, physical health, …

• and we were able to create, document and measure changes in service provision,e.g., “integration” such as Children’s Centres

• Then a population-wide data linkage information system could be used to helpquantitatively evaluate service innovations on a routine, cost-effective andsustainable basis

• And potentially in close to real time to provide clinical and practice feedback to improve service quality

Information Systems and Improving Effectiveness of Services

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The science of the “bleeding obvious” …?