E-health records research: optimising congenital anomaly data

Dr. Shantini Paranjothy

Cochrane Institute of Primary Care and Public Health, College of Biomedical and Life Sciences - Cardiff University

Centre for Improvement in Population Health through E-records Research (CIPHER)

• E-health record linkage studies focussed on congenital anomalies– Literature review

• Wales Electronic Cohort for Children– Exemplar analyses: Outcomes for children

with Down’s syndrome

• Conclusion / reflections

Overview

E-health record linkage studies focussed on congenital anomalies

Search strategy:"data linkage" OR "record linkage" OR "database studies" AND "congenital anomalies" - 26 results (OvidSP)

USA (n=6), Canada (n=4), England (n=3), Scotland (n=1), Australia (n=2), Denmark (n=1)

Literature review

17 distinct studies

Types of studies• Trends and inequalities in birth prevalence (n=4)

• Aetiology of congenital anomalies (n=7)– Risk factors:

• maternal characteristics (age, parity, cigarette smoking, socio-economic status),

• occupational exposures• parental cancer treatment • prenatal alcohol exposure

– Limited by poor characterisation of exposure measures

E-health record linkage studies focussed on congenital anomalies

Refs: BMJ 1993;307:164-8, BDR Part A97(7): 497 – 504, BDR Part(A) 91(12): 1011-1018, Int J Environ Res Public Health 10(4):1312-1323, Epidemiology 13(2):197-204, Prenat Diagn 29():613-619, Occup Environ Med 54(9):629-635, Scand J Public Health 37(3):246-251, Dev Med Child Neurol 52(4):345-351, Arch Dis Child: Fetal and Neonatal Edition 94(1):F23-F27, BDR A Clin Mol Teratol 73(10):663-668

Types of studies• Follow-up studies

– Survival at 1 year, 6 years, 10 years (n=2)– Childhood cancers (n=2)– Hospital admissions (n=1)

Limited data from total population studies– Healthcare utilisation – GP consultations, hospital

admissions– Social care, education– Inequalities in health and social outcomes

E-health record linkage studies focussed on congenital anomalies

Refs: BDR A Clin Mol Teratol 67(9):656-661, BDR A Clin Mol Teratol 79(11):792-797, Am J Public Health 89(6):887-892, Am J Epi 175(12): 1210-1224, Pediatric Blood and Cancer 51(5):608-612, PLOS One 2013:8(8)e70401

Population ~3M, ~35,000 births per year

1. Welsh Demographic Service2. Office for National Statistics (birth and mortality

files)

3. National Community Child Health Database4. Patient Episode Database for Wales (PEDW)

5. General Practice consultations6. Congenital Anomaly Registry and Information Service

(CARIS)

7. National Pupil Dataset

Routinely collected data in Wales

• Platform for translating routinely collected data into an anonymised population based e-cohort of children to

– Investigate the widest possible range of social and environmental determinants of child health and social outcomes

– Inform the development of interventions to reduce health inequalities of children in Wales

• E-cohort development

• Exemplar analysis: Down syndrome

Wales Electronic Cohort for Children (WECC)

• Inclusion criteria– Children born or resident in Wales– Phase 1: Date of birth between 1st Jan 1990 – 31st Dec 2008– Phase 2: extended to include births until 7th October 2012

• Core databases– Welsh Demographic Service (WDS)– National Community Child Health Database (NCCHD)

• Linking field– NHS number --- encrypted anonymised linking field (ALF_E)

WECC development

Birth records

(ONS births)

Mortality records

(ONS deaths)

Wales Electronic Cohort for Children

N=981,404

WECC eligibility criteria applied

Data cleaning: rules for removal of duplicates and errors

WDSChild

Health(NCCHD)

ALF_E

WDS: Welsh Demographic Service, NCCHD: National Community Child Health, ONS: Office for National Statistics

WECC development

• Links with health and education data via ALF_E• Links with maternal health data via mALF_E• Links with SAIL eGIS data via ALF_E/RALF_E

WECC coren = 981,404

♂: 500,181 (51.0%)♀ : 481,205 (49.0%)

Inpatient

GP consultation

s

Perinatal and Child

health

Environment

House Moves

Non-Welsh births

n=215,095♂: 107,222 (49.8%)♀ : 107,872 (50.2%)

Born in Walesn= 766,309

♂: 392,959 (51.3%)♀ : 373,333 (49.0%)

WECC derived tables

National dataset

Education

Gestational Age, Birth Weight, and Risk of Respiratory Hospital Admission in Childhood (Paranjothy S. et al (2013) Pediatrics 132:6 e1562-e1569)

Association between hospitalisation for childhood head injury and academic performance (Gabbe B.J. et al (2014)Journal of Epidemiology and Community Health, J Epidemiol Community Health.68:5 466-470 )

Frequent house moves and educational outcomes (Hutchings H. et al (2013) PLoS One. 8(8) e70601)

Examples of analyses

How do survival and hospital admission rates compare between the following groups of children?

1. No major life-threatening congenital anomalies2. Major life-threatening congenital anomalies (excl DS)3. Down’s syndrome without major life-threatening congenital

anomalies4. Down’s syndrome and major life-threatening congenital

anomalies

Follow-up of children with Down’s syndrome in WECC

Welsh births 1st Jan 1998 – 7th Oct 2012N = 491,036

No Down’s syndrome

N = 488,850

No LTCAN = 486,468

1,941,801 pyrs

LTCAN = 2,3828,575 pyrs

Down’s syndromeN = 502

No LTCAN = 432

1588 pyrs

LTCAN = 70

215 pyrs

Excluded stillbirthsN = 1,684

% survival(95%CI)

No LTCA LTCA DS - LTCA DS + LTCA

6 months 99.7(99.7, 99.7)

90.0(88.0, 91.0)

97.0(95.0, 98.0)

81.0(70.0, 89.0)

1 year 99.7(99.7, 99.7)

89.0(87.0, 90.0)

96.0(94.0, 98.0)

78.0(66.0, 86.0)

3 years 99.7(99.7, 99.7)

88.0(86.0, 89.0)

94.0(91.0, 96.0)

73.0(60.0, 82.0)

5 years 99.6(99.6, 99.6)

87.0(86.0, 88.0)

92.0(89.0, 95.0)

73.0(60.0, 82.0)

Survival up to age 5 years

No LTCAN =

486,468

LTCA N = 2,382

DS – LTCAN = 432

DS + LTCAN = 70

IncidenceNo. of

admissions per 100 person

years (95%CI)

11.6(11.5, 11.7)

21.3(20.4, 22.3)

21.9(19.4, 24.0)

28.4(22.1, 36.5)

Number of children

admitted

225,299 1,828 343 61

Median age at first admission

9 months 2 months 4 months 2 months

Emergency hospital admissions

HR (95% CI) No LTCA LTCA (excl DS)

DS - LTCA DS + LTCA

6 months 1.0 2.8 (2.6 – 2.9) 4.1 (3.6 – 4.7)

5.7 (4.2 – 7.8)

1 year 1.0 2.4 (2.2 – 2.6) 4.2 (3.7 – 4.8)

5.5 (3.8 – 7.8)

3 years 1.0 2.0 (1.8 – 2.2) 4.3 (3.5 – 5.3)

5.2 (3.1 – 8.8)

5 years 1.0 1.8 (1.6 – 2.0) 4.4 (3.4 – 5.7)

5.1 (2.6 – 9.8)

Risk of emergency respiratory hospital admission up to age 5 years

HR for maternal age 25 – 34 years and middle quintile of social deprivation

Welsh births (1998 – 2004)

Entered for KS1

Yes No

No LTCA 186,354 (85.2%) 32,295 (14.8%)

LTCA (excl DS) 789 (76.2%) 247 (23.8%)

DS 142 (70%) 59 (29.4%)

Children in LEA maintained schools

Welsh births (1998 – 2004)

No LTCAN = 186,354

LTCA (excl DS)N = 789

DSN = 142

School action 16.0% 18.9% <5%

School action plus

7.5% 17.4% 7.0%

Statemented 1.8% 11.8% 89.4%

Provision for children with special educational needs (SEN)

• Feasible to use anonymised record linkage of routinely collected datasets across disciplines to create a population based e-cohort of children

• Cost-effective resource for research to support policy

• System facilitates:– Interdisciplinary, observational and interventional research at any

geographical level– appropriate hierarchical analyses– augmentation of traditional survey cohorts

Conclusion/reflections

• Platforms for congenital anomaly research– WECC– Euromedicat (Safety of medicines in pregnancy)– MEPREP (Medical exposure in Pregnancy Risk Evaluation

Programme)

• Potential for defining exposure variables– Alcohol exposure, stressful life events

• Future:– Potential for web-based assessment of exposures and

behaviours, integration of biological data (e.g. newborn bloodspots)

Conclusion/reflections

Cardiff University• Annette Evans• David Fone• Frank Dunstan

Public Health Wales• Sion Lingard• David Tucker• Ciaran Humphreys

Swansea University• Ronan Lyons• Sinead Brophy• Joanne Demmler• Amrita Banyopadhyay

Acknowledgements

This study makes use of the anonymized data held in the SAIL system which is part of the national e-health records research infrastructure for Wales.We acknowledge all the data providers who make anonymized data available for research.WECC was funded by NISCHR Translational Health Research Platform Award (2009 – 12)D-WECC was funded by NISCHR (2012 – 15)

Thank you

Any questions?