Dr Shantini Paranjothy

Report
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)
Overview
• 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
Literature review
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)
17 distinct studies
USA (n=6), Canada (n=4), England (n=3), Scotland (n=1), Australia
(n=2), Denmark (n=1)
E-health record linkage studies
focussed on congenital anomalies
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, socioeconomic status),
• occupational exposures
• parental cancer treatment
• prenatal alcohol exposure
– Limited by poor characterisation of exposure measures
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
E-health record linkage studies
focussed on congenital anomalies
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
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
Routinely collected data in Wales
Population ~3M, ~35,000 births per year
1.
2.
3.
4.
5.
6.
7.
Welsh Demographic Service
Office for National Statistics (birth and mortality files)
National Community Child Health Database
Patient Episode Database for Wales (PEDW)
General Practice consultations
Congenital Anomaly Registry and Information Service (CARIS)
National Pupil Dataset
Wales Electronic Cohort for Children
(WECC)
• 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
WECC development
• 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
WECC eligibility
criteria applied
WDS
Child Health
(NCCHD)
ALF_E
Birth records
(ONS births)
Mortality
records (ONS
deaths)
Data cleaning: rules for removal of duplicates and errors
Wales Electronic Cohort for
Children
N=981,404
WDS: Welsh Demographic Service, NCCHD: National Community Child Health, ONS: Office for National Statistics
• 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
Born in Wales
n= 766,309
♂: 392,959 (51.3%)
♀ : 373,333 (49.0%)
Environment
House Moves
WECC core
n = 981,404
♂: 500,181 (51.0%)
♀ : 481,205 (49.0%)
Non-Welsh births
n=215,095
♂: 107,222 (49.8%)
♀ : 107,872 (50.2%)
WECC derived tables
National dataset
Inpatient
GP
consultations
Perinatal and
Child health
Education
Examples of analyses
 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)
Follow-up of children with Down’s
syndrome in WECC
How do survival and hospital admission rates compare between
the following groups of children?
1. No major life-threatening congenital anomalies
2. Major life-threatening congenital anomalies (excl DS)
3. Down’s syndrome without major life-threatening congenital
anomalies
4. Down’s syndrome and major life-threatening congenital
anomalies
Welsh births 1st Jan 1998 – 7th Oct 2012
N = 491,036
Excluded
stillbirths
N = 1,684
No Down’s
syndrome
Down’s
syndrome
N = 488,850
N = 502
No LTCA
LTCA
No LTCA
LTCA
N = 486,468
N = 2,382
N = 432
N = 70
1,941,801 pyrs
8,575 pyrs
1588 pyrs
215 pyrs
Survival up to age 5 years
% 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)
Emergency hospital admissions
Incidence
No. of
admissions
per 100
person years
(95%CI)
Number of
children
admitted
Median age
at first
admission
No LTCA
N = 486,468
LTCA
N = 2,382
DS – LTCA
N = 432
DS + LTCA
N = 70
11.6
(11.5, 11.7)
21.3
(20.4, 22.3)
21.9
(19.4, 24.0)
28.4
(22.1, 36.5)
225,299
1,828
343
61
9 months
2 months
4 months
2 months
Risk of emergency respiratory
hospital admission up to age 5 years
HR (95% CI)
No LTCA
LTCA (excl DS)
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)
HR for maternal age 25 – 34 years and middle
quintile of social deprivation
DS + LTCA
Children in LEA maintained schools
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%)
Provision for children with special
educational needs (SEN)
Welsh births
(1998 – 2004)
No LTCA
N = 186,354
LTCA (excl DS)
N = 789
DS
N = 142
School action
16.0%
18.9%
<5%
School action
plus
7.5%
17.4%
7.0%
Statemented
1.8%
11.8%
89.4%
Conclusion/reflections
• 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)
Acknowledgements
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
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?

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