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E-health records research : optimising congenital anomaly data

E-health records research : optimising congenital anomaly data

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E-health records research : optimising congenital anomaly data

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  1. 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)

  2. 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

  3. 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) USA (n=6), Canada (n=4), England (n=3), Scotland (n=1), Australia (n=2), Denmark (n=1) 17 distinct studies

  4. 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, socio-economic 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, PrenatDiagn 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 ClinMolTeratol 73(10):663-668

  5. 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 ClinMolTeratol 67(9):656-661, BDR A ClinMolTeratol 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

  6. Routinely collected data in Wales Population ~3M, ~35,000 births per year • 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

  7. 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

  8. 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)

  9. 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

  10. 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%) WECC core n = 981,404 ♂: 500,181 (51.0%) ♀ : 481,205 (49.0%) Environment House Moves Inpatient Non-Welsh births n=215,095 ♂: 107,222 (49.8%) ♀ : 107,872 (50.2%) GP consultations Education WECC derived tables National dataset Perinatal and Child health

  11. Examples of analyses • Gestational Age, Birth Weight, and Risk of Respiratory Hospital Admission in Childhood (Paranjothy S. et al (2013) Pediatrics132:6 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)

  12. Follow-up of children with Down’s syndrome in WECC How do survival and hospital admission rates compare between the following groups of children? • No major life-threatening congenital anomalies • Major life-threatening congenital anomalies (excl DS) • Down’s syndrome without major life-threatening congenital anomalies • Down’s syndrome and major life-threatening congenital anomalies

  13. Survival up to age 5 years

  14. Emergency hospital admissions

  15. Risk of emergency respiratory hospital admission up to age 5 years HR for maternal age 25 – 34 years and middle quintile of social deprivation

  16. Children in LEA maintained schools

  17. Provision for children with special educational needs (SEN)

  18. 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

  19. 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)

  20. Acknowledgements Cardiff University • Annette Evans • David Fone • Frank Dunstan Public Health Wales • SionLingard • 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)

  21. Thank you Any questions?