1. Using routine data to build the Wales Electronic Cohort for Children (WECC) Joanne Demmler, Melanie Hyatt, Sarah Rodgers, Shantini Paranjothy, Frank Dunstan, David Fone, Gareth John, John Watkins, Mark Kelly, Annette Evans, Muhammad Rahman, Ronan Lyons

2. to build a child health cohort for Wales for all children born in Wales between 1990 and 2008 gathering birth, education and hospital admissions data purely from routinely collected data Objective

3. Routinely Collected Data PEDW – Patient Episode Database for Wales NCCHD – National Community Child Health Database WDS - Wales Demographics Service AWPS – All Wales Perinatal Survey CARIS – Congenital Anomaly Register & Information Service ONSB – Office of National Statistics Births ONSM – Office of National Statistics Mortality NPD – National Pupil Database

4. Research Questions 1. What factors determine the future health service need for individuals that are vulnerable at birth, and inform the development of interventions to reduce health inequalities for these groups? 2. What is the influence of the social and physical environment on childhood obesity?

5. From Health Record to Secure Anonymous Information Linkage NameSurnameDate of birthAddressAdmission date Diagnosis code Discharge date

6. From Health Record to Secure Anonymous Information Linkage NameSurnameDate of birth AddressAdmission date Diagnosis code Discharge date Personal identifyable informationNon-identifyable health information

7. From Health Record to Secure Anonymous Information Linkage NameSurnameDate of birthAddress Personal identifyable informationNon-identifyable health information Admission dateDiagnosis codeDischarge date 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 NHS Wales Informatics Service (NWIS)Health Information Research Unit (HIRU)

8. From Health Record to Secure Anonymous Information Linkage ALFWOBLSOA Personal anonymous informationNon-identifyable health information Admission date Diagnosis code Discharge date 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 NHS Wales Informatics Service (NWIS)Health Information Research Unit (HIRU)

9. From Health Record to Secure Anonymous Information Linkage ALFWOBLSOA Personal anonymous information& Non-identifyable health information Admission dateDiagnosis codeDischarge date HIRU

10. WDS: Welsh Demographic Service, NCCHD: National Community Child Health, CARIS: Congenital Anomaly Register and Information Service, ONS: Office for National Statistics, AWPS: All Wales Perinatal Survey Using anonymised record linkage to create WECC Congenital Anomalies (CARIS) Birth records (ONS births) Infant mortality (AWPS) Mortality records (ONS deaths) Wales Electronic Cohort for Children n=804,243 ♂: 411,515 (51.2%) ♀ : 392,728 (48.8%) Wales Electronic Cohort for Children n=804,243 ♂: 411,515 (51.2%) ♀ : 392,728 (48.8%) WECC eligibility criteria applied Data enrichment: augment data by joining with additional datasets dataset Data cleansing: - precedence vs. consistency rule for duplicate data items key demographic variables: gender, week of birth, date of death Record linkage: ALF_E WDS Child Health (NCCHD) Child Health (NCCHD) Demographic data* n=210,151 Non-Welsh births ♂: 107,256 (51.0%) ♀ : 102,859 (49.0%) n= 596,411 Born in Wales ♂: 304,259 (51.2%) ♀ : 289,833 (48.8%)

11. Major stumbling blocks Duplicate records for the same child  people with multiple NHS numbers  slightly different records for the same date/year for the same person Same parameters with different content in different databases  e.g. WOB in WDS, NCCHD, ONSB, ONSM Missing information in WDS  person never registered with a GP during their stay in Wales Recording errors  measurements are outside sensible limits

12. Complexity

13. Vulnerable babies: respiratory admissions Vulnerable group All subjects (n = 320,730) Hazard Ratio 95% Confidence Interval Very low birth weight5,7032.351.90 to 2.91 Low birth weight39,9941.361.26 to 1.467 High birth weight64,1620.920.87 to 0.98 Moderately preterm34,1191.471.32 to 1.53 Very preterm8,5101.991.59 to 2.24 Extremely preterm2,7113.492.10 to 4.77 Small for gestation60,5990.970.91 to 1.04 Caesarean section77,7301.141.09 to 1.19 Mother aged <1717,7861.060.95 to 1.18 Mother aged <151,5481.190.85 to 1.66 Subjects selected for PEDW coverage 1995-2001 n=320,730

14. Time to first respiratory admission - Adjusted for confounders APGAR (6-10) 0-31.10.95 to 1.28 4-61.081.00 to 1.16 Breastfeeding (no) Yes0.830.79 to 0.86 Smoking (never smoked) Gave up1.080.98 to 1.20 1-91.141.07 to 1.21  10 1.111.04 to 1.18 Gender (Male) Female0.750.72 to 0.78 Townsend (1)HR95% CI 21.060.95 to 1.18 31.040.94 to 1.16 41.060.96 to 1.18 51.141.03 to 1.26 61.121.01 to 1.23 71.191.08 to 1.30 81.141.03 to 1.26 91.161.05 to 1.29 101.31.17 to 1.43

15. Time to first respiratory admission: hazard ratios, relative to term UnadjustedAdjusted PretermHR95% CIHR95% CI Extremely3.412.10 to 4.773.172.10 to 4.77 Very2.091.59 to 2.241.891.59 to 2.24 Moderately1.461.32 to 1.531.421.32 to 1.53

16. WECC capabilities and future Cost effective resource for research supporting policy development System facilitates:  Interdisciplinary, observational and interventional research at any geographical level  appropriate hierarchical analyses  Future developments  Extend cohort to 2012+  Create hybrid cohort with Millennium Cohort Study (and UKBCS)  Build in web-based assessment of exposures and behaviours

17. Craig Cerrig-gleisiad, Brecon Beacons, South Wales SN 963 218 GB grid Any queries about the SAIL databank hiru@swansea.ac.uk Any queries about WECC Ronan Lyons:r.a.lyons@swansea.ac.uk Joanne Demmler:j.demmler@swansea.ac.uk Melanie Hyatt:m.a.hyatt@swansea.ac.uk Project lead Database analysts