title: Linking Data for Mothers and Babies in De-Identified Electronic Health Data.
abstract: OBJECTIVE
  Linkage of longitudinal administrative data for mothers and babies supports research and service evaluation in several populations around the world. We established a linked mother-baby cohort using pseudonymised, population-level data for England.
  
  
  METHODS
  Retrospective linkage study using electronic hospital records of mothers and babies admitted to NHS hospitals in England, captured in Hospital Episode Statistics between April 2001 and March 2013.
  
  
  RESULTS
  Of 672,955 baby records in 2012/13, 280,470 (42%) linked deterministically to a maternal record using hospital, GP practice, maternal age, birthweight, gestation, birth order and sex. A further 380,164 (56%) records linked using probabilistic methods incorporating additional variables that could differ between mother/baby records (admission dates, ethnicity, 3/4-character postcode district) or that include missing values (delivery variables). The false-match rate was estimated at 0.15% using synthetic data. Data quality improved over time: for 2001/02, 91% of baby records were linked (holding the estimated false-match rate at 0.15%). The linked cohort was representative of national distributions of gender, gestation, birth weight and maternal age, and captured approximately 97% of births in England.
  
  
  CONCLUSIONS
  Probabilistic linkage of maternal and baby healthcare characteristics offers an efficient way to enrich maternity data, improve data quality, and create longitudinal cohorts for research and service evaluation. This approach could be extended to linkage of other datasets that have non-disclosive characteristics in common.
authors.affiliation: Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, United Kingdom.
authors.forename: Katie
authors.identifier: http://orcid.org/0000-0002-3418-2856
authors.initials: K
authors.lastname: Harron
authors.affiliation: Institute of Child Health, University College London, 30 Guilford Street, London, United Kingdom.
authors.forename: Ruth
authors.initials: R
authors.lastname: Gilbert
authors.affiliation: Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Cromwell
authors.affiliation: Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, United Kingdom.
authors.forename: Jan
authors.initials: J
authors.lastname: van der Meulen
mesh_terms: D001719:Birth Certificates; D005260:Female; D006753:Hospital Records / Q000706:statistics & numerical data; D006760:Hospitalization; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008423:Maternal Age; D008498:Medical Record Linkage / Q000379:methods*; D009035:Mothers; D036801:Parturition; D012189:Retrospective Studies