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. 2016 Oct 20;11(10):e0164667.
doi: 10.1371/journal.pone.0164667. eCollection 2016.

Linking Data for Mothers and Babies in De-Identified Electronic Health Data

Katie Harron  1 , Ruth Gilbert  2 , David Cromwell  1 , Jan van der Meulen  1
Affiliations

Linking Data for Mothers and Babies in De-Identified Electronic Health Data

Katie Harron et al. PLoS One. .

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.

Design and setting: 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.

Conclusion: 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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Extract flow-diagram for delivery and birth episodes captured in HES for 2012/13.
Fig 2
Fig 2. Estimated false-match rate and sensitivity for a range of threshold weights, based on synthetic data.
Fig 3
Fig 3. Contribution of each linking variable to overall match weight.
Agreement = positive contribution (solid line), disagreement = negative contribution (dashed line). The higher the value, the more information the linkage variable provides.
Fig 4
Fig 4. Distribution of birth weight by week of gestation in baby records.
Vertical lines show 3 standard deviations from the average; values above the upper limit are likely to have been miscoded as days (rather than weeks) of gestation, truncated to 2 digits.
Fig 5
Fig 5. Representativeness of linked HES cohort in terms of maternal age, birth weight and gestational age.
Dark shade = HES, light shade = Office for National Statistics.
See this image and copyright information in PMC

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