Data linkage errors in hospital administrative data when applying a pseudonymisation algorithm to paediatric intensive care records.

OBJECTIVES: Our aim was to estimate the rate of data linkage error in Hospital Episode Statistics (HES) by testing the HESID pseudoanonymisation algorithm against a reference standard, in a national registry of paediatric intensive care records. SETTING: The Paediatric Intensive Care Audit Network (PICANet) database, covering 33 paediatric intensive care units in England, Scotland and Wales. PARTICIPANTS: Data from infants and young people aged 0-19 years admitted between 1 January 2004 and 21 February 2014. PRIMARY AND SECONDARY OUTCOME MEASURES: PICANet admission records were classified as matches (records belonging to the same patient who had been readmitted) or non-matches (records belonging to different patients) after applying the HESID algorithm to PICANet records. False-match and missed-match rates were calculated by comparing results of the HESID algorithm with the reference standard PICANet ID. The effect of linkage errors on readmission rate was evaluated. RESULTS: Of 166,406 admissions, 88,596 were true matches (where the same patient had been readmitted). The HESID pseudonymisation algorithm produced few false matches (n=176/77,810; 0.2%) but a larger proportion of missed matches (n=3609/88,596; 4.1%). The true readmission rate was underestimated by 3.8% due to linkage errors. Patients who were younger, male, from Asian/Black/Other ethnic groups (vs White) were more likely to experience a false match. Missed matches were more common for younger patients, for Asian/Black/Other ethnic groups (vs White) and for patients whose records had missing data. CONCLUSIONS: The deterministic algorithm used to link all episodes of hospital care for the same patient in England has a high missed match rate which underestimates the true readmission rate and will produce biased analyses. To reduce linkage error, pseudoanonymisation algorithms need to be validated against good quality reference standards. Pseudonymisation of data 'at source' does not itself address errors in patient identifiers and the impact these errors have on data linkage.Economic and Social Research Council (ESRC) National Centre for Research Methods (NCRM), grant number ES/F035098/1

Ethnic and socioeconomic variation in incidence of congenital heart defects

Introduction: Ethnic differences in the birth prevalence of congenital heart defects (CHDs) have been reported; however, studies of the contemporary UK population are lacking. We investigated ethnic variations in incidence of serious CHDs requiring cardiac intervention before 1 year of age. Methods: All infants who had a cardiac intervention in England and Wales between 1 January 2005 and 31 December 2010 were identified in the national congenital heart disease surgical audit and matched with paediatric intensive care admission records to create linked individual child records. Agreement in reporting of ethnic group by each audit was evaluated. For infants born 1 January 2006 to 31 December 2009, we calculated incidence rate ratios (IRRs) for CHDs by ethnicity and investigated age at intervention, antenatal diagnosis and area deprivation. Results: We identified 5350 infants (2940 (55.0%) boys). Overall CHD incidence was significantly higher in Asian and Black ethnic groups compared with the White reference population (incidence rate ratios (IRR) (95% CIs): Asian 1.5 (1.4 to 1.7); Black 1.4 (1.3 to 1.6)); incidence of specific CHDs varied by ethnicity. No significant differences in age at intervention or antenatal diagnosis rates were identified but affected children from non-White ethnic groups were more likely to be living in deprived areas than White children. Conclusions: Significant ethnic variations exist in the incidence of CHDs, including for specific defects with high infant mortality. It is essential that healthcare provision mitigates ethnic disparity, including through timely identification of CHDs at screening, supporting parental choice and effective interventions. Future research should explore the factors underlying ethnic variation and impact on longer-term outcomes