Challenges in administrative data linkage for research

Linkage of population-based administrative data is a valuable tool for combining detailed individual-level information from different sources for research. While not a substitute for classical studies based on primary data collection, analyses of linked administrative data can answer questions that require large sample sizes or detailed data on hard-to-reach populations, and generate evidence with a high level of external validity and applicability for policy making. There are unique challenges in the appropriate research use of linked administrative data, for example with respect to bias from linkage errors where records cannot be linked or are linked together incorrectly. For confidentiality and other reasons, the separation of data linkage processes and analysis of linked data is generally regarded as best practice. However, the ‘black box’ of data linkage can make it difficult for researchers to judge the reliability of the resulting linked data for their required purposes. This article aims to provide an overview of challenges in linking administrative data for research. We aim to increase understanding of the implications of (i) the data linkage environment and privacy preservation; (ii) the linkage process itself (including data preparation, and deterministic and probabilistic linkage methods) and (iii) linkage quality and potential bias in linked data. We draw on examples from a number of countries to illustrate a range of approaches for data linkage in different contexts

Impact of EU regulatory label changes for diclofenac in people with cardiovascular disease in four countries:interrupted time series regression analysis

Objective: Due to cardiovascular safety concerns, the European Medicines Agency (EMA) recommended new contraindications and changes to product information for diclofenac across Europe in 2013. This study aims to measure their impact among targeted populations. Method: Quarterly interrupted time series regression (ITS) analyses of diclofenac initiation among cohorts with contraindications (congestive cardiac failure [CHF], ischaemic heart disease [IHD], peripheral arterial disease [PAD], cerebrovascular disease [CVD]) and cautions (hypertension, hyperlipidaemia, diabetes) from Denmark, the Netherlands, England and Scotland. Results: The regulatory action was associated with significant immediate absolute reductions in diclofenac initiation in all countries for IHD (Denmark −0.08%, 95%CI −0.13, −0.03; England −0.09%, 95%CI −0.13 to −0.06%; the Netherlands −1.84%, 95%CI −2.51 to −1.17%; Scotland −0.34%, 95%CI −0.38 to −0.30%), PAD and hyperlipidaemia, the Netherlands, England and Scotland for hypertension and diabetes, and England and Scotland for CHF and CVD. Post-intervention there was a significant negative trend in diclofenac initiation in the Netherlands for IHD (−0.12%, 95%CI −0.19 to −0.04), PAD (−0.13%, 95%CI −0.22 to −0.05), hypertension, hyperlipidaemia and diabetes, and in Scotland for CHF (−0.01%, 95%CI −0.02 to −0.007%), IHD (−0.017, 95%CI −0.02, −0.01%), PAD and hypertension. In England, diclofenac initiation rates fell less steeply. In Denmark changes were more strongly associated with the earlier EMA 2012 regulatory action. Conclusion: Although significant reductions in diclofenac initiation occurred, patients with contraindications continued to be prescribed diclofenac, the extent of which varied by country and target condition. Understanding reasons for such variation may help to guide the design or dissemination of future safety warnings

Sources of potential bias when combining routine data linkage and a national survey of secondary school-aged children: a record linkage study

Background Linking survey data to administrative records requires informed participant consent. When linkage includes child data, this includes parental and child consent. Little is known of the potential impacts of introducing consent to data linkage on response rates and biases in school-based surveys. This paper assessed: i) the impact on overall parental consent rates and sample representativeness when consent for linkage was introduced and ii) the quality of identifiable data provided to facilitate linkage. Methods Including an option for data linkage was piloted in a sub-sample of schools participating in the Student Health and Wellbeing survey, a national survey of adolescents in Wales, UK. Schools agreeing to participate were randomized 2:1 to receive versus not receive the data linkage question. Survey responses from consenting students were anonymised and linked to routine datasets (e.g. general practice, inpatient, and outpatient records). Parental withdrawal rates were calculated for linkage and non-linkage samples. Multilevel logistic regression models were used to compare characteristics between: i) consenters and non-consenters; ii) successfully and unsuccessfully linked students; and iii) the linked cohort and peers within the general population, with additional comparisons of mental health diagnoses and health service contacts. Results The sub-sample comprised 64 eligible schools (out of 193), with data linkage piloted in 39. Parental consent was comparable across linkage and non-linkage schools. 48.7% (n = 9232) of students consented to data linkage. Modelling showed these students were more likely to be younger, more affluent, have higher positive mental wellbeing, and report fewer risk-related behaviours compared to non-consenters. Overall, 69.8% of consenting students were successfully linked, with higher rates of success among younger students. The linked cohort had lower rates of mental health diagnoses (5.8% vs. 8.8%) and specialist contacts (5.2% vs. 7.7%) than general population peers. Conclusions Introducing data linkage within a national survey of adolescents had no impact on study completion rates. However, students consenting to data linkage, and those successfully linked, differed from non-consenting students on several key characteristics, raising questions concerning the representativeness of linked cohorts. Further research is needed to better understand decision-making processes around providing consent to data linkage in adolescent populations