Record linkage in Scotland and its applications to health research

Aims and objectives. This paper will focus on the key concepts behind record linkage and describe how probability matching of Scottish health records can be used for national health research. Background. Record linkage can bring together two or more records relating to the same individual. This allows information from multiple sources to be joined together to produce richer data sets for research purposes and has wide applicability in public health and epidemiological research. The probability matching techniques underpinning record linkage bring together records on a patient basis using key identifying information on each record. Scotland has a strong track record for performing linkage for research purposes owing to routinely collected and well‐maintained national administrative health data sets, the emergence of the Scottish record linkage system and organisations like the Information Services Division of NHS National Services Scotland who centrally hold permanently linked patient‐based databases. Design. A record linkage retrospective population cohort study is described within this paper. Methods. The paper will describe current linkage methodology before discussing typical applications in the setting of Information Services Division and focusing on a particular linkage study investigating rates and risk factors for gastroschisis. Results. Conclusions from the gastroschisis study are typical of the types of important findings drawn from analysing linked health data. Conclusions. Scotland’s good track record for linking records for health research is evidenced by the high volume of research projects, publications and findings resulting from probability matching of national health data. Relevance to clinical practice. Record linkage allows information relating to the same person held across different data sources to be brought together. Probabilistic record linkage can overcome data quality issues, producing accurate matches. This allows linked, analysable, patient‐based databases, capable of answering complex research questions, to be produced from several data sources with wide applications in the field of health research.