CPRD GOLD and linked ONS mortality records: Reconciling guidelines.

Background: The Clinical Practice Research Datalink (CPRD) GOLD is an extremely influential U.K. primary care dataset for epidemiological research having a number of published papers based on its data much bigger than any other U.K. primary care dataset. The Office for National Statistics (ONS) death data for England can be linked to GOLD at the patient level and are considered the gold standard on mortality. GOLD, which also holds death data, has been recently assessed against ONS linked dataset and the accuracy of its dates of death has been deemed sufficient for the majority of observational studies. However, there is a lack of guidance on how to manage the challenges existing when ONS mortality and GOLD datasets are linked, including linkage coverage period, linkage correctness likelihood, linkage regional limitations and data discrepancy.
Objectives: Provide reconciling guidelines on how to make maximum and at the same time trustworthy use of mortality information coming from both GOLD and ONS linked datasets with the aim of improving the quality, reproducibility, transparency and comparison of clinical research.
Method and Results: We have developed recommendations on how to manage mortality data coming from both GOLD and linked ONS, taking into account linkage coverage period, linkage correctness likelihood, linkage regional limitations and data discrepancies between these two datasets. We have also implemented these guidelines in an SQL algorithm for researchers to use.
Conclusion: We have provided detailed guidelines on the reconciliation of mortality data between GOLD and ONS linked death datasets, taking into account both their strengths and limitations. The consistent application of these guidelines made practical by an SQL algorithm, has the potential to improve clinical research quality, reproducibility, transparency and comparison.
Competing Interests: Declaration of Competing Interest The authors have no competing interests to declare.
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