文章基本信息

标题：Evaluation of the reported data linkage process and associated quality issues for linked routinely collected healthcare data in Multimorbidity research: a systematic review.
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作者：Maria Elstad ; Abdel Douiri ; Jo Røislien 等
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2022
卷号：7
期号：3
DOI：10.23889/ijpds.v7i3.2047
语种：English
出版社：Swansea University
摘要：Objectives The objective for this systematic review was to examine how the record linkage process was reported and to understand challenges related to accessing, linking, and analysing linked routinely collected data used for multimorbidity research. Approach A systematic search for relevant studies was conducted in three online databases (Medline, Web of Science and Embase) in May 2021 using predefined search terms, and inclusion and exclusion criteria. Studies using linked routinely collected data for multimorbidity research were included. Information was extracted on how the linkage process was reported, which conditions were studied together, which data sources were used, as well as challenges encountered during the linkage process or with the linked dataset. The findings from this study will feed into further guidance to understand and minimise bias due to linkage error in medical research. Results Twenty studies were included, of which seventeen looked at the relationship between two specified long-term conditions. Fourteen studies received the linked dataset from an external data linkage provider. Hospital Episode Statistics was the most common source of data (n=5). Eight studies reported variables used for the data linkage, while only two studies reported pre-linkage checks. The quality of the linkage was assessed by three studies, of which two reported linkage rate and one reported raw linkage figures. Only one study checked for bias by comparing patient characteristics of linked and non-linked records. Conclusions The linkage process was poorly reported in multimorbidity research, even though this might introduce bias and potentially lead to inaccurate inferences drawn from the results. There is therefore a need for increased awareness of linkage bias and transparency of the linkage processes, which could be achieved through better adherence to reporting guidelines.