Evaluation of the reported data linkage process and associated quality issues for linked routinely collected healthcare data in Multimorbidity research: a systematic review

Author:

Elstad Maria1,Ahmed Saiam2,Røislien Jo3,Douiri Abdel1

Affiliation:

1. King’s College London

2. UCL

3. University of Stavanger

Abstract

Abstract Background: Datasets from multi-sources that routinely collect healthcare information such as patient medical records, admissions and disease registries are increasingly used for medical research. In some cases, multiple sources are combined using data linkage techniques to create comprehensive datasets. The patient records are linked on an individual level using available person level identifiers. Errors in this process can introduce bias of unknown size and direction. the objective of 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. Methods: 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. All published 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. Results: Twenty studies were included, of which seventeen investigated at the relationship between two specified long-term conditions. Fourteen studies received the linked dataset from a trusted third party. 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 only 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.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3