Evidence map›Paper›PMID 35748342›Full record

ArticleInternational journal of epidemiology2023

Linkage of multiple electronic health record datasets using a 'spine linkage' approach compared with all 'pairwise linkages'.

Helen A Blake, Linda D Sharples, Katie Harron, Jan H van der Meulen, Kate Walker

Abstract read
In one paragraph

Article in International journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Helen A BlakeDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0001-7856-5931
Linda D SharplesDepartment of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0003-0894-966X
Katie HarronPopulation, Policy & Practice Department, University College London (UCL) Great Ormond Street Institute of Child Health, UCL, London, UK.ORCID 0000-0002-3418-2856
Jan H van der MeulenDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
Kate WalkerDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.

Funding

Department of Health 17/05/45Medical Research CouncilWellcome TrustWellcome Trust 212953/Z/18/Z
6 · The paper itself

Abstract

backgroundMethods for linking records between two datasets are well established. However, guidance is needed for linking more than two datasets. Using all 'pairwise linkages'-linking each dataset to every other dataset-is the most inclusive, but resource-intensive, approach. The 'spine' approach links each dataset to a designated 'spine dataset', reducing the number of linkages, but potentially reducing linkage quality.

methodsWe compared the pairwise and spine linkage approaches using real-world data on patients undergoing emergency bowel cancer surgery between 31 October 2013 and 30 April 2018. We linked an administrative hospital dataset (Hospital Episode Statistics; HES) capturing patients admitted to hospitals in England, and two clinical datasets comprising patients diagnosed with bowel cancer and patients undergoing emergency bowel surgery.

resultsThe spine linkage approach, with HES as the spine dataset, created an analysis cohort of 15 826 patients, equating to 98.3% of the 16 100 patients identified using the pairwise linkage approach. There were no systematic differences in patient characteristics between these analysis cohorts. Associations of patient and tumour characteristics with mortality, complications and length of stay were not sensitive to the linkage approach. When eligibility criteria were applied before linkage, spine linkage included 14 509 patients (90.0% compared with pairwise linkage).

conclusionSpine linkage can be used as an efficient alternative to pairwise linkage if case ascertainment in the spine dataset and data quality of linkage variables are high. These aspects should be systematically evaluated in the nominated spine dataset before spine linkage is used to create the analysis cohort.

Indexed as

Colorectal NeoplasmsElectronic Health RecordsHospitalizationHospitalsHumansMedical Record Linkageelectronic health recordspairwise linkageRecord linkagespine linkage approach

Identifiers

PMID35748342
PMCPMC9908066

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.