Linkage of multiple electronic health record datasets using a 'spine linkage' approach compared with all 'pairwise linkages'.
Linkage of multiple electronic health record datasets using a 'spine linkage' approach compared with all 'pairwise linkages'.
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DOI:
10.1093/ije/dyac130
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发表时间:
2023-02-08
影响因子:
7.7
通讯作者:
中科院分区:
文献类型:
--
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Methods 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. We 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. The 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). Spine 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.
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影响因子:
2.9
作者:
Hagger-Johnson, Gareth;Harron, Katie;Parslow, Roger C.
通讯作者:
Parslow, Roger C.
影响因子:
7.2
作者:
Lee KJ;Tilling KM;Cornish RP;Little RJA;Bell ML;Goetghebeur E;Hogan JW;Carpenter JR;STRATOS initiative
通讯作者:
STRATOS initiative
影响因子:
7.2
作者:
Blake, Helen A.;Sharples, Linda D.;Walker, Kate
通讯作者:
Walker, Kate
影响因子:
3.5
作者:
Chiu, Maria;Lebenbaum, Michael;Guttmann, Astrid
通讯作者:
Guttmann, Astrid
影响因子:
4.5
作者:
John, Ann;McGregor, Joanna;Lloyd, Keith
通讯作者:
Lloyd, Keith