ArticleBMJ health & care informatics2021
Comparison of identifiable and non-identifiable data linkage: health technology assessment of MitraClip using registry, administrative and mortality datasets.
Article in BMJ health & care informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesThe UK MitraClip registry was commissioned by National Health Service (NHS) England to assess real-world outcomes from percutaneous mitral valve repair for mitral regurgitation using a new technology, MitraClip. This study aimed to determine longitudinal patient outcomes by linking to routine datasets: Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Office of National Statistics.
methodsTwo methods of linkage were compared, using identifiable (NHS number, date of birth, postcode, gender) and non-identifiable data (hospital trust, age in years, admission, discharge and operation dates, operation and diagnosis codes). Outcome measures included: matching success, patient demographics, all-cause mortality and subsequent cardiac intervention.
resultsA total of 197 registry patients were eligible for matching with routine administrative data. Using identifiable linkage, a total of 187 patients (94.9%) were matched with the HES APC dataset. However, 21 matched individuals (11.2%) had inconsistencies across the datasets (eg, different gender) and were subsequently removed, leaving 166 (84.3%) for analysis. Using non-identifiable data linkage, a total of 170 patients (86.3%) were uniquely matched with the HES APC dataset.Baseline patient characteristics were not significantly different between the two methods of data linkage. The total number of deaths (all causes) identified from identifiable and non-identifiable linkage methods was 37 and 40, respectively, and the difference in subsequent cardiac interventions identified between the two methods was negligible.
conclusionsPatients from a bespoke clinical procedural registry were matched to routine administrative data using identifiable and non-identifiable methods with equivalent matching success rates, similar baseline characteristics and similar 2-year outcomes.
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