ArticleJournal of innovation in health informatics2017
Probabilistic linkage to enhance deterministic algorithms and reduce data linkage errors in hospital administrative data.
Article in Journal of innovation in health informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
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- Firearm rights restoration after prohibiting criminal convictions: a statewide descriptive study.Injury epidemiology · 2025Article
- Improving opportunities for data linkage within Children Looked After administrative records in Wales.International journal of population data science · 2025Article
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- Linking migration and hospital data in England: linkage process and evaluation of bias.International journal of population data science · 2024Article
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- Linkage of multiple electronic health record datasets using a 'spine linkage' approach compared with all 'pairwise linkages'.International journal of epidemiology · 2023Article
- Data linkage in medical research.BMJ medicine · 2022Article
- Implementation of Fingerprint Technology for Unique Patient Matching and Identification at an HIV Care and Treatment Facility in Western Kenya: Cross-sectional Study.Journal of medical Internet research · 2021Article
- Leveraging National Claims and Hospital Big Data: Cohort Study on a Statin-Drug Interaction Use Case.JMIR medical informatics · 2021Article
- Automatic Information Exchange in the Early Rescue Chain Using the International Standard Accident Number (ISAN).Healthcare (Basel, Switzerland) · 2021Article
- Comparison of identifiable and non-identifiable data linkage: health technology assessment of MitraClip using registry, administrative and mortality datasets.BMJ health & care informatics · 2021Article
- Linking education and hospital data in England: linkage process and quality.International journal of population data science · 2021Article
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- Assessing data linkage quality in cohort studies.Annals of human biology · 2020Article
- Can the Use of Bayesian Analysis Methods Correct for Incompleteness in Electronic Health Records Diagnosis Data? Development of a Novel Method Using Simulated and Real-Life Clinical Data.Frontiers in public health · 2020Article
- Record Linkage Approaches Using Prescription Drug Monitoring Program and Mortality Data for Public Health Analyses and Epidemiologic Studies.Epidemiology (Cambridge, Mass.) · 2020Article
- Article
- Sociodemographic differences in linkage error: an examination of four large-scale datasets.BMC health services research · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundThe pseudonymisation algorithm used to link together episodes of care belonging to the same patients in England (HESID) has never undergone any formal evaluation, to determine the extent of data linkage error.
objectiveTo quantify improvements in linkage accuracy from adding probabilistic linkage to existing deterministic HESID algorithms.
methodsInpatient admissions to NHS hospitals in England (Hospital Episode Statistics, HES) over 17 years (1998 to 2015) for a sample of patients (born 13/28th of months in 1992/1998/2005/2012). We compared the existing deterministic algorithm with one that included an additional probabilistic step, in relation to a reference standard created using enhanced probabilistic matching with additional clinical and demographic information. Missed and false matches were quantified and the impact on estimates of hospital readmission within one year were determined.
resultsHESID produced a high missed match rate, improving over time (8.6% in 1998 to 0.4% in 2015). Missed matches were more common for ethnic minorities, those living in areas of high socio-economic deprivation, foreign patients and those with 'no fixed abode'. Estimates of the readmission rate were biased for several patient groups owing to missed matches, which was reduced for nearly all groups.
conclusionProbabilistic linkage of HES reduced missed matches and bias in estimated readmission rates, with clear implications for commissioning, service evaluation and performance monitoring of hospitals. The existing algorithm should be modified to address data linkage error, and a retrospective update of the existing data would address existing linkage errors and their implications.
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