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Technical challenges of providing record linkage services for research

Overview of attention for article published in BMC Medical Informatics and Decision Making, March 2014
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Technical challenges of providing record linkage services for research
Published in
BMC Medical Informatics and Decision Making, March 2014
DOI 10.1186/1472-6947-14-23
Pubmed ID
Authors

James H Boyd, Sean M Randall, Anna M Ferrante, Jacqueline K Bauer, Adrian P Brown, James B Semmens

Abstract

Record linkage techniques are widely used to enable health researchers to gain event based longitudinal information for entire populations. The task of record linkage is increasingly being undertaken by specialised linkage units (SLUs). In addition to the complexity of undertaking probabilistic record linkage, these units face additional technical challenges in providing record linkage 'as a service' for research. The extent of this functionality, and approaches to solving these issues, has had little focus in the record linkage literature. Few, if any, of the record linkage packages or systems currently used by SLUs include the full range of functions required.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Australia 2 4%
Canada 1 2%
Unknown 48 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 30%
Student > Master 12 23%
Professor > Associate Professor 5 9%
Student > Ph. D. Student 5 9%
Student > Bachelor 4 8%
Other 7 13%
Unknown 4 8%
Readers by discipline Count As %
Computer Science 15 28%
Medicine and Dentistry 12 23%
Biochemistry, Genetics and Molecular Biology 3 6%
Nursing and Health Professions 3 6%
Social Sciences 3 6%
Other 8 15%
Unknown 9 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 May 2017.
All research outputs
#14,102,908
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,006
of 2,030 outputs
Outputs of similar age
#113,759
of 228,653 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 30 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 228,653 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.