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Mapping Acute Coronary Syndrome Registries to SNOMED CT

Overview of attention for article published in Methods of Information in Medicine, January 2018
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Mapping Acute Coronary Syndrome Registries to SNOMED CT
Published in
Methods of Information in Medicine, January 2018
DOI 10.3414/me16-02-0027
Pubmed ID
Authors

Ismat Mohd Sulaiman, Daniel Karlsson, Sabine Koch

Abstract

Malaysia and Sweden have mapped their acute coronary syndrome registries using SNOMED CT. Since similar-purposed patient registries can be expected to collect similar data, these data should be mapped to the same SNOMED CT codes despite the different languages used. Previous studies have however shown variations in mapping between different mappers but the reasons behind these variations and the influence of different mapping approaches are still unknown. To analyze similar-purposed registries and their registry-to-SNOMED CT maps, using two national acute coronary syndrome registries as examples, to understand the reasons for mapping similarities and differences as well as their implications. The Malaysian National Cardiovascular Disease - Acute Coronary Syndrome (NCVD-ACS) registry was compared to the Swedish Register of Information and Knowledge about Swedish Heart Intensive Care Admissions (RIKS-HIA). The structures of NCVD-ACS and RIKS-HIA registry forms and their distributions of headings, variables and values were studied. Data items with equivalent meaning (EDIs) were paired and their mappings were categorized into match, mismatch, and non-comparable mappings. Reasons for match, mismatch and non-comparability of each paired EDI were seen as factors that contributed to the similarities and differences between the maps. The registries and their respective maps share a similar distribution pattern regarding the number of headings, variables and values. The registries shared 101 EDIs, whereof 42 % (42) were mapped to SNOMED CT. 45 % (19) of those SNOMED CT coded EDIs had matching codes. The matching EDIs occurred only in pre-coordinated SNOMED CT expressions. Mismatches occurred due to challenges arising from the mappers themselves, limitations in SNOMED CT, and complexity of the registries. Non-comparable mappings appeared due to the use of other coding systems, unmapped data items, as well as requests for new SNOMED CT concepts. To ensure reproducible and reusable maps, the following three actions are recommended: (i) develop a specific mapping guideline for patient registries; (ii) openly share maps; and (iii) establish collaboration between clinical research societies and the SNOMED CT community.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 5%
Unknown 19 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 15%
Student > Doctoral Student 3 15%
Lecturer > Senior Lecturer 1 5%
Other 1 5%
Student > Bachelor 1 5%
Other 5 25%
Unknown 6 30%
Readers by discipline Count As %
Medicine and Dentistry 6 30%
Computer Science 5 25%
Agricultural and Biological Sciences 1 5%
Social Sciences 1 5%
Economics, Econometrics and Finance 1 5%
Other 0 0%
Unknown 6 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 August 2017.
All research outputs
#8,260,791
of 25,382,440 outputs
Outputs from Methods of Information in Medicine
#146
of 697 outputs
Outputs of similar age
#156,637
of 450,340 outputs
Outputs of similar age from Methods of Information in Medicine
#115
of 521 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 697 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 79% of its peers.
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 450,340 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 521 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.