Methods Inf Med 2017; 56(04): 330-338
DOI: 10.3414/ME16-02-0027
Chronic Disease Registries
Schattauer GmbH

Mapping Acute Coronary Syndrome Registries to SNOMED CT

A Comparative Study between Malaysia and Sweden
Ismat Mohd Sulaiman
1   Health Informatics Centre, Planning Division, Ministry of Health Malaysia, Putrajaya, Malaysia
,
Daniel Karlsson
2   Department of Biomedical Engineering, Linköping University, Linköping, Sweden
,
Sabine Koch
3   Health Informatics Centre, Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden
› Author Affiliations
Further Information

Publication History

received: 01 September 2016

accepted in revised form: 27 January 2017

Publication Date:
24 January 2018 (online)

Summary

Background: 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.

Objectives: 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.

Methods: 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.

Results: 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-coordi- nated 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.

Conclusions: 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.

 
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