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Mapping Local Codes to Read Codes.

作者信息

Bonney Wilfred, Galloway James, Hall Christopher, Ghattas Mikhail, Tramma Leandro, Nind Thomas, Donnelly Louise, Jefferson Emily, Doney Alexander

机构信息

Health Informatics Centre, University of Dundee, Dundee, Scotland, United Kingdom.

出版信息

Stud Health Technol Inform. 2017;234:29-36.

Abstract

UNLABELLED

Background & Objectives: Legacy laboratory test codes make it difficult to use clinical datasets for meaningful translational research, where populations are followed for disease risk and outcomes over many years. The Health Informatics Centre (HIC) at the University of Dundee hosts continuous biochemistry data from the clinical laboratories in Tayside and Fife dating back as far as 1987. However, the HIC-managed biochemistry dataset is coupled with incoherent sample types and unstandardised legacy local test codes, which increases the complexity of using the dataset for reasonable population health outcomes. The objective of this study was to map the legacy local test codes to the Scottish 5-byte Version 2 Read Codes using biochemistry data extracted from the repository of the Scottish Care Information (SCI) Store.

METHODS

Data mapping methodology was used to map legacy local test codes from clinical biochemistry laboratories within Tayside and Fife to the Scottish 5-byte Version 2 Read Codes.

RESULTS

The methodology resulted in the mapping of 485 legacy laboratory test codes, spanning 25 years, to 124 Read Codes.

CONCLUSION

The data mapping methodology not only facilitated the restructuring of the HIC-managed biochemistry dataset to support easier cohort identification and selection, but it also made it easier for the standardised local laboratory test codes, in the Scottish 5-byte Version 2 Read Codes, to be mapped to other health data standards such as Clinical Terms Version 3 (CTV3); LOINC; and SNOMED CT.

摘要

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