Mapping Local Codes to Read Codes

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

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

2 Citations (Scopus)
100 Downloads (Pure)

Abstract

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.

Original languageEnglish
Title of host publicationBuilding Capacity for Health Informatics in the Future
EditorsFrancis Lau, John Bartle-Clar, Gerry Bliss, Elizabeth Borycki, Karen Courtney, Alex Kuo
Place of PublicationAmsterdam
PublisherIOS Press
Pages29-36
Number of pages8
ISBN (Electronic)9781614997429
ISBN (Print)9781614997412
DOIs
Publication statusPublished - 2017

Publication series

NameStudies in Health Technology and Informatics
PublisherIOS Press
Volume234

Keywords

  • Clinical Datasets
  • Read Codes
  • Data Mapping
  • Health Data Standards

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  • Cite this

    Bonney, W., Galloway, J., Hall, C., Ghattas, M., Tramma, L., Nind, T., Donnelly, L., Jefferson, E., & Doney, A. (2017). Mapping Local Codes to Read Codes. In F. Lau, J. Bartle-Clar, G. Bliss, E. Borycki, K. Courtney, & A. Kuo (Eds.), Building Capacity for Health Informatics in the Future (pp. 29-36). (Studies in Health Technology and Informatics; Vol. 234). IOS Press. https://doi.org/10.3233/978-1-61499-742-9-29