Adapting historical clinical genetic test records for anonymised data linkage: obstacles and opportunities

Extracting useful information from historical clinical genetic test records is a significant challenge with technical and governance aspects. The mixing of unique identifiers with clinical data in heterogeneous, unstructured free text combined with a lack of automated tools meant that manual annotation was required to adhere to the separation principle. As such, only a minimum of the available clinical data was annotatable within the project timeline and mutually exclusive access to the identifiable and pseudonymised data meant that annotations could not later be validated. Future efforts to link clinical genetic test records for research must consider these challenges in their approach.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-02-20
DOI
https://doi.org/10.23889/ijpds.v8i5.2924
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00

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article

Adapting historical clinical genetic test records for anonymised data linkage: obstacles and opportunities

Kate Reed, Andrew E. Fry, Ralph Maddison, Fiona Lugg‐Widger et al.
International Journal for Population Data Science
Genomics and Rare Diseases
article

Adapting historical clinical genetic test records for anonymised data linkage: obstacles and opportunities

Kate Reed, Andrew E. Fry, Ralph Maddison, Fiona Lugg‐Widger, Rebecca L. Cannings-John, Sarah Anderson, Thomas Stoneman
article en

Abstract

Extracting useful information from historical clinical genetic test records is a significant challenge with technical and governance aspects. The mixing of unique identifiers with clinical data in heterogeneous, unstructured free text combined with a lack of automated tools meant that manual annotation was required to adhere to the separation principle. As such, only a minimum of the available clinical data was annotatable within the project timeline and mutually exclusive access to the identifiable and pseudonymised data meant that annotations could not later be validated. Future efforts to link clinical genetic test records for research must consider these challenges in their approach.

International Journal for Population Data ScienceVol. 8(5)
Public Health Wales (GB), Genomics (United Kingdom) (GB), Cardiff University (GB)
Health and Care Research Wales, Parc Geneteg Cymru, Cardiff University
Openalex Percentile: Top 96%
Genomics and Rare Diseases
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Adapting historical clinical genetic test records for anonymised data linkage: obstacles and opportunities — Kate Reed, Andrew E. Fry, et al. · International Journal for Population Data Science (2025) | TGRS Research Map | TGRS