Supporting trend detection in the cumulative display of electronic laboratory reports from multiple laboratories while preserving measurement provenance

Electronic health records will increasingly aggregate longitudinal laboratory results from multiple providers, but availability alone does not guarantee safe interpretation. We present guidance, developed by laboratory professionals with the DGKL medical informatics division, for cumulative displays that are clinically meaningful. The core principle is to group medically comparable analyses while preserving laboratory provenance so that clinicians can follow true patient trends without conflating them with laboratory-induced variation. Comparability is defined algorithmically from Logical Observation Identifiers Names and Codes (LOINC) axis: analyses estimating the same patient property (allowing serum/plasma system equivalence and mathematically convertible properties such as substance vs. mass concentration) are grouped; coding of units is harmonized via Unified Code for Units of Measure (UCUM) with consistent conversion of numeric results and corresponding reference intervals, including inequality qualifiers. Analyte-specific conversion factors should come from authoritative sources; for poorly standardized measurands (e.g., tumor markers) or when conversions are inappropriate (e.g., Lp(a)), results remain separated. Methodological distinctions that affect interpretation - such as screening vs. confirmatory drug testing and point-of-care testing - are displayed independently to signal potential analytical discontinuities. A standardized, medically meaningful default result sequence - derived from LOINC metadata and clinical nomenclatures, with alphabetic naming as a pragmatic fallback - supports cross-laboratory aggregation; rare or novel tests lacking robust standardization remain as free text. The rules-based approach updates seamlessly with LOINC releases and remains compatible with the Nomenclature for Properties and Units (NPU), facilitating cross-border exchange within the European Health Data Space. While harmonized presentation improves trend analysis, true comparability ultimately requires measurement procedures traceable to reference methods and materials.

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Publication Details

Journal
Clinical Chemistry and Laboratory Medicine (CCLM)
Published
2025-09-24
DOI
https://doi.org/10.1515/cclm-2025-1160
Citations
3
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
3.49
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article

Supporting trend detection in the cumulative display of electronic laboratory reports from multiple laboratories while preserving measurement provenance

Andreas Bietenbeck, Alexander Tolios, Julian Gebauer, Jakob Adler et al.
3 citations
Clinical Chemistry and Laboratory Medicine (CCLM)
Clinical Laboratory Practices and Quality Control
3.49
article

Supporting trend detection in the cumulative display of electronic laboratory reports from multiple laboratories while preserving measurement provenance

Andreas Bietenbeck, Alexander Tolios, Julian Gebauer, Jakob Adler, Bernhard Wiegel, Matthias Orth, Alexander Meyer, Thomas Streichert, Jürgen Durner, Bernd Müller, Sascha Lüdemann
article en
3 citations

Abstract

Electronic health records will increasingly aggregate longitudinal laboratory results from multiple providers, but availability alone does not guarantee safe interpretation. We present guidance, developed by laboratory professionals with the DGKL medical informatics division, for cumulative displays that are clinically meaningful. The core principle is to group medically comparable analyses while preserving laboratory provenance so that clinicians can follow true patient trends without conflating them with laboratory-induced variation. Comparability is defined algorithmically from Logical Observation Identifiers Names and Codes (LOINC) axis: analyses estimating the same patient property (allowing serum/plasma system equivalence and mathematically convertible properties such as substance vs. mass concentration) are grouped; coding of units is harmonized via Unified Code for Units of Measure (UCUM) with consistent conversion of numeric results and corresponding reference intervals, including inequality qualifiers. Analyte-specific conversion factors should come from authoritative sources; for poorly standardized measurands (e.g., tumor markers) or when conversions are inappropriate (e.g., Lp(a)), results remain separated. Methodological distinctions that affect interpretation - such as screening vs. confirmatory drug testing and point-of-care testing - are displayed independently to signal potential analytical discontinuities. A standardized, medically meaningful default result sequence - derived from LOINC metadata and clinical nomenclatures, with alphabetic naming as a pragmatic fallback - supports cross-laboratory aggregation; rare or novel tests lacking robust standardization remain as free text. The rules-based approach updates seamlessly with LOINC releases and remains compatible with the Nomenclature for Properties and Units (NPU), facilitating cross-border exchange within the European Health Data Space. While harmonized presentation improves trend analysis, true comparability ultimately requires measurement procedures traceable to reference methods and materials.

Clinical Chemistry and Laboratory Medicine (CCLM)Vol. 64(3)
University of Stuttgart (DE), University of Passau (DE), Medizinisches Versorgungszentrum Prof. Mathey, Prof. Schofer (DE), Krankenhaus Barmherzige Brüder (DE), Sonic Healthcare (Germany) (DE), Pathodiagnostik Berlin (DE), CS Diagnostics (DE), CBL (Germany) (DE), University Hospital Cologne (DE), Medical University of Vienna (AT)
Openalex Percentile: Top 7%
Clinical Laboratory Practices and Quality Control
3.49
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