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March 12, 2026JMIR Medical Informatics2 citationsOpen Access

Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation

PNParvati NaliyatthaliyazchayilTSTravis Stenerson

Key Points

  • The aim is to develop a normalization process to improve laboratory data quality in oncology systems.
  • Developed a system-agnostic normalization process
  • Evaluated gaps in laboratory data quality
  • Focused on therapy selection and disease monitoring
  • Identified key gaps in current laboratory data quality
  • Proposed a scalable solution for data normalization
  • Enhanced consistency in data reporting across systems

Abstract

Laboratory data quality is crucial in oncology systems for therapy selection, monitoring, and disease progression assessment. This proposed solution is a first-of-its-kind, system-agnostic, and scalable normalization process that addresses key gaps in laboratory data quality across multiple dimensions.

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Cite This Study

Naliyatthaliyazchayil et al. (2026) studied this question.

synapsesocial.com/papers/69b2589696eeacc4fcec85achttps://doi.org/10.2196/81254
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review2022 · 251 citations
  2. 2The LOINC Content Model and Its Limitations of Usage in the Laboratory Domain2020 · 18 citations
  3. 3The role of blood testing in prevention, diagnosis, and management of chronic diseases: A review2024 · 23 citations
  4. 4Unit conversions between LOINC codes2017 · 21 citations
  5. 5Detecting data errors2016 · 247 citations