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Related Concept Videos

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Nursing Clinical Information System

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Related Experiment Video

Updated: Jun 25, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

LOINC codes for hospital information systems documents: a case study.

Martin Dugas1, Sylvia Thun, Thomas Frankewitsch

  • 1Department of Medical Informatics and Biomathematics, University of Münster, Germany, Domagkstr 9; D-48149 Münster; Germany. dugas@uni-muenster.de

Journal of the American Medical Informatics Association : JAMIA
|March 6, 2009
PubMed
Summary
This summary is machine-generated.

Standardized coding of clinical documents in Hospital Information Systems (HIS) is crucial for data exchange. This study found that while most German HIS document types can be mapped to LOINC codes, many lack specificity.

Related Experiment Videos

Last Updated: Jun 25, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

  • Health Informatics
  • Medical Documentation
  • Clinical Data Standards

Background:

  • Hospital Information Systems (HIS) generate diverse document types, necessitating standardized identification for effective data exchange and analysis.
  • HL7's Clinical Document Architecture (CDA) utilizes LOINC (Logical Observation Identifiers Names and Codes) for clinical document classification.
  • Assessing the adequacy of LOINC code coverage for local HIS document types is essential for interoperability.

Purpose of the Study:

  • To evaluate the coverage and specificity of LOINC codes for document types within a German Hospital Information System (HIS).
  • To determine the proportion of local HIS documents that can be assigned a LOINC code for improved data standardization.

Main Methods:

  • Analysis of approximately 1.3 million documents from a commercial HIS at a German University Hospital.
  • Manual mapping of frequently occurring document types (>10 occurrences) to LOINC codes using the Regenstrief LOINC Mapping Assistant (RELMA).
  • Consensus-based coding by two physicians, with a third expert consulted for discrepancies.

Main Results:

  • LOINC codes were identified for 76 out of 86 analyzed document categories (88.4%).
  • A significant proportion, 38 of the identified LOINC codes (50%), were not specific enough for the local document types.
  • Over 93% of local HIS document types could be assigned a LOINC code, indicating broad, albeit sometimes non-specific, coverage.

Conclusions:

  • LOINC provides broad coverage for document types in German HIS, facilitating data standardization and exchange.
  • A substantial number of mapped LOINC codes lack the necessary specificity, highlighting a need for more granular coding options.
  • Further refinement of LOINC or local mapping strategies is required to enhance the precision of clinical document identification in HIS.