Mapping French terms in a Belgian guideline on heart failure to international classifications and nomenclatures: the devil is in the detail.

INTRODUCTION With growing sophistication of eHealth platforms, medical information is increasingly shared across patients, health care providers, institutions and across borders. This implies more stringent demands on the quality of data entry at the point-of-care. Non-native English-speaking general practitioners (GPs) experience difficulties in interacting with international classification systems and nomenclatures to facilitate the secondary use of their data and to ensure semantic interoperability. AIM To identify words and phrases pertaining to the heart failure domain and to explore the difficulties in mapping to corresponding concepts in ICPC-2, ICD-10, SNOMED-CT and UMLS. METHODS The medical concepts in a Belgian guideline for GPs in its French version were extracted manually and coded first in ICPC-2, then ICD-10 by a physician, an expert in classification systems. In addition, mappings were sought with SNOMED-CT and UMLS concepts, using the UMLS SNOMED-CT browser. RESULTS We identified 143 words and phrases, of which 128 referred to a single concept (1-to-1 mapping), while 15 referred to two or more concepts (1-to-n mapping to ICPC rubrics or to the other nomenclatures). In the guideline, words or phrases were often too general for specific mapping to a code or term. Marked discrepancy between semantic tags and types was found. CONCLUSION This article shows the variability of the various international classifications and nomenclatures, the need for structured guidelines with more attention to precise wording and the need for classification expertise embedded in sophisticated terminological resources. End users need support to perform their clinical work in their own language, while still assuring standardised and semantic interoperable medical registration. Collaboration between computational linguists, knowledge engineers, health informaticians and domain experts is needed.

[1]  U. Eco,et al.  Dire quasi la stessa cosa : esperienze di traduzione , 2003 .

[2]  S. de Lusignan.  Codes, classifications, terminologies and nomenclatures: definition, development and application in practice. , 2005, Informatics in primary care.

[3]  I R McWhinney,et al.  Patient-centred care: the family practice model. , 1983, Canadian family physician Medecin de famille canadien.

[4]  George Hripcsak,et al.  Evaluation of a UMLS Auditing Process of Semantic Type Assignments , 2007, AMIA.

[5]  Laurent Romary,et al.  Towards a terminologies support system in primary care. , 2011, Informatics in primary care.

[6]  Elena Cardillo,et al.  Using ISO and Semantic Web standards for creating a Multilingual Medical Interface Terminology : A use case for Hearth Failure. , 2013 .

[7]  S. de Lusignan,et al.  The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review , 2013, Yearbook of Medical Informatics.

[8]  Werner Ceusters,et al.  An Ontology-Based Methodology for the Migration of Biomedical Terminologies to Electronic Health Records , 2005, AMIA.

[9]  G. Canguilhem,et al.  On the Normal and the Pathological , 1978 .

[10]  Werner Ceusters,et al.  Syntactic-semantic tagging as a mediator between linguistic representations and formal models: an exercise in linking SNOMED to GALEN , 1999, Artif. Intell. Medicine.

[11]  M Jamoulle,et al.  ICPC-2-E: the electronic version of ICPC-2. Differences from the printed version and the consequences. , 2000, Family practice.

[12]  Susan Leigh Star,et al.  Sorting Things Out: Classification and Its Consequences , 1999 .

[13]  Carol Friedman,et al.  Word Sense Disambiguation via Semantic Type Classification , 2008, AMIA.

[14]  Casimir A. Kulikowski,et al.  Vocabulary Requirements for Implementing Clinical Guidelines in an Electronic Medical Record: A Case Study , 2005, AMIA.

[15]  Sachin H. Jain,et al.  Practicing medicine in the age of Facebook. , 2009, The New England journal of medicine.

[16]  Umberto Eco,et al.  Mouse or Rat?: Translation as Negotiation , 2003 .

[17]  William Long,et al.  Extracting Diagnoses from Discharge Summaries , 2005, AMIA.

[18]  Olivier Bodenreider,et al.  Integrating Consumer-Oriented Vocabularies with Selected Professional Ones from the UMLS Using Semantic Web Technologies , 2010, eHealth.

[19]  Diego Calvanese,et al.  The VERICLIG Project: Extraction of Computer Interpretable Guidelines via Syntactic and Semantic Annotation , 2013 .

[20]  M. Raizada,et al.  Language Preferences on Websites and in Google Searches for Human Health and Food Information , 2007, Journal of medical Internet research.

[21]  J. Marc Overhage,et al.  Case Report: Computerizing Guidelines to Improve Care and Patient Outcomes: The Example of Heart Failure , 1995, J. Am. Medical Informatics Assoc..