1. Translating patient-related narratives into SNOMED-CT to enable interoperability of healthcare data
SNOMED-CT representation
Radiologic report
Admission Letter
Discharge Letter
Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) offers a very large semantic combinatorial coverage and can be used to represent any medical concept.
Electronic Health Records (EHRs) are principally composed of:
Structured data
Narrative data (free text)
Narrative data contains crucial semantic and conceptual information.
However, the major part of narrative data is not reused.
|Vitamin measurement
|situation with explicit context|:
Refinement
|Level =
#70
|Associated finding =
|Serum vitamin B12 low
Refinement
|Units =
= |Nanogram/liter
“Translating” narratives into SNOMED-CT would bring unprecedented possibilities for primary and secondary usage.
Goal: automatic translation of narratives into SNOMED-CT sentences
Corpus processing using Natural Language Processing (NLP) tools
Fips syntactic parser
Unitex corpus processor
NLP Tools
Automatic SNOMED-CT Translation
De-identification of Protected Health Information (PHI) following HIPAA rules
using finite state automata
Corpus of de-identified French narratives
Syntactico-semantic analysis
SNOMED-CT representation
Radiologic report
Admission Letter
Discharge Letter
Creation of a corpus of patient related narratives extracted from EHRs
Information Extraction (IE)
Monsieur Blavignac a été transféré aux Hôpitaux Universitaires de Genève le 6 décembre 2012.
Monsieur Nompatient a été transféré à l’Hôpital le 30 février 2012.
Named-Entity Recognition (NER)
Monolingual electronic dictionaries
Construction of lexico-semantic resources of French medical terms followed by morphological, semantic and syntactic features
Evaluation of the performance of the translation tool
Gold standard corpus
Creation of a gold standard corpus
Bilingual electronic dictionaries
Local grammars
Manual translation into SNOMED-CT
SNOMED-CT Translation
Conclusion
Automatic annotation of a corpus of 11’000 discharge summaries
Results
Examples of annotated sentences
Annotation evaluation
5 discharge summaries (1’820 words) manually annotated with SNOMED-CT concepts by an expert
By mapping the equivalences between simple terms, collocations and SNOMED- CT concepts, 421 medical terms were automatically annotated.
First evaluation results (perfect match):
Precision: 0,7173
Recall: 0,5171
F-score: 0,6009
Remarks
The automatic translation of medical free text into SNOMED-CT is a demanding and cost- effective task
Constructing lexico-semantic resources is a mandatory step to process medical natural language
Automatic post-coordination can be performed by implementing rules derived from the SNOMED-CT compositional grammar in a syntactico-semantic parser.
Next steps
Improvement of the post-coordination
Processing of the negation, e.g. Il n'y a pas de signe d'insuffisance circulatoire
Enrichment of the lexico-semantic resources
Enrichment of the corpora
Evaluation of translation
Corpus size (words)
4’481’191
Annotated terms
892’787
Unique SNOMED-CT concepts
7’569
Annotated terms per sentence
4.17
Un cathétérisme cardiaque droit sera réalisé chez le patient.
SNOMED-CT code
French term
cathétérisme du cœur droit
réalisé
patient
Post-coordination
Example of automatic translation after partial implementation of post- coordination rules following SNOMED-CT compositional grammar.
Le patient présente une plaie du pied droit.
| plaie
Le patient prend des anti-inflammatoires, traitement qui est poursuivi durant l'hospitalisation.
SNOMED-CT code
French term
patient
anti-inflammatoire
poursuivre le traitement
hospitalisation
| finding site
| pied
{ | patient | },
{ | plaie | :
| finding site | = | pied | :
| laterality | = | droit | }
| laterality
| droit
Christophe GAUDET-BLAVIGNAC, Bmed, Mmed, BSc CS Vasiliki FOUFI, PhD
Eric WEHRLI, PhD
Christian LOVIS, MD MPH