Suzanne Pereira

Multiple Terminologies in a Health Portal: Automatic Indexing and Information Retrieval

Background: In the specific context of developing quality-controlled health gateways, several standards must be respected (e.g. Dublin Core for metadata element set; thesaurus MeSH as the controlled vocabulary to index Internet resources; HON code to accredit quality of health Web sites). These standards were applied to create the CISMeF Web site (French acronym for Catalog & Index of Health Internet resources in French). Objective: In this work, the strategic shift of the CISMeF team is intended to index and retrieve French resources not anymore with a single terminology (MeSH thesaurus) but with the main health terminologies available in French (ICD 10, SNOMED International, CCAM, ATC). Methods & Results: Since 2005, we have developed the French Multi-Terminology Indexer (F-MTI), using a multi-terminology approach and mappings between health terminologies. This tool is used for automatic indexing and information retrieval. Conclusion: Since the last quarter of 2008, F-MTI is daily used in the CISMeF production environment and is connected to a French Health Multi-Terminology Server.

Linguistic and temporal processing for discovering hospital acquired infection from patient records

This paper describes the first steps of development of a rulebased system that automatically processes medical records in order to discover possible cases of hospital acquired infections (HAI). The system takes as input a set of patient records in electronic format and gives as output, for each document, information regarding HAI. In order to achieve this goal, a temporal processing together with a deep syntactic and semantic analysis of the patient records is performed. Medical knowledge used by the rules is derived from a set of documents that have been annotated by medical doctors. After a brief description of the context of this work, we present the general architecture of our document processing chain and explain how we perform our temporal and linguistic analysis. Finally, we report our preliminary results and we lay out the next steps of the project.

Improving access to clinical practice guidelines with an interactive graphical interface using an iconic language

BackgroundClinical practice guidelines are useful for physicians, and guidelines are available on the Internet from various websites such as Vidal Recos. However, these guidelines are long and difficult to read, especially during consultation. Similar difficulties have been encountered with drug summaries of product characteristics. In a previous work, we have proposed an iconic language (called VCM, for Visualization of Concepts in Medicine) for representing patient conditions, treatments and laboratory tests, and we have used these icons to design a user interface that graphically indexes summaries of product characteristics. In the current study, our objective was to design and evaluate an iconic user interface for the consultation of clinical practice guidelines by physicians.MethodsFocus groups of physicians were set up to identify the difficulties encountered when reading guidelines. Icons were integrated into Vidal Recos, taking human factors into account. The resulting interface includes a graphical summary and an iconic indexation of the guideline. The new interface was evaluated. We compared the response times and the number of errors recorded when physicians answered questions about two clinical scenarios using the interactive iconic interface or a textual interface. Users’ perceived usability was evaluated with the System Usability Scale.ResultsThe main difficulties encountered by physicians when reading guidelines were obtaining an overview and finding recommendations for patients corresponding to “particular cases”. We designed a graphical interface for guideline consultation, using icons to identify particular cases and providing a graphical summary of the icons organized by anatomy and etiology. The evaluation showed that physicians gave clinical responses more rapidly with the iconic interface than the textual interface (25.2 seconds versus 45.6, p < 0.05). The physicians appreciated the new interface, and the System Usability Scale score value was 75 (between good and excellent).ConclusionAn interactive iconic interface can provide physicians with an overview of clinical practice guidelines, and can decrease the time required to access the content of such guidelines.

Évaluation d’un outil d’aide á l’anonymisation des documents médicaux basé sur le traitement automatique du langage naturel

Anonymization of personal data is a legal requirement for their use as part of a research project. In the context of developing a tool for detecting hospital-acquired infections, 2000 medical documents were needed for the research project ALADIN. To help annotators to anonymize this corpus of documents, a tool for the anonymization has been developed, relying on Natural Language Processing techniques. The recall, precision and F-score of the automatic phase of the anonymizer were respectively 79.7, 85.2 and 82.4%. The gold- standard used for the evaluation was the manual anonymization of the documents. The performance of the automatic anonymization can still be improved but the tool is already a considerable help in this process in terms of saving time and in terms of quality of anonymization (including the accuracy of labeling anonymized terms and computation of time duration).

Recherche d’information multiterminologique en contexte: étude préliminaire

Background: Information retrieval becomes more relevant thanks to document (semi)automatic indexation with terminologies adapted to the domain. Being interested in the medical domain, we used the main health terminologies available in French in two different contexts: (a) during the health resource indexation process and (b) during the information retrieval. Methods: Within the CISMeF catalog (French acronym of Catalogue et index des Sites Medicaux Francophones), we have evolved from a monoterminological world (based on the MeSH thesaurus) to a multi-terminological universe (based on ICDIO, CCAM, SNOMED terminologies and ATC classification). This new structure allows us to make the information retrieval in two different contexts: to retrieve (a) reports from the electronic health record (EHR) of patients and (b) resources from a health portal (such as CISMeF). Results: Both contexts share the same representation meta-model, however, they differ during the information retrieval, according to the size and the nature of the corpus, the role of dates and the query, which can include both structured and unstructured elements in EHR. Conclusion: In 2008, the information retrieval has already become multi-terminological in the Drug Information Portal and will become available in the catalog CISMeF at the beginning of 2009.

F-MTI: outil d’indexation muititerminologique: application à l’indexation automatique de la SNOMED International

Background SNOMED is becoming a major health terminology to index electronic medical records. Most of developed countries have chosen SNOMED CT. France has chosen SNOMED International which is already translated in French. We developed the F-MTI tool, a generic automatic indexing tool able to index documentation in several health terminologies written in French (CCAM, TUV) or translated in French (MeSH, ICD-lO, SNOMED International).

Codage standardisé de données médicales textuelles à l’aide d’un serveur multi-terminologique de santé: Exemple d’application en épidémiologie hospitalière

Currently, extraction of data for epidemiological surveillance is severely limited by the lack of standardised structuring of medical records. The objective of this study is to describe a semi-automatic method for standardized coding of textual medical records for epidemiological use. In the context of the ALADIN-DTH research project, we are planning to develop a tool for detecting nosocomial infections. With that goal in mind we will ask physicians to manually code 2,000 hospital medical records using different appropriate medical terminologies (ICD10, SNOMED 3.5, ATC, CCAM, MeSH). A French automatic Multi-Terminology Health Concept Extractor (French acronym: ECMT) can offer a choice of labels and codes of different terminologies. This tool can be called on a distant server via an Internet connection thanks to an XML service. Among 3,450 medical expressions queried by users, the ECMT has proposed relevant codes for 70,5% of them (original formulation) and 87,7% of them after correction of the formulation by the annotator, this result ranging from 51,3% (bacteriological examinations) to 96,4% (symptoms/diagnoses). A multi-terminology health concept extractor is an interesting tool for standardized coding of textual data for epidemiological use.

InterSTIS: Interopérabilité sémantique de terminologies de santé francophones

Background: the proliferation of health-related documents raises issues of indexing and search in large databases. Various terminologies are then used to index documents of all types: SNOMED Int. for clinical information coding, ICD-10 and the French CCAM for medico-economic coding, ICPC used by general practitioners, the MeSH for scientific literature, etc. Objective: the goal of the project InterSTIS was to unify these terminologies and to make them interoperable within a “multisource terminology server”. Material and method: the design and developments are based on standards and norms recognized for modeling and implementation. Results: results are a meta-model for healthcare terminologies, the integration of some of them in a unique system, the mapping of terminologies by means of the UMLS Metathesaurus, and the demonstration made by the integration of a new terminology dedicated to drugs documentation, and services applied to indexing and retrieving information. Discussion: further developments may involve both the National Cancer Institute Metathesaurus and the Semantic Network of the UMLS which complete the UMLS Metathesaurus by means of explicit semantic relationships.

Extraction des noms de médicaments dans les comptes rendus hospitaliers

Background: We report here the implementation of a medication extraction system which extracts drugs names from French clinical texts, on the basis of Natural Language Processing algorithms (NLP). Within the framework of the PSIP project, the French Multi- Terminology Indexer (FMTI) is used to extract drug-related information from records for the detection of Adverse Drug Events (ADEs) that can endanger the patients. FMTI is here needed in the absence of computerized physician order entry (CPOE), because then discharged summaries are the only source of information about the drugs prescribed during hospitalization. Methods: FMTI uses appropriate terminologies (TUV, ATC, DCI, NC) with different algorithms using stemming and phonemization. We performed two evaluations to measure the performances of the FMTI tool to extract medication codes from free-text documents: one using the stemming algorithm and the other using the phonemization algorithm. Results: The FMTI tool performs better results using the phonemization algorithm: 97% for precision and 95% for recall. Conclusion: For the PSIP project, we showed that the semantic mining using FMTI can help to extract drug- related information from records in absence of CPOE.