Integrating a new knowledge organisation system for monoclonal antibodies for therapeutic use authorised in Europe into HeTOP terminology-ontology server.

Monoclonal antibodies (MAs) are increasingly used in the therapeutic arsenal. Clinical Data Warehouses (CDWs) offer unprecedented opportunities for research on real-word data. The objective of this work is to develop a knowledge organization system on MAs for therapeutic use (MATUs) applicable in Europe to query CDWs from a multi-terminology server (HeTOP). After expert consensus, three main health thesauri were selected: the MeSH thesaurus, the National Cancer Institute thesaurus (NCIt) and the SNOMED CT. These thesauri contain 1,723 MAs concepts, but only 99 (5.7 %) are identified as MATUs. The knowledge organisation system proposed in this article is a six-level hierarchical system according to their main therapeutic target. It includes 193 different concepts organised in a cross lingual terminology server, which will allow the inclusion of semantic extensions. Ninety nine (51.3 %) MATUs concepts and 94 (48.7 %) hierarchical concepts composed the knowledge organisation system. Two separates groups (an expert group and a validation group) carried out the selection, creation and validation processes. Queries identify, for unstructured data, 83 out of 99 (83.8 %) MATUs corresponding to 45,262 patients, 347,035 hospital stays and 427,544 health documents, and for structured data, 61 out of 99 (61.6 %) MATUs corresponding to 9,218 patients, 59,643 hospital stays and 104,737 hospital prescriptions. The volume of data in the CDW demonstrated the potential for using these data in clinical research, although not all MATUs are present in the CDW (16 missing for unstructured data and 38 for structured data). The knowledge organisation system proposed here improves the understanding of MATUs, the quality of queries and helps clinical researchers retrieve relevant medical information. The use of this model in CDW allows for the rapid identification of a large number of patients and health documents, either directly by a MATU of interest (e.g. Rituximab) but also by searching for parent concepts (e.g. Anti-CD20 Monoclonal Antibody).

Decision-support systems for managing polypharmacy in the elderly: A scoping review.

Polypharmacy, the consuming of more than five drugs, is a public health problem. It can lead to many interactions and adverse drug reactions and is very expensive. Therapeutic guidelines for managing polypharmacy in the elderly have been issued, but are highly complex, limiting their use. Decision-support systems have therefore been developed to automate the execution of these guidelines, or to provide information about drugs adapted to the context of polypharmacy. These systems differ widely in terms of their technical design, knowledge sources and evaluation methods. We present here a scoping review of electronic systems for supporting the management, by healthcare providers, of polypharmacy in elderly patients. Most existing reviews have focused mainly on evaluation results, whereas the present review also describes the technical design of these systems and the methodologies for developing and evaluating them. A systematic bibliographic search identified 19 systems differing considerably in terms of their technical design (rule-based systems, documentary approach, mixed); outputs (textual report, alerts and/or visual approaches); and evaluations (impact on clinical practices, impact on patient outcomes, efficiency and/or user satisfaction). The evaluations performed are minimal (among all the systems identified, only one system has been evaluated according to all the criteria mentioned above) and no machine learning systems and/or conflict management systems were retrieved. This review highlights the need to develop new methodologies, combining various approaches for decision support system in polypharmacy.

Modeling and integrating interactions involving the CYP450 enzyme system in a multi-terminology server: Contribution to information extraction from a clinical data warehouse.

INTRODUCTION: The cytochrome P450 (CYP450) enzyme system is involved in the metabolism of certain drugs and is responsible for most drug interactions. These interactions result in either an enzymatic inhibition or an enzymatic induction mechanism that has an impact on the therapeutic management of patients. Detecting these drug interactions will allow for better predictability in therapeutic response. Therefore, computerized solutions can represent a valuable help for clinicians in their tasks of detection. OBJECTIVE: The objective of this study is to provide a structured data-source of interactions involving the CYP450 enzyme system. These interactions are aimed to be integrated in the cross-lingual multi-terminology server HeTOP (Health Terminologies and Ontologies Portal), to support the query processing of the clinical data warehouse (CDW) EDSaN (Entrepôt de Données de Santé Normand). MATERIAL AND METHODS: A selection and curation of drug components (DCs) that share a relationship with the CYP450 system was performed from several international data sources. The DCs were linked according to the type of relationship which can be substrate, inhibitor, or inducer. These relationships were then integrated into the HeTOP server. To validate the CYP450 relationships, a semantic query was performed on the CDW, whose search engine is founded on HeTOP data (concepts, terms, and relations). RESULTS: A total of 776 DCs are associated by a new interaction relationship, integrated in HeTOP, by 14 enzymes. These are CYP450 1A2, 2A6, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 3A4, 3A7, 11B1,11B2 mitochondrial and P-glycoprotein, constituting a total of 2,088 relationships. A general modelling of cytochromic interactions was performed. From this model, 233,006 queries were processed in less than two hours, demonstrating the usefulness and performance of our CDW implementation. Moreover, they showed that in our university hospital, the concurrent prescription that could cause a cytochromic interaction is Bisoprolol with Amiodarone by enzymatic inhibition for 2,493 patients. DISCUSSION: The queries submitted to the CDW EDSaN allowed to highlight the most prescribed molecules simultaneously and potentially responsible for cytochromic interactions. In a second step, it would be interesting to evaluate the real clinical impact by looking for possible adverse effects of these interactions in the patients' files. Other computational solutions for cytochromic interactions exist. The impact of CYP450 is particularly important for drugs with narrow therapeutic window (NTW) as they can lead to increased toxicity or therapeutic failure. It is also important to define which drug component is a pro-drug and to considerate the many genetic polymorphisms of patients. CONCLUSION: The HeTOP server contains a non-negligible number of relationships between drug components and CYP450 from multiple reference sources. These data allow us to query our Clinical Data Warehouse to highlight these cytochromic interactions. It would be interesting in the future to assess the actual clinical impact in hospital reports.

Improving information retrieval using Medical Subject Headings Concepts: a test case on rare and chronic diseases.

BACKGROUND: As more scientific work is published, it is important to improve access to the biomedical literature. Since 2000, when Medical Subject Headings (MeSH) Concepts were introduced, the MeSH Thesaurus has been concept based. Nevertheless, information retrieval is still performed at the MeSH Descriptor or Supplementary Concept level. OBJECTIVE: The study assesses the benefit of using MeSH Concepts for indexing and information retrieval. METHODS: Three sets of queries were built for thirty-two rare diseases and twenty-two chronic diseases: (1) using PubMed Automatic Term Mapping (ATM), (2) using Catalog and Index of French-language Health Internet (CISMeF) ATM, and (3) extrapolating the MEDLINE citations that should be indexed with a MeSH Concept. RESULTS: Type 3 queries retrieve significantly fewer results than type 1 or type 2 queries (about 18,000 citations versus 200,000 for rare diseases; about 300,000 citations versus 2,000,000 for chronic diseases). CISMeF ATM also provides better precision than PubMed ATM for both disease categories. DISCUSSION: Using MeSH Concept indexing instead of ATM is theoretically possible to improve retrieval performance with the current indexing policy. However, using MeSH Concept information retrieval and indexing rules would be a fundamentally better approach. These modifications have already been implemented in the CISMeF search engine.

When Context Matters for Credible Measurement of Drug-Drug Interactions Based on Real-World Data.

The frequency of potential drug-drug interactions (DDI) in published studies on real world data considerably varies due to the methodological framework. Contextualization of DDI has a proven effect in limiting false positives. In this paper, we experimented with the application of various DDIs contexts elements to see their impact on the frequency of potential DDIs measured on the same set of prescription data collected in EDSaN, the clinical data warehouse of Rouen University Hospital. Depending on the context applied, the frequency of daily prescriptions with potential DDI ranged from 0.89% to 3.90%. Substance-level analysis accounted for 48% of false positives because it did not account for some drug-related attributes. Consideration of the patient's context could eliminate up to an additional 29% of false positives.

Assisting Data Retrieval with a Drug Knowledge Graph.

The Normandy health data warehouse EDSaN integrates the medication orders from the University Hospital of Rouen (France). This study aims at describing the design and the evaluation of an information retrieval system founded on a complex and semantically augmented knowledge graph dedicated to EDSaN drugs' prescriptions. The system is intended to help the selection of drugs in the search process by health professionals. The manual evaluation of the relevance of the returned drugs showed encouraging results as expected. A deeper analysis in order to improve the ranking method is needed and will be performed in a future work.

Qualitative Evaluation of a Drug Terminology Server.

BACKGROUND: Although the drug is finished, identifiable, there is no universally accepted standard for naming them. The objective of this work is to evaluate qualitatively the HeTOP drug terminology server by two categories of students: (a) pharmacy students and (b) a control group. METHODS: A formal evaluation was built to measure the perception of users about the HeTOP drug server, using the three mains questions about "teaching interest", "skill interest" (or competence) and "ergonomics". RESULTS: The three pharmacy student subgroups gave the best and the worst score to the same categories. CONCLUSION: All three criteria are rated above 6.5 out of 10. The HeTOP drug terminology server is freely available to "non drug" specialists (URL: www.hetop.eu/hetop/drugs/).

ABiMed: Towards an Innovative Clinical Decision Support System for Medication Reviews and Polypharmacy Management.

Polypharmacy in elderly is a public health problem with both clinical (increase of adverse drug events) and economic issues. One solution is medication review, a structured assessment of patients' drug orders by the pharmacist for optimizing the therapy. However, this task is tedious, cognitively complex and error-prone, and only a few clinical decision support systems have been proposed for supporting it. Existing systems are either rule-based systems implementing guidelines, or documentary systems presenting drug knowledge. In this paper, we present the ABiMed research project, and, through literature reviews and brainstorming, we identified five candidate innovations for a decision support system for medication review: patient data transfer from GP to pharmacists, use of semantic technologies, association of rule-based and documentary approaches, use of machine learning, and a two-way discussion between pharmacist and GP after the medication review.

Mapping the ATC classification to the UMLS metathesaurus: some pragmatic applications.

ATC classification is a WHO international classification used to classify drugs. The aim of this paper is to evaluate two lexical methods in English and in French to map ATC to UMLS. Several applications have been impemented to illustrate the use of the ATC mapping in English and French: (a) MeSH translation in Norwegian, (b) Drug Information Portal, and (c) ATC to PubMed tool. Two lexical methods were used to map ATC to UMLS. The first approach used a French natural language processing tool to map French terms of ATC to the French terminologies of UMLS. The second approach used the MetaMap tool to map English terms of ATC to UMLS. The English MetaMap provides slightly more mappings than the French NLP tool (3,170 vs. 2,992). On the other hand, the French NLP tool provides a slightly better precision than MetaMap (88% vs. 86%). Using a manual mapping between ATC and MeSH, the union of the validated mappings between ATC and MeSH provides 2,824 mappings (68.7% of ATC codes of the fifth level). Lexical methods are powerful methods to map health terminologies to the UMLS Metathesaurus. Manual mapping is still necessary to complete the mapping.

Automatic indexing in a drug information portal.

OBJECTIVE: The objective of this work is to create a bilingual (French/English) Drug Information Portal (DIP), in a multi-terminological context and to emphasize its exploitation by an ATC automatic indexing allowing having more pertinent information about substances, organs or systems on which drugs act and their therapeutic and chemical characteristics. METHODS: The development of the DIP was based on the CISMeF portal, which catalogues and indexes the most important and quality-controlled sources of institutional health information in French. DIP has created specific functionalities and uses specific drugs terminologies such as the ATC classification which used to automatic index the DIP resources. RESULTS: DIP is the result of collaboration between the CISMeF team and the VIDAL Company, specialized in drug information. DIP is conceived to facilitate the user information retrieval. The ATC automatic indexing provided relevant results in 76% of cases. CONCLUSION: Using multi-terminological context and in the framework of the drug field, indexing drugs with the appropriate codes or/and terms revealed to be very important to have the appropriate information storage and retrieval. The main challenge in the coming year is to increase the accuracy of the approach.

Projection and inheritance of SNOMED CT relations between MeSH terms.

This paper proposes a methodology to achieve the automatic inheritance of SNOMED CT relations applied to MeSH preferred terms using UMLS as knowledge source server. We propose an interoperability wildcard to achieve this objective. A quantitative and a qualitative analysis were performed on top four SNOMED CT relations inherited between MeSH preferred terms. A total of 12,030 couples of MeSH preferred terms are in relation via at least one SNOMED CT relationship. For the top-four relations inherited between MeSH preferred terms, overall 79.25% of them are relevant, 16.25% as intermediate and 4.5% as irrelevant, as judged by a medical librarian. This work should lead to an optimization of multi-terminology indexing tools, multi-terminology information retrieval and navigation among a multi-terminology server.

Drug information portal in Europe: information retrieval with multiple health terminologies.

The objective of this work is the creation of a bilingual (French/English) drug information portal (DIP), in a multi-terminological context. The development of the DIP was based on the CISMeF portal, which catalogues and indexes the most important and quality-controlled sources of institutional health information in French. DIP has created specific functionalities related to drug and used specific drugs terminologies and classifications: the ATC classification, the CAS numbers, the French codes CIS, and CIP, as well as trade names and the International Nonproprietary Names of the drugs. DIP is the result of collaboration between the CISMeF team and the VIDAL private Company, specialized in drug information. DIP is conceived to facilitate the user information retrieval using several health terminologies. In the framework of the drug field, using multi-terminological context, indexing drugs with the appropriate codes or/and terms revealed to be very important to have the appropriate information storage and retrieval.

Impact on medical practice of accessing pharmaceutical records.

INTRODUCTION: The pharmaceutical record system (PRS) is a French nationwide centralized electronic database shared among all community pharmacists listing all drugs dispensed by community pharmacists in the last four months. The objective of this study, the Medication Assessment Through Real time Information eXchange - Distributed Pharmaceutical Record System (MATRIX - DPRS) study, was to assess the clinical impact of the PRS upon granting access to physicians in three hospital specialties: anesthesiology, emergency medicine and geriatrics. MATERIAL AND METHODS: A multicenter prospective study was conducted in six hospital departments, two per specialty. Participating physicians noted medication information found exclusively in the pharmaceutical record (PR) of each patient unavailable elsewhere and any diagnostic or therapeutic management changes resulting from the PR information. The primary objective was to assess the proportion of diagnostic or therapeutic management changes attributable to the PR among patients who had an accessible PR. RESULTS: The inclusion level ranged from 1.1 to 30% in the six departments. The rate of diagnostic or therapeutic management changes was highest in geriatrics (n = 31/67; 46.3% 95% Confidence IntervaI (CI): 34.0-58.9%) and lowest in anesthesiology (n = 36/227; 15.9% 95% CI: 11.4-21.3%). Emergency medicine was intermediate (n = 5/22; 22.7% 95% CI: 7.8-45.4%). CONCLUSION: Although the inclusion rate and statistical precision were low, these findings suggest that the information contained in the PRS is useful and may result in modifying patient management in a sizeable proportion of patients. This opens the prospect of evaluating other hospital specialties, as well as primary and secondary care settings.

Searching related resources in a quality controlled health gateway: a feasibility study.

OBJECTIVE: The neighbors of a document are those documents in a corpus that are most similar to it. The objective of this paper is to develop and evaluate the related resources algorithm (CISMeF-RRA) in the context of a quality-controlled health gateway on the Internet CISMeF. METHOD: CISMeF-RRA is inspired by the PubMed Related Citations Articles. CISMeF-RRA combines statistical distances with a semantic distance using MeSH terms/qualifiers. MATERIAL: In this feasibility study an evaluation was performed using 50 CISMeF resources randomly chosen. RESULTS: Overall, 49% of the related documents were ranked as relevant. CONCLUSION: if this feasibility study is confirmed by another evaluation of more resources, CISMeF-RRA will be implemented in the CISMeF catalog.

Improving information retrieval with multiple health terminologies in a quality-controlled gateway.

BACKGROUND: The Catalog and Index of French-language Health Internet resources (CISMeF) is a quality-controlled health gateway, primarily for Web resources in French (n=89,751). Recently, we achieved a major improvement in the structure of the catalogue by setting-up multiple terminologies, based on twelve health terminologies available in French, to overcome the potential weakness of the MeSH thesaurus, which is the main and pivotal terminology we use for indexing and retrieval since 1995. The main aim of this study was to estimate the added-value of exploiting several terminologies and their semantic relationships to improve Web resource indexing and retrieval in CISMeF, in order to provide additional health resources which meet the users' expectations. METHODS: Twelve terminologies were integrated into the CISMeF information system to set up multiple-terminologies indexing and retrieval. The same sets of thirty queries were run: (i) by exploiting the hierarchical structure of the MeSH, and (ii) by exploiting the additional twelve terminologies and their semantic links. The two search modes were evaluated and compared. RESULTS: The overall coverage of the multiple-terminologies search mode was improved by comparison to the coverage of using the MeSH (16,283 vs. 14,159) (+15%). These additional findings were estimated at 56.6% relevant results, 24.7% intermediate results and 18.7% irrelevant. CONCLUSION: The multiple-terminologies approach improved information retrieval. These results suggest that integrating additional health terminologies was able to improve recall. Since performing the study, 21 other terminologies have been added which should enable us to make broader studies in multiple-terminologies information retrieval.

Translating MeSH concepts.

The concept-oriented structure of the MeSH® thesaurus is not yet in common use. Nevertheless, it has been shown that a concept-based querying of PubMed may be of interest. To take full advantage of the concept-oriented structure of MeSH in the information retrieval tool associated with the CISMeF catalogue, it was necessary to translate such concepts into French.

Assisting the translation of SNOMED CT into French.

The objective of this study is to evaluate to approaches assisting the translation of SNOMED CT into French. Two types of approaches were combined: a concept-based one, which relies on conceptual information of the UMLS Metathesaurus and a lexical-based one, which relieson NLP techniques. In addition to the French terminologies (whether included in UMLS or not). Using the concept-based approach, a set of 156,157 (39.4%) SNOMED CT terms were translated to at least one French term from UMLS. Expanded to the French terms from UMLS terminologies translated by CISMeF, 2,548 (+0.7%) additional SNOMED CT terms were translated to at least one French term. Using the lexical-based approach, a set of 145,737 (36.8%) SNOMED CT terms were translated to at least one French term from HeTOP. The qualitative evaluation showed that 44% of the translations were rated as "relevant". Overall, the two approaches have provided the translation of 168,750 (42.6%) SNOMED CT terms into French using different bilingual terminological sources included in UMLS or in HeTOP.

Integrating the human phenotype ontology into HeTOP terminology-ontology server.

The Human Phenotype Ontology (HPO) is a controlled vocabulary which provides phenotype data related to genes or diseases. The Health Terminology/Ontology Portal (HeTOP) is a tool dedicated to both human beings and computers to access and browse biomedical terminologies or ontologies (T/O). The objective of this work was to integrate the HPO into HeTOP in order to enhance both works. This integration is a success and allows users to search and browse the HPO with a dedicated interface. Furthermore, the HPO has been enhanced with the addition of content such as new synonyms, translations, mappings. Integrating T/O such as the HPO into HeTOP is a benefit to vocabularies because it allows enrichment of them and it is also a benefit for HeTOP which provides a better service to both humans and machines.