The Prescription of Drug Ontology 2.0 (PDRO): More Than the Sum of Its Parts.

While drugs and related products have profoundly changed the lives of people around the world, ongoing challenges remain, including inappropriate use of a drug product. Inappropriate uses can be explained in part by ambiguous or incomplete information, for example, missing reasons for treatments, ambiguous information on how to take a medication, or lack of information on medication-related events outside the health care system. In order to fully assess the situation, data from multiple systems (electronic medical records, pharmacy and radiology information systems, laboratory management systems, etc.) from multiple organizations (outpatient clinics, hospitals, long-term care facilities, laboratories, pharmacies, registries, governments) on a large geographical scale is needed. Formal knowledge models like ontologies can help address such an information integration challenge. Existing approaches like the Observational Medical Outcomes Partnership are discussed and contrasted with the use of ontologies and systems using them for data integration. The PRescription Drug Ontology 2.0 (PDRO 2.0) is then presented and entities that are paramount in addressing this problematic are described. Finally, the benefits of using PDRO are discussed through a series of exemplar situation.

Correction: Modulation of the mechanical energy storage performance of the MIL-47(VIV) metal organic framework by ligand functionalization.

Correction for 'Modulation of the mechanical energy storage performance of the MIL-47(VIV) metal organic framework by ligand functionalization' by Pascal G. Yot et al., Dalton Trans., 2019, DOI: 10.1039/c8dt04214d.

Modulation of the mechanical energy storage performance of the MIL-47(VIV) metal organic framework by ligand functionalization.

The functionalization of the metal-organic framework MIL-47(VIV) with ligands bearing bulky functional groups (-Br or -CF3) has been envisaged as a possible route to enhance the mechanical energy storage performances of this family of hybrid porous materials. This exploratory work was carried out by coupling advanced experimental techniques (mercury intrusion and X-ray powder diffraction) supported by density functional theory calculations. MIL-47(VIV)-BDC-CF3 was demonstrated to be one of the most promising porous materials for mechanical energy-related applications with performance in terms of work energy which surpasses that of any porous solids reported so far.

Mechanical energy storage performance of an aluminum fumarate metal-organic framework.

The aluminum fumarate MOF A520 or MIL-53-FA is revealed to be a promising material for mechanical energy-related applications with performances in terms of work and heat energies which surpass those of any porous solids reported so far. Complementary experimental and computational tools are deployed to finely characterize and understand the pressure-induced structural transition at the origin of these unprecedented levels of performance.

Design of hydrophilic metal organic framework water adsorbents for heat reallocation.

A new hydrothermally stable Al polycarboxylate metal-organic framework (MOF) based on a heteroatom bio-derived aromatic spacer is designed through a template-free green synthesis process. It appears that in some test conditions this MOF outperforms the heat reallocation performances of commercial SAPO-34.

The structure of the aluminum fumarate metal-organic framework A520.

The synthesis of the commercially available aluminum fumarate sample A520 has been optimized and its structure analyzed through a combination of powder diffraction, solid-state NMR spectroscopy, molecular simulation, IR spectroscopy, and thermal analysis. A520 is an analogue of the MIL-53(Al)-BDC solid, but with a more rigid behavior. The differences between the commercial and the optimized samples in terms of defects have been investigated by in situ IR spectroscopy and correlated to their catalytic activity for ethanol dehydration.

Determinants of A (H1N1) vaccination: cross-sectional study in a population of pregnant women in Quebec.

BACKGROUND: Because of the risk of complication, pregnant women were a priority target for vaccination during the A (H1N1) pandemic influenza. In Quebec, 63% of pregnant women were vaccinated, which is a higher rate than vaccination against seasonal influenza. However, the behaviour of pregnant women relative to the vaccination during the H1N1 pandemic is unknown. The present study was aimed at identifying factors influencing the decision-making of pregnant women regarding H1N1 vaccination. METHODS: A cross-sectional survey was conducted in February 2010 in pregnant women or in early postpartum at the Sherbrooke University Hospital Centre using a self-administered questionnaire based on the Health Belief Model (HBM). Data items collected were: socio-demographic data, vaccination status, information sources consulted, knowledge on vaccination, and the HBM dimensions: effectiveness and risks of vaccination, severity and vulnerability towards the influenza. The associations between questionnaire variables and vaccination status were assessed by univariate and multivariate analysis. RESULTS: Of the 250 women interviewed, 95% knew that the vaccination was recommended, but only 76% received the vaccine. Variables positively associated with vaccination were late vaccination during pregnancy (OR=7.3, 95% CI 2.1-25.3), belief in the efficacy of the vaccine (OR=7, 95% CI 2-23.4), and consultation of the Pandémie-Québec website (OR=4.5, 95% CI 1.5-13.4). However, the belief that the vaccine had not been adequately tested (OR=0.08, 95% CI 0.02-0.35) and consultation of mainstream websites (OR=0.22, 95% CI 0.06-0.81) were associated with lower vaccination rates. CONCLUSIONS: The vast majority of pregnant women were aware of the recommendations relative to A (H1N1) vaccination. Internet media played an important role in their decision to get vaccinated. Better information on the safety of the vaccine must be prepared for future pandemics.

Using argumentation to extract key sentences from biomedical abstracts.

PROBLEM: key word assignment has been largely used in MEDLINE to provide an indicative "gist" of the content of articles and to help retrieving biomedical articles. Abstracts are also used for this purpose. However with usually more than 300 words, MEDLINE abstracts can still be regarded as long documents; therefore we design a system to select a unique key sentence. This key sentence must be indicative of the article's content and we assume that abstract's conclusions are good candidates. We design and assess the performance of an automatic key sentence selector, which classifies sentences into four argumentative moves: PURPOSE, METHODS, RESULTS and METHODS: we rely on Bayesian classifiers trained on automatically acquired data. Features representation, selection and weighting are reported and classification effectiveness is evaluated on the four classes using confusion matrices. We also explore the use of simple heuristics to take the position of sentences into account. Recall, precision and F-scores are computed for the CONCLUSION class. For the CONCLUSION class, the F-score reaches 84%. Automatic argumentative classification using Bayesian learners is feasible on MEDLINE abstracts and should help user navigation in such repositories.

Amplification of Terminologia anatomica by French language terms using Latin terms matching algorithm: a prototype for other language.

OBJECTIVE: Terminologia anatomica is the new standard in anatomical terminology. This terminology is available only in Latin and English and its worldwide adoption is subject to the addition of terms from others languages. On the other hand, Nomina anatomica, the previous standard, has been widely translated. Aim of this work was to append foreign terms to Terminologia by using similarity-matching algorithm between its Latin terms and those from Nomina. METHODS: A semi-automatic matching of Latin terms from Terminologia with those of Nomina was performed using a string-to-string distance algorithm and manual assessment. We used a French-Latin version of Nomina together with Terminologia and we suggested French terms for Terminologia. Coverage was evaluated by the number of exact and approximate matches. A target of 78% was set due to the higher number of terms in Terminologia compared to Nomina. Relevance was estimated by manually comparing the meanings of the English and French terms related to the same Latin term. The question was whether they refer to the same anatomical structure. RESULTS: Exact or approximate matches were found for 5982 terms (76.5%) of Terminologia. Our results indicated that more than 75% of the terms from Terminologia came from Nomina, most of them were left unchanged and all were used with the same meaning. CONCLUSION: This method produces relevant results, reaching our 78% target. The method is based only on Latin terms and can be used for other languages. We consider this work as a starting point for adding terms to other knowledge sources, such as the foundational model of anatomy or the Unified Medical Language System (UMLS).

Methodology to ease the construction of a terminology of problems.

INTRODUCTION: Problem lists summarize an aspect of the patient's medical history and provide an important way to implement entry points for clinical pathways and guideline-oriented care. However, in order to automate processes based on problem lists, the use of controlled vocabularies is required. We developed a methodology to extract a collection of standardized problem-related terms from medical documents entered in free text by physicians. METHODS: We extracted a corpus of sentences describing problems from a randomized selection of admission notes collected at the University Hospitals of Geneva. Theses sentences underwent manual and automatic normalization processes, and a statistical clustering, in order to build a set of terms. RESULTS: We obtained 17,805 sentences from 5000 admission notes. We refined them into 1546 terms, 88.6% of which could be related to a relevant problem statement. DISCUSSION: A clinically relevant problems terminology was derived from clinical admission notes in free-text using a few methodical steps with a reasonable investment of human resources. Such an approach will ease the development and the use of problem lists better suited to user needs.

Desiderata for representing anatomical knowledge.

The general problem of knowledge representation for gross anatomy supporting both computers and human is rarely globally solved. Partial solutions are flourishing, but the actual and potential users are left with a lack of satisfaction and uncomfortable feeling of incompleteness. Moreover, these solutions are not ready for a sound evolution and are at risk to disappear at any moment by default of adequate maintenance. In addition, the problem is complicated by the fact that any solutions should be relevant for Natural Language Processing applications in a multilingual environment.This paper tackles with this problem and defines the basic steps for a proper knowledge representation scheme. Taking the subdomain of gross anatomy, it shows how each step has been solved and what performances and benefits are expected by such a solution. A discussion is done on the way to interface from a common source for both computers and humans.

Towards a multilingual version of terminologia anatomica.

OBJECTIVE: Terminologia Anatomica (TA) is the new standard in anatomical terminology. This terminology is available only in Latin and English and its worldwide adoption is subdued to the addition of terms from others languages. On the other hand Nomina Anatomica (NA), the previous standard, has been widely translated. Aim of this work was to append foreign terms to TA by using similarity matching algorithm between its Latin terms and those from NA. METHODS: A semi-automatic matching of Latin terms from TA with those of NA was performed using a string-to-string distance algorithm and manual assessment. We used a French - Latin version of NA together with TA and we suggested French terms for TA. Coverage was evaluated by the number of exact and approximate matches. A target of 80% was set due to the superior number of terms in TA compared to NA. Relevance was estimated by manually comparing the meanings of the English and French terms related to the same Latin term. The question was whether they refer to the same anatomical structure. RESULTS: Exact or approximate matches were found for 5,982 terms (76.5%) of TA. Our results outlined that more than 75% of the terms from TA came from NA, most of them were left unchanged and all were used with the same meaning. CONCLUSION: This method produces relevant results, reaching our 80% target. The method is based only on Latin terms and can be used for other languages and for others terminologies including Latin terms.

Coping with the variability of medical terms.

OBJECTIVES: To cope with medical terms, which present a high variability of expression through a single natural language, in the sense that any term may be reformulated in hundred of different ways. METHODS: A typology of term variants is presented as a systematic approach in order to favour the implementation of an exhaustive solution. Then, an algorithm able to handle all variants is designed. RESULTS: Using MetaMap, single terms are analyzed with a success rate varying between 68 and 88 %; the algorithm presented in this paper improves this situation. CONCLUSIONS: This experience shows that a semantic driven method, based on a thesaurus, provides a satisfactory solution to the problem of variability of a single term. The presented typology is representative of most variants in a language.

User acceptance of clinical information systems: a methodological approach to identify the key dimensions allowing a reliable evaluation framework.

The introduction of Computerized Information Systems (CIS) in clinical settings encountered difficulties. These difficulties highlight the lack of understanding of factors and mechanisms influencing user acceptance. The existing tools and research obtained contradictory results that point out the existence of neglected aspects, such as impacts of CIS, in computer science developments in complex settings. This paper proposes to identify key dimensions which make up user acceptance in clinical settings through the union of three methods. They define five main dimensions which require a concrete evaluation to validate the underlying proposed framework and to complete the description of the acceptance phenomenon. Identifying key dimensions opens the gate to comparative evaluation of many CIS and adds new indicators to evaluate the highlighted dimensions. A long-term aim is the development of longitudinal studies and to state priorities and guidelines for new CIS designs.

A frame-based representation of ICD-10.

UNLABELLED: Physicians are required to code information concerning a patient's stay in order to measure the medical activity in hospitals. They use the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Coding is usually performed manually and computerized tools may be useful in speeding up and facilitating the tedious task of coding patient information. The aim of this work is to build a surface semantic model of ICD-10 in order to ameliorate a coding help system. METHODS: This work was focused on chapter XI of the ICD-10, Diseases of the Digestive System. Each term from both analytical and alphabetical indexes about this chapter were submitted to a morphological analysis in order to extract the medical concepts within. After a statistical analysis of these concepts and the way they connect themselves, a semantic model based on a "semantic frame" approach was built. RESULTS: Although this model could represent a reasonable amount of medical knowledge within chapter XI of the ICD-10 in a quite satisfactory way, it shows lack of efficiency for some other chapters. CONCLUSION: Difficulties have to be overcome when modelling a classification meant for manual utilisation, and a lot of work still has to be done to obtain an effective coding help system using the ICD-10.

Clinical documents: attribute-values entity representation,context, page layout and communication.

This paper presents how acquisition, storage and communication of clinical documents is implemented at the University Hospitals of Geneva. Careful attention has been given to user-interfaces, in order to support complex layouts, spell checking, and templates management with automatic prefilling. A dual architecture has been developed for storage using an entity-attribute-value unified database and a consolidated, patient-centered, layout-respectful file-based storage, providing both representation power and speed of access. This architecture allows a great flexibility for storing a continuum of data types, ranging from simple typed values to complex clinical reports. Finally, communication is entirely based on HTTP-XML internally, and a HL-7 CDA interface V2 is currently studied for external communication. Some of the problems encountered, mostly related to the typology of documents and the ontology of clinical attributes are evoked.