Accuracy of using natural language processing methods for identifying healthcare-associated infections

International audienceThere is a growing interest in using natural language processing (NLP) for healthcare-associated infections (HAIs) monitoring. A French project consortium, SYNODOS, developed a NLP solution for detecting medical events in electronic medical records for epidemiological purposes. The objective of this study was to evaluate the performance of the SYNODOS data processing chain for detecting HAIs in clinical documents

Accuracy of using natural language processing methods for identifying healthcare-associated infections

International audienceThere is a growing interest in using natural language processing (NLP) for healthcare-associated infections (HAIs) monitoring. A French project consortium, SYNODOS, developed a NLP solution for detecting medical events in electronic medical records for epidemiological purposes. The objective of this study was to evaluate the performance of the SYNODOS data processing chain for detecting HAIs in clinical documents

Accuracy of using natural language processing methods for identifying healthcare-associated infections

International audienceThere is a growing interest in using natural language processing (NLP) for healthcare-associated infections (HAIs) monitoring. A French project consortium, SYNODOS, developed a NLP solution for detecting medical events in electronic medical records for epidemiological purposes. The objective of this study was to evaluate the performance of the SYNODOS data processing chain for detecting HAIs in clinical documents

Breast cancer risk in relation to ambient concentrations of nitrogen dioxide and particulate matter: results of a population-based case-control study corrected for potential selection bias (the CECILE study)

Background: There is only scant evidence that air pollution increases the risk of breast cancer. Objectives: We investigated this relationship for three air pollutants: nitrogen dioxide (NO2) and particulate matter with an aerodynamical diameter below 10 µm (PM10) and 2.5 µm (PM2.5). Methods: We conducted a population-based case-control study on breast cancer in two French départements, including 1,229 women diagnosed with breast cancer in 2005–2007 and 1,316 control women frequency-matched on age. Concentrations of NO2, PM10 and PM2.5 at participants’ addresses occupied during the last 10 years were assessed using a chemistry transport model. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using multivariable logistic regression models where each woman was assigned a weight depending on her probability of selection into the study. Results: The OR for breast cancer per 10-µg/m3 increase in NO2 was 1.11 (95% CI, 0.98, 1.26), and 1.41 (95% CI 1.07, 1.86) in the highest exposure quintile (Q5), compared to the first. The ORs per 10-µg/m3 NO2 did not markedly differ between pre- (OR 1.09, 95% CI 0.89, 1.35)) and post-menopausal women (OR 1.14, 95% CI 0.97, 1.33)), but the OR was substantially higher for hormone-receptor positive (ER+/PR+) breast tumor subtypes (OR 1.15, 95% CI 1.00, 1.31) than for ER–/PR– tumors (OR 0.95, 95% CI 0.72, 1.26). Breast cancer risk was not associated with either PM10 (OR per 1 µg/m3 1.01, 95% CI, 0.96, 1.06) or PM2.5 (OR per 1 µg/m3 1.02, 95% CI 0.95, 1.08), regardless of the menopausal status or of the breast tumor subtype. Discussion: Our study provides evidence that NO2 exposure, a marker of traffic-related air pollutants, may be associated with an increased risk of breast cancer, particularly ER+/PR+ tumors

Création d'une matrice emplois-expositions sur le travail à horaires atypiques

35e congrès national de médecine et santé au travail, MARSEILLE, FRANCE, 05-/06/2018 - 08/06/2018Depuis plusieurs années, le travail à horaires atypiques, et le travail de nuit en particulier, suscite de fortes inquiétudes liées à ses effets avérés ou supposés sur la santé. En 2007, le Centre international de recherche sur le cancer (CIRC) classait le travail posté comme probablement cancérogène pour l'homme (2A) par son rôle de perturbateur du rythme circadien. Dans ce contexte, nous avons souhaité développer un outil permettant une évaluation exhaustive et rétrospective des emplois à horaires atypiques en distinguant les différents types d'horaires ainsi que son évolution au cours du temps. La construction de la matrice est basée sur les données des Enquêtes emploi (EE) de l'Institut national des statistiques et des études économiques (INSEE). Ces enquêtes transversales répétées au cours du temps, contiennent des informations sur l'emploi et les conditions de travail recueillies au niveau individuel sur un échantillon représentatif de la population française en métropole et dans les DOM. La matrice, basée sur les professions et les branches d'activités, est construite à partir d'une méthode de segmentation des données, dite méthode d'inférence conditionnelle. Les contraintes organisationnelles évaluées dans la matrice sont l'existence d'un travail du soir entre 20heures et minuit (régulier, occasionnel, jamais), d'un travail de nuit entre minuit et 5heures (régulier, occasionnel, jamais), ou d'un travail à alternance régulière ou irrégulière. Cette matrice indique la probabilité de travailler de soir, de nuit ou d'avoir un travail posté en fonction de la profession, du secteur d'activité en France et de l'année de l'emploi. Elle permettra l'évaluation et la mesure de la perturbation du rythme circadien en milieu de travail ainsi que l'étude des liens entre le travail à horaires décalés et la santé

Annotation methods to develop and evaluate an expert system based on natural language processing in electronic medical records

International audienceThe objective of the SYNODOS collaborative project was to develop a generic IT solution, combining a medical terminology server, a semantic analyser and a knowledge base. The goal of the project was to generate meaningful epidemiological data for various medical domains from the textual content of French medical records. In the context of this project, we built a care pathway oriented conceptual model and corresponding annotation method to develop and evaluate an expert system's knowledge base. The annotation method is based on a semi-automatic process, using a software application (MedIndex). This application exchanges with a cross-lingual multi-termino-ontology portal. The annotator selects the most appropriate medical code proposed for the medical concept in question by the multi-termino-ontology portal and temporally labels the medical concept according to the course of the medical event. This choice of conceptual model and annotation method aims to create a generic database of facts for the secondary use of electronic health records data

Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study

International audienc

Annotation methods to develop and evaluate an expert system based on natural language processing in electronic medical records

International audienceThe objective of the SYNODOS collaborative project was to develop a generic IT solution, combining a medical terminology server, a semantic analyser and a knowledge base. The goal of the project was to generate meaningful epidemiological data for various medical domains from the textual content of French medical records. In the context of this project, we built a care pathway oriented conceptual model and corresponding annotation method to develop and evaluate an expert system's knowledge base. The annotation method is based on a semi-automatic process, using a software application (MedIndex). This application exchanges with a cross-lingual multi-termino-ontology portal. The annotator selects the most appropriate medical code proposed for the medical concept in question by the multi-termino-ontology portal and temporally labels the medical concept according to the course of the medical event. This choice of conceptual model and annotation method aims to create a generic database of facts for the secondary use of electronic health records data

Annotation methods to develop and evaluate an expert system based on natural language processing in electronic medical records

International audienceThe objective of the SYNODOS collaborative project was to develop a generic IT solution, combining a medical terminology server, a semantic analyser and a knowledge base. The goal of the project was to generate meaningful epidemiological data for various medical domains from the textual content of French medical records. In the context of this project, we built a care pathway oriented conceptual model and corresponding annotation method to develop and evaluate an expert system's knowledge base. The annotation method is based on a semi-automatic process, using a software application (MedIndex). This application exchanges with a cross-lingual multi-termino-ontology portal. The annotator selects the most appropriate medical code proposed for the medical concept in question by the multi-termino-ontology portal and temporally labels the medical concept according to the course of the medical event. This choice of conceptual model and annotation method aims to create a generic database of facts for the secondary use of electronic health records data

Outsciencing the scientists : a cross-sectional mixed-methods investigation of public trust in scientists in seven European countries

Abstract: Background In this era of global health crises, public trust in scientists is a crucial determinant of adherence to public health recommendations. Studies of trust in scientists often link sociodemographic and other factors to such adherence but rely on assumptions about scientists and neglect scientific uncertainty. We undertook a cross-sectional mixed-methods study evaluating factors associated with public trust of scientists in Europe, investigating how and why respondents embraced certain claims in scientific debates. Methods A survey was administered to 7000 participants across seven European countries in December 2020. Data concerning sociodemographic characteristics, trust in scientists, information source preferences, COVID-19 experiences and beliefs about pandemic origins were analysed using a multiple regression model. We employed thematic analysis to interpret open-text responses about pandemic origins and likely acceptance of treatments and vaccination. Results Trust in scientists was associated with multiple sociodemographic characteristics, including higher age and educational levels, left/centre political affiliation and use of certain information sources. Respondents claiming that COVID-19 was deliberately released and that 5G technology worsened COVID-19 symptoms had lower levels of trust in scientists. Explaining their positions in debates about pandemic origins, respondents trusting and not trusting scientists invoked scientific results and practices, arguing that scientists were not the most important actors in these debates. Conclusions Although our quantitative analyses align with prior studies, our qualitative analyses of scientists, their practices and perceived roles are more varied than prior research presumed. Further investigation of these variations is needed to strengthen scientific literacy and trust in scientists