Evaluation of natural language processing from emergency department computerized medical records for intra-hospital syndromic surveillance

<p>Abstract</p> <p>Background</p> <p>The identification of patients who pose an epidemic hazard when they are admitted to a health facility plays a role in preventing the risk of hospital acquired infection. An automated clinical decision support system to detect suspected cases, based on the principle of syndromic surveillance, is being developed at the University of Lyon's Hôpital de la Croix-Rousse. This tool will analyse structured data and narrative reports from computerized emergency department (ED) medical records. The first step consists of developing an application (UrgIndex) which automatically extracts and encodes information found in narrative reports. The purpose of the present article is to describe and evaluate this natural language processing system.</p> <p>Methods</p> <p>Narrative reports have to be pre-processed before utilizing the French-language medical multi-terminology indexer (ECMT) for standardized encoding. UrgIndex identifies and excludes syntagmas containing a negation and replaces non-standard terms (abbreviations, acronyms, spelling errors...). Then, the phrases are sent to the ECMT through an Internet connection. The indexer's reply, based on Extensible Markup Language, returns codes and literals corresponding to the concepts found in phrases. UrgIndex filters codes corresponding to suspected infections. Recall is defined as the number of relevant processed medical concepts divided by the number of concepts evaluated (coded manually by the medical epidemiologist). Precision is defined as the number of relevant processed concepts divided by the number of concepts proposed by UrgIndex. Recall and precision were assessed for respiratory and cutaneous syndromes.</p> <p>Results</p> <p>Evaluation of 1,674 processed medical concepts contained in 100 ED medical records (50 for respiratory syndromes and 50 for cutaneous syndromes) showed an overall recall of 85.8% (95% CI: 84.1-87.3). Recall varied from 84.5% for respiratory syndromes to 87.0% for cutaneous syndromes. The most frequent cause of lack of processing was non-recognition of the term by UrgIndex (9.7%). Overall precision was 79.1% (95% CI: 77.3-80.8). It varied from 81.4% for respiratory syndromes to 77.0% for cutaneous syndromes.</p> <p>Conclusions</p> <p>This study demonstrates the feasibility of and interest in developing an automated method for extracting and encoding medical concepts from ED narrative reports, the first step required for the detection of potentially infectious patients at epidemic risk.</p

Stabilization mechanisms of CH4 premixed swirled flame enriched with a non-premixed hydrogen injection

High-fidelity Large Eddy Simulations (LES) are performed to study the effect of hydrogen injection on a lean turbulent CH4 /Air premixed flame. An Analytically Reduced Chemistry (ARC) mechanism is used to achieve a detailed description of CH4/Air-H2 chemistry. First, a validation of this kinetic scheme against the detailed GRI-Mech 3.0 mechanism is presented considering both simplified and complex transport properties. When hydrogen is added to the mixture, large variations of the mixture Prandtl and of the N2 Schmidt numbers are observed depending on the local species concentrations, features that are missed by simplified models. LES is then applied to study the structure and stabilization mechanisms of a lean (φ = 0.8) premixed CH4/Air swirled flame enriched with hydrogen by using different transport modeling strategies. First, the fully pre- mixed CH4/Air case is considered and results are found to validate the LES approach. In agreement with experiments, a classical V-shape flame is stabilized in the low-velocity region near the flame holder created by a central recirculation zone (CRZ). Then, hydrogen enrichment is achieved injecting 2% of the CH4 thermal power with a central fuel injection lance. Both premixed and diffusion flame branches are present in this case, impacting flame stabilization and flame angle. The flame root of the main premixed flame is stabilized by a diffusion flame kernel created by the injected hydrogen reacting with the oxygen in excess of the premixed stream. Moreover, the H2 consumed with the remaining oxygen in burnt gases leads to the formation of a second flame branch inside the CRZ which is responsible of an increase of the flame angle. Given the high concentration of hydrogen, an impact of the molecular transport models is observed on the flame lift-off height highlighting the importance of using complex transport properties in any LES involving hydrogen combustion

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

International audienc

DOLPHIN: A Framework for the Design and Perceptual Evaluation of Ultrasound Mid-Air Haptic Stimuli

International audienceUltrasound mid-air haptic interfaces can display highly reconfigurable vibrotactile shapes in mid-air for human-computer interaction (HCI) applications. The choice of stimulus shape, spatial, temporal and modulation parameters yields a complex design space, yet relatively little is known about the impact of these design choices on perceived stimulus properties. We define the combination of a spatial discretization of an abstract shape and a set of rules for the temporal display order and intensity modulation of the resulting points as a sampling strategy. We developed DOLPHIN, an open-source framework to aid in designing mid-air stimuli. DOLPHIN allows the study of the impact of rendering parameters on perceived stimulus properties. This platform-agnostic framework standardizes stimulus descriptions as a step toward more replicability and easier communication in the field. It enables reproduction of stimuli between perceptual experiments and ensures stimuli used in applications correspond to those evaluated in prior perceptual studies. We validated DOLPHIN's usability by conducting a user study assessing the impact of sampling strategy design on curvature discrimination for dynamic mid-air haptic stimuli. The Weber fractions for just-noticeable differences (JNDs) in curvature were found to range between 1 and 1.4, yet no significant effect of the number of spatial sampling points on curvature discrimination was found. This result shows a practical use-case for DOLPHIN and provides insight into rendering mid-air haptic curvature

Réunions pluridisciplinaires déterminant l’imputabilité des xénobiotiques dans les causes de la mort : quel apport aux données de pharmacovigilance ? [Multidisciplinary meetings determining the imputability of xenobiotics in causes of death: What contribution to pharmacovigilance data?]

National audienc

Use of troponin assay after electrical injuries: a 15-year multicentre retrospective cohort in emergency departments

International audienceBACKGROUND: Patients with electrical injury are considered to be at risk of cardiac arrhythmia. Assessing the risk of developing a major adverse cardiac event (MACE) is the cornerstone of patient management. The aim of this study was to assess the performance of initial troponin and troponin rise to predict Major Adverse Cardiac Events (MACEs) in all patients with electrical injuries admitted to the Emergency Department. METHODS: This is a multicentre retrospective study in which consecutive patients with electrical injuries admitted to the Emergency Departments (ED) (adult and paediatric) of five French Hospitals were included between 2005 and 2019. The threshold for troponin elevation is based on the European Society of Cardiology guidelines for patients presenting without persistent ST segment elevation. The primary endpoint was the rate of MACE. RESULTS: A total of 785 included patients were admitted to ED with a first diagnosis of electrical injury during the study period. Troponin assays were performed in 533 patients (67.9%), including 465 of 663 adults (70.1%) and 68 of 122 children (55.7%) and 17/533 (3.2%) of patients had an initial elevated troponin. If none of the clinical criteria for MACE were present (i.e., previous known heart disease, exposure to a high voltage of ≥ 1000 Volts, initial loss of consciousness, or an abnormal initial ECG), this defined a low-risk subgroup (n = 573, 76.0%) that could be safely discharged. The initial positive troponin assay had a sensitivity of 83.3 (95% CI 35.9-99.6%), a specificity of 97.7 (95% CI 96.1-98.8%), a positive likelihood ratio 36.6 (95% CI 18.8-71.1%) and a negative predictive value of 99.9 (95% CI 99.2-99.9%) in predicting a MACE. CONCLUSIONS: Troponin assay appears to be a predictive marker of MACE risk and should be considered in high-risk patients

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

Development of an Automated Detection Tool for Health Care-Associated Infections Based on Screening Natural Language Medical Reports

Poster at AMIA Sym

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