Titre : Relations interprofessionnelles

Relations interprofessionnelles : Questions médicales fréquentes

Termes MeSH sélectionnés :

Natural Language Processing
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améliorer les traitements par la collaboration ?\nQuels traitements favorisent la communication ?\nComment évaluer l'efficacité des traitements interprofessionnels ?\nQuels traitements sont adaptés aux équipes interprofessionnelles ?\nComment les traitements peuvent-ils être personnalisés ?", "url": "https://questionsmedicales.fr/mesh/D007400?mesh_terms=Natural+Language+Processing&page=3#section-traitements" }, { "@type": "MedicalWebPage", "name": "Complications", "headline": "Complications sur Relations interprofessionnelles", "description": "Quelles complications résultent d'une mauvaise communication ?\nComment les conflits affectent-ils les résultats des soins ?\nQuelles complications peuvent survenir en cas de mauvaise collaboration ?\nComment évaluer l'impact des complications sur les soins ?\nQuelles sont les conséquences d'une mauvaise dynamique d'équipe ?", "url": "https://questionsmedicales.fr/mesh/D007400?mesh_terms=Natural+Language+Processing&page=3#section-complications" }, { "@type": "MedicalWebPage", "name": "Facteurs de risque", "headline": "Facteurs de risque sur Relations interprofessionnelles", "description": "Quels facteurs augmentent le risque de conflits ?\nComment le stress influence-t-il les relations interprofessionnelles ?\nQuels facteurs de risque sont liés à la collaboration ?\nComment les différences de statut affectent-elles les relations ?\nQuels facteurs environnementaux influencent la collaboration ?", "url": "https://questionsmedicales.fr/mesh/D007400?mesh_terms=Natural+Language+Processing&page=3#section-facteurs de risque" } ] }, { "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "Comment évaluer la communication interprofessionnelle ?", "position": 1, "acceptedAnswer": { "@type": "Answer", "text": "Utiliser des outils d'évaluation comme des questionnaires et des entretiens." } }, { "@type": "Question", "name": "Quels indicateurs mesurent la collaboration interprofessionnelle ?", "position": 2, "acceptedAnswer": { "@type": "Answer", "text": "Les indicateurs incluent la satisfaction des patients et l'efficacité des soins." } }, { "@type": "Question", "name": "Quels outils facilitent le diagnostic interprofessionnel ?", "position": 3, "acceptedAnswer": { "@type": "Answer", "text": "Les outils incluent des plateformes de partage d'informations et des réunions d'équipe." } }, { "@type": "Question", "name": "Comment identifier les barrières à la collaboration ?", "position": 4, "acceptedAnswer": { "@type": "Answer", "text": "Par des enquêtes et des discussions en groupe pour recueillir des retours d'expérience." } }, { "@type": "Question", "name": "Quel rôle joue la culture organisationnelle dans le diagnostic ?", "position": 5, "acceptedAnswer": { "@type": "Answer", "text": "Une culture ouverte favorise la communication et la collaboration entre les professionnels." } }, { "@type": "Question", "name": "Quels symptômes indiquent une mauvaise communication ?", "position": 6, "acceptedAnswer": { "@type": "Answer", "text": "Des erreurs médicales fréquentes et des plaintes des patients peuvent en être des signes." } }, { "@type": "Question", "name": "Comment reconnaître un manque de collaboration ?", "position": 7, "acceptedAnswer": { "@type": "Answer", "text": "Des conflits fréquents et un manque de coordination dans les soins sont des indicateurs." } }, { "@type": "Question", "name": "Quels symptômes affectent la dynamique d'équipe ?", "position": 8, "acceptedAnswer": { "@type": "Answer", "text": "Le stress, la frustration et le turnover élevé peuvent affecter la dynamique d'équipe." } }, { "@type": "Question", "name": "Quels signes montrent une bonne collaboration ?", "position": 9, "acceptedAnswer": { "@type": "Answer", "text": "Une communication fluide et des résultats positifs pour les patients sont des signes clés." } }, { "@type": "Question", "name": "Comment les symptômes de stress impactent-ils les relations ?", "position": 10, "acceptedAnswer": { "@type": "Answer", "text": "Le stress peut mener à des conflits et à une communication inefficace entre les professionnels." } }, { "@type": "Question", "name": "Comment prévenir les conflits interprofessionnels ?", "position": 11, "acceptedAnswer": { "@type": "Answer", "text": "Par des formations régulières sur la communication et la gestion des conflits." } }, { "@type": "Question", "name": "Quelles stratégies améliorent la prévention des erreurs ?", "position": 12, "acceptedAnswer": { "@type": "Answer", "text": "Mettre en place des protocoles clairs et des revues de cas régulières." } }, { "@type": "Question", "name": "Comment sensibiliser à l'importance de la collaboration ?", "position": 13, "acceptedAnswer": { "@type": "Answer", "text": "Organiser des séminaires et des ateliers sur les bénéfices de la collaboration interprofessionnelle." } }, { "@type": "Question", "name": "Quels outils aident à la prévention des erreurs médicales ?", "position": 14, "acceptedAnswer": { "@type": "Answer", "text": "Les check-lists et les systèmes de double vérification sont des outils efficaces." } }, { "@type": "Question", "name": "Comment la prévention impacte-t-elle les soins ?", "position": 15, "acceptedAnswer": { "@type": "Answer", "text": "Une bonne prévention réduit les erreurs et améliore la satisfaction des patients." } }, { "@type": "Question", "name": "Comment améliorer les traitements par la collaboration ?", "position": 16, "acceptedAnswer": { "@type": "Answer", "text": "En intégrant des équipes multidisciplinaires pour une approche globale des soins." } }, { "@type": "Question", "name": "Quels traitements favorisent la communication ?", "position": 17, "acceptedAnswer": { "@type": "Answer", "text": "Des formations en communication et des ateliers de team-building sont bénéfiques." } }, { "@type": "Question", "name": "Comment évaluer l'efficacité des traitements interprofessionnels ?", "position": 18, "acceptedAnswer": { "@type": "Answer", "text": "Par des études de cas et des analyses de résultats cliniques post-traitement." } }, { "@type": "Question", "name": "Quels traitements sont adaptés aux équipes interprofessionnelles ?", "position": 19, "acceptedAnswer": { "@type": "Answer", "text": "Les traitements complexes comme la gestion de la douleur nécessitent une approche collaborative." } }, { "@type": "Question", "name": "Comment les traitements peuvent-ils être personnalisés ?", "position": 20, "acceptedAnswer": { "@type": "Answer", "text": "En tenant compte des compétences et des expertises de chaque professionnel de santé." } }, { "@type": "Question", "name": "Quelles complications résultent d'une mauvaise communication ?", "position": 21, "acceptedAnswer": { "@type": "Answer", "text": "Des erreurs de traitement et des retards dans les soins peuvent survenir." } }, { "@type": "Question", "name": "Comment les conflits affectent-ils les résultats des soins ?", "position": 22, "acceptedAnswer": { "@type": "Answer", "text": "Les conflits peuvent mener à des soins fragmentés et à une insatisfaction des patients." } }, { "@type": "Question", "name": "Quelles complications peuvent survenir en cas de mauvaise collaboration ?", "position": 23, "acceptedAnswer": { "@type": "Answer", "text": "Des complications médicales et des réadmissions fréquentes peuvent en résulter." } }, { "@type": "Question", "name": "Comment évaluer l'impact des complications sur les soins ?", "position": 24, "acceptedAnswer": { "@type": "Answer", "text": "Par des analyses de données sur les résultats cliniques et la satisfaction des patients." } }, { "@type": "Question", "name": "Quelles sont les conséquences d'une mauvaise dynamique d'équipe ?", "position": 25, "acceptedAnswer": { "@type": "Answer", "text": "Une mauvaise dynamique peut entraîner un turnover élevé et une baisse de la qualité des soins." } }, { "@type": "Question", "name": "Quels facteurs augmentent le risque de conflits ?", "position": 26, "acceptedAnswer": { "@type": "Answer", "text": "Des différences culturelles et des styles de communication variés peuvent augmenter les conflits." } }, { "@type": "Question", "name": "Comment le stress influence-t-il les relations interprofessionnelles ?", "position": 27, "acceptedAnswer": { "@type": "Answer", "text": "Le stress peut réduire la communication et augmenter les tensions entre les professionnels." } }, { "@type": "Question", "name": "Quels facteurs de risque sont liés à la collaboration ?", "position": 28, "acceptedAnswer": { "@type": "Answer", "text": "Un manque de formation et des horaires de travail chargés peuvent nuire à la collaboration." } }, { "@type": "Question", "name": "Comment les différences de statut affectent-elles les relations ?", "position": 29, "acceptedAnswer": { "@type": "Answer", "text": "Les différences de statut peuvent créer des déséquilibres et des tensions dans l'équipe." } }, { "@type": "Question", "name": "Quels facteurs environnementaux influencent la collaboration ?", "position": 30, "acceptedAnswer": { "@type": "Answer", "text": "Un environnement de travail positif et des ressources adéquates favorisent la collaboration." } } ] } ] }

Sources (10000 au total)

Enhancing Pressure Injury Surveillance Using Natural Language Processing.

This study assessed the feasibility of nursing handoff notes to identify underreported hospital-acquired pressure injury (HAPI) events.... We have established a natural language processing-assisted manual review process and workflow for data extraction from a corpus of nursing notes across all medical inpatient and intensive care units i... Our initial corpus involved 70,981 notes during a 1-year period from 5484 unique admissions for 4220 patients. Our interrater human reviewer agreement on identifying HAPI was high ( κ = 0.67; 95% conf... Natural language processing-based surveillance is proven to be feasible and high yield using nursing handoff notes....

Identification of Preanesthetic History Elements by a Natural Language Processing Engine.

Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of re... For each patient, we collected all pertinent notes from the institution's electronic medical record that were available no later than 1 day before their preoperative anesthesia clinic appointment. Per... A total of 93 patients were included in the NLP pipeline input. Free-text notes were extracted from the electronic medical record of these patients for a total of 9765 notes. The NLP pipeline and anes... In this proof-of-concept study, we demonstrated that utilization of NLP produced an output that identified medical conditions relevant to preanesthetic evaluation from unstructured free-text input. Au...

MedLexSp - a medical lexicon for Spanish medical natural language processing.

Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, le... This article describes an unified medical lexicon for Medical Natural Language Processing in Spanish. MedLexSp includes terms and inflected word forms with PoS information and Unified Medical Language... The lexicon is distributed in a delimiter-separated value file; an XML file with the Lexical Markup Framework; a lemmatizer module for the Spacy and Stanza libraries; and complementary Lexical Record ...

The use of natural language processing in palliative care research: A scoping review.

Natural language processing has been increasingly used in palliative care research over the last 5 years for its versatility and accuracy.... To evaluate and characterize natural language processing use in palliative care research, including the most commonly used natural language processing software and computational methods, data sources,... A scoping review using the framework by Arksey and O'Malley and the updated recommendations proposed by Levac et al. was conducted.... PubMed, Web of Science, Embase, Scopus, and IEEE Xplore databases were searched for palliative care studies that utilized natural language processing tools. Data on study characteristics and natural l... 197 relevant references were identified. Of these, 82 were included after full-text review. Studies were published in 48 different journals from 2007 to 2022. The average sample size was 21,541 (media... We found 82 papers on palliative care using natural language processing methods for a wide-range of topics and sources of data that could expand the use of this methodology. We encourage researchers t...

A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome.

The evolution of the Exposome concept revolutionised the research in exposure assessment and epidemiology by introducing the need for a more holistic approach on the exploration of the relationship be... We conduct a literature search on PubMed, Scopus and Web of Science for scientific articles published between 2011 and 2021. We use both quantitative and qualitative methods to screen papers and provi... Overall, 6420 articles were screened for the suitability of this review, where we review 37 articles in depth. Finally, we discuss future avenues of research and outline challenges in existing work.... Our results show that (i) there has been an increase in articles published that focus on applying NLP to exposure and epidemiology research, (ii) most work uses existing NLP tools and (iii) traditiona...

Natural Language Processing of Radiology Reports to Detect Complications of Ischemic Stroke.

Abstraction of critical data from unstructured radiologic reports using natural language processing (NLP) is a powerful tool to automate the detection of important clinical features and enhance resear... We trained machine learning classifiers to identify categorical outcomes of edema, midline shift (MLS), hemorrhagic transformation, and parenchymal hematoma, as well as rule-based systems (RBS) to ide... In all data sets, a deep neural network with pretrained biomedical word embeddings (BioClinicalBERT) achieved the highest discrimination performance for binary prediction of edema (area under precisio... Our study demonstrates robust performance and external validity of a core NLP tool kit for identifying both categorical and continuous outcomes of ischemic stroke from unstructured radiographic text d...

Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.

To establish whether or not a natural language processing technique could identify two common inpatient neurosurgical comorbidities using only text reports of inpatient head imaging.... A training and testing dataset of reports of 979 CT or MRI scans of the brain for patients admitted to the neurosurgery service of a single hospital in June 2021 or to the Emergency Department between... For "brain compression", a random forest classifier outperformed other candidate algorithms with an accuracy of 0.81 and area under the curve of 0.90 in the testing dataset. For "brain edema", a rando... A natural language processing-based machine learning algorithm can reliably and reproducibly identify selected common neurosurgical comorbidities from radiology reports.... This result may justify the use of machine learning-based decision support to augment provider documentation....