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Implementing dysphagia assessment in stroke patients: Hospital-based education quality improvement project

2015· article· en· W6982430547 sur OpenAlexaboutno aff

Notice bibliographique

RevueJournal of the Arkansas Academy of Science · 2015
Typearticle
Langueen
DomaineMaterials Science
ThématiqueX-ray Diffraction in Crystallography
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDysphagiaStroke (engine)Descriptive statisticsAspiration pneumoniaPneumoniaPrimary care
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Dysphagia is a prevalent manifestation of stroke. An evidence-based dysphagia assessment is needed to provide quality care to stroke patients. Aims: To provide a descriptive analysis of the patient’s admitted to the hospital with the primary diagnosis of stroke; to evaluate three dysphagia screening tools; and to develop an education program to address training and implementation of the chosen dysphagia assessment tool on pilot units. Design: Descriptive analysis, and an educational program. Setting: Local hospital in Northwest Arkansas. Patients: Pre-data included patients with the primary diagnosis of stroke, over the age of 18, excluding those identified with cognitive impairment, admitted to the local hospital between August 2013 and August 2014. Methodology: Phase I was conducted during May to July 2014 and consisted of comparing three dysphagia screening tools; Barnes Jewish Hospital Stroke Dysphagia Screen, the Toronto, and the Gugging Swallow Screen. Next a retroactive medical record review of patients over the age of 18 admitted to the hospital between August 2013 and August 2014, with the primary diagnosis of stroke was conducted. Patients identified with cognitive impairment were excluded from the study. The charts were evaluated to determine: if a dysphagia assessment was administered and how soon following admission to the hospital, the rate of documented pneumonia (information from nurses notes, physician notes, and chest x-ray), medications, occurrence of diagnostic tests, and bed positioning. Phase II consisted of development and implementation of an education program based on the hospital adopted dysphagia assessment tool. Analysis: A descriptive analysis and summary statistics were performed to summarize the information obtained through a review of medical records from patients admitted with the primary diagnosis of stroke. Results: Of the charts analyzed, 94 met the study’s inclusion criteria. Of the 94 charts analyzed, 23 charts did not include a dysphagia assessment. Of the 94 charts analyzed, 44 charts revealed administration of PO medications before the documentation of a dysphagia assessment. Of the 44 patients who received PO medications before a dysphagia assessment, 12 charts revealed no documentation of one of the diagnostic tests included in the study, in other words, no documentation of a chest x-ray. Of the 12 charts that revealed no chest x-ray, as well as PO medications before a dysphagia assessment, 4 were declared an aspiration risk. Of the 94 charts analyzed, 2 charts had documented pneumonia at discharge. Conclusion: The data in this study shows the need for dysphagia assessment and the literature shows the evidence of this need. While the national organizations have not chosen a superior dysphagia screen, the hospital in this study has. The Barnes Jewish Hospital Stroke Dysphagia Screen/ASDS is the dysphagia screen of choice for the hospital in this study, which was implemented in September 2014. The goal of a bedside dysphagia assessment is to detect those suffering from dysphagia with an easy-to-use tool that can be performed by many professions, including nursing. Therefore, nurses must be aware of this need and solution to care. The organization may implement the assessment, but it is up to the nurses to carry out the implementation. Further assessment should be completed to assess the compliance with the newly implemented dysphagia assessment tool in relation to the education program created and presented to the hospital during this study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,517
Score d'incertitude au seuil0,406

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0090,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,371
Écart entre enseignants0,340 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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