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Validation of an assessment tool for direct observation performance skills at triage (DOPS-T) for the health care professionals in the emergency department of tertiary care hospital - a work place based assessment

2018· dissertation· en· W6987896751 sur OpenAlexaboutno aff

Notice bibliographique

RevueeCommons - AKU (Aga Khan University) · 2018
Typedissertation
Langueen
DomaineMedicine
ThématiqueInnovations in Medical Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTriageEmergency departmentHealth careScale (ratio)Test (biology)AttendanceCertificationAcute careMEDLINEEmergency nursing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Workplace based assessment is an effective way to measure the knowledge translation into clinical practice and has an important place in residency education with emphasis on skill acquisition and enhancement of learning through effective feedback. One of the goals of academic programmes in emergency medicine is to develop expertise in triage. Triage in the emergency department (ED) is the first contact point of a patient with the health care where patients are categorized as per their disease acuity which in turn can determine how fast the patient would be provided care. No instrument for workplace-based assessment of triage skills in the ED could be found. This study was aimed to develop and validate a tool for Direct Observation of Performance Skills at Triage (DOPS-T) for health care professions (HCPs) in the ED. Method The study was conducted at the emergency department of Sultan Qaboos University Hospital (SQUH) after ethics approval. SQUH is a tertiary care hospital at Muscat, Oman. Fifty HCPs (25 nurses and 25 physicians) were included in the study after informed consent. All HCP's underwent a Canadian Triage and Acuity Scale (CTAS) certification course. The change in knowledge was assessed by pre-test and post-test. After three months all FICP's were observed for their triage performance skills during the morning, evening and night shifts by two independent assessors in real-time clinical setting. Nine — point DOPS-T scale was utilized to rate the performance. SPSS version 22 and Stata version 12 were used for data analysis. Spearman correlation and interclass correlation test were used to calculate construct validity and inter-rater reliability. Effect size was calculated using Cohen's d. Learner's satisfaction and feedback were recorded. Feasibility was assessed by professionals' satisfaction and time spent in observation and providing feedback. Results Significant improvement in knowledge pertaining to triage was noticed in post-test (88.214.0) as compared to pre-test (42.2+9.0). Three hundred items were recorded using the direct observation of performance skills at triage (DOPS-T) tool for nurses and physicians. DOPS-T overall mean score on the 9-point Likert scale ±1 SD was 76.7112.44 (minimum-maximum: 57.78 - 96.67). Score was highest (8.4811.22) for 'taking the vital signs', followed by 'communication skills' (8.2110.96) while lowest score (6.32+1.58) was observed for 'reassessment done appropriately on separate items on the scale'. Summed scores were high in all the three shifts that is morning, evening and night for HCPs with more than 5 years of experience (79.12110.86 vs 74.03+8.29). Inter-rater reliability was high for assessors (ICC = 0.918 (95%0: 0.89-0.94) as well as for DOPS-T score (95%CI: 0.89-0.94). Inter-item correlation matrix showed moderate correlation. Internal consistency calculated by Cronbach's alpha was 0.911. The assessment process was rated as "very satisfied" (7-8 on a 9-point Likert scale).Mean time (±1SD) to complete the DOPS-T tool by the assessors was 15.4514.76 minutes while giving feedback took 5.77±1 .22 minutes. Conclusion The study demonstrated that recently developed DOPS-T instrument showed construct validity and reliability for direct observation of performance skills at triage for nurses and physicians. DOPS-T is feasible to be used despite of distinctive ED work hours.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,324
Score d'incertitude au seuil0,874

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,016
Tête enseignante GPT0,355
Écart entre enseignants0,339 · 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
Publié2018
Routes d'admission1
Résumé présentoui

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Même revueeCommons - AKU (Aga Khan University)Même sujetInnovations in Medical EducationTravaux en français237 207