76 Practices and infrastructure to support patients and families who speak languages other than English (LOE) in Ontario Paediatric Inpatient Units: A multicentre survey study
Notice bibliographique
Résumé
Abstract Background Patients who use languages other than English (LOE) for healthcare communication are at increased risk for adverse events and worse health outcomes in paediatric care settings. Effective communication practices (such as using interpreters) and supports addressing factors such as a sense of belonging and trust are critical to improving health outcomes. We must understand the policies, procedures and practices currently in place in the paediatric inpatient units to support these patients and families. Objectives The objective of this study was to understand the current policies, procedures, processes and infrastructure to support children and families who use LOE for healthcare communication in paediatric inpatient units across Ontario. Design/Methods We conducted a cross-sectional multi-site survey study of paediatric inpatient unit leaders at hospitals in Ontario, Canada. The web-based survey asked multiple choice and open-ended questions about how the unit identifies patient and caregiver language needs, availability and types of interpreter services, frequency and modality of interpreter use on the unit, training on interpreter use provided to staff, tracking of patient safety events involving patients with LOE, and perceived facilitators and barriers to providing care in a patient’s LOE. Quantitative data was analyzed using descriptive statistics, and qualitative data was analyzed using content analysis. Results Responses were received from paediatric inpatient leaders at 25 (83%) of 30 hospitals. Only 11 (44%) of the 25 hospitals had a formal policy for identifying language needs through standardized screening tools or processes. 15 (60%) of the sites surveyed reported that they do not routinely identify interpreter requirements on admission. Less than one-third of the inpatient units had a formal documentation process to ensure that the need for interpreter services was consistently communicated throughout their care. Units report being unable to identify specific health outcome data for patients with LOE as specific data is not collected. Qualitative comments identify challenges including lack of consensus in tools and terminologies and resources for interpreters. There was wide recognition of significant opportunities to better support these patients. Conclusion Despite the recognized importance of interpreters, many paediatric inpatient units lack the foundational processes, procedures and infrastructure to most effectively support patients and families who use LOE. The findings underscore the need for standardized policies and procedures to identify patients and families with LOE so that we effectively support patients. It is important to collect data to help identify and address healthcare disparities for these patients. Our foundational work can help drive ongoing equity-centered design.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».