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Enregistrement W4390957032 · doi:10.5334/ijic.icic23260

ICT-Refugee: The development, implementation, and evaluation of an integrated care team to support refugee patients as they transition from temporary to permanent primary care

2023· article· en· W4390957032 sur OpenAlexaffabout
Catherine Tong, Alexandra Whate, Wajma Attayi, Debbie Engel, Jacobi Elliott, Paul Stolee

Notice bibliographique

RevueInternational Journal of Integrated Care · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiqueInterpreting and Communication in Healthcare
Établissements canadiensUniversity of WaterlooLawson Health Research InstituteCentre for Community Based ResearchCentre for Family Medicine
Organismes subventionnairesnon disponible
Mots-clésRefugeeInformation and Communications TechnologyHealth careNursingMedicineAgency (philosophy)Government (linguistics)Political scienceSociology

Résumé

récupéré en direct d'OpenAlex

Upon arrival to Canada, government assisted refugees typically can access settlement services and universally funded health care; health care may be delivered through refugee health clinics, which are meant offer temporary care until patients are stable and able to transition to a permanent primary care practice (PCP). In Southern Ontario, Canada, we evaluated the development and implementation of an integrated care team (ICT-Refugee) that supports refugee patients and receiving clinics in this transition. Several refugee health and service organizations partnered with the local Ontario Health Team (the regional health administrative body) to offer this program. All Ontario Health Teams have patient partners who attend strategic planning sessions and approve programming. This initiative was also guided by ICT members (see below), some of whom are refugees themselves, and who shared their perspectives on what would and would not work in their respective communities. Launched in January 2022, the ICT-Refugee program includes access to an on-demand interpretation service, and the interdisciplinary ICT. Members of the team include: two discharge and intake coordinators (at refugee health clinics), a case manager, a pharmacist, three “newcomer system navigators”, and representatives from home and community care services and a refugee settlement agency. To date (the program and evaluation are ongoing), the ICT has transitioned 499 patients to 15 primary care practices. All 499 patients were offered access to the ICT, and 41 self-selected or were referred by their new practice to receive more intensive, interdisciplinary support from the ICT (8%). Our evaluation team has observed 22 ICT meetings, composed field notes, and consolidated program statistics. To understand the development and impact of the program, we interviewed all ICT staff (n=9), and six patients (in three languages, with interpreters) . Interviews were digitally recorded, then anonymized and uploaded into NVivo 12 for thematic analysis. The 41 patients requiring ICT supports in 2022 (Jan-Nov.) received 396 hours of interdisciplinary care/supports over 833 sessions. Patients had high and diverse needs. Approximately 20% of these hours were spent directly linking or referring patients to community resources. In addition to navigating the medical transition, the ICT supported patients with education, employment, finances, mental health, transportation, social isolation, and other needs. Staff noted that it was easier to attend to the patients’ medical needs (e.g. getting to their appointments), once the basics of survival (e.g. food, housing) were addressed. The evaluation identified many lessons learned in the first year, including: expect the development and refinement of an ICT program to take time (it cannot be designed, refined, and implemented with demonstrated impact in one year); embedding interpretation services into all aspects of the program was essential; it can be challenging to find clinics willing to accept refugee patients; patients are unique and will required a tailored approach and care plan; and, these types of programs are essential for bridging health and social care services, which in our region had previously been operating in silos. ICT support of refugee patients is ongoing. PCPs will be interviewed in the next phase of the evaluation.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,016
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,310
Score d'incertitude au seuil0,616

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0160,017
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,002
Communication savante0,0020,001
Science ouverte0,0020,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,049
Tête enseignante GPT0,446
Écart entre enseignants0,396 · 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 source (Gemma direct ou Codex distillé), 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
Publié2023
Routes d'admission2
Résumé présentoui

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