93 Mapping Mobile Health Clinics in Canada: Delivering Equitable Primary Care to Children and Vulnerable Populations
Notice bibliographique
Résumé
Abstract Background Low-income and racially diverse populations often have multiple barriers in accessing healthcare and are at increased risk of poor health outcomes. COVID-19 exacerbated these health inequities: decreased in-person appointments, difficult access to virtual care and deprioritization of elective clinical activity led to delays in well-child visits and vaccination. This public health emergency highlighted a need to develop alternative models to enable access to primary care for vulnerable children. While mobile clinics are well-established in the United States, little is known about them in Canada. Objectives This study aims to characterize Canadian mobile clinics providing primary care health services to vulnerable populations, including children, and seeks to inform the implementation of a pediatric mobile clinic under development. Design/Methods This environmental scan screened scientific databases and the grey literature using a combination of terms designating mobile health clinics and Canadian locations. Relevant Canadian primary care mobile clinic initiatives were subsequently included. We defined primary care mobile clinics as movable health care units providing primary healthcare services delivered by general medical practitioners (pediatricians and family physicians). Examples of excluded initiatives were mobile clinics focused on education/literacy, dental care, vision care, endocrinology, cancer screening, safe injection sites, vaccination, physical rehabilitation and urgent care. Descriptive statistics and qualitative analysis were performed. Results 29 clinics were identified, of which 26 are still active. Most clinics were located in Ontario (n=11), followed by British Columbia (n=8), Alberta (n=5), Quebec (n=2) and the Maritimes (n=2). The first mobile clinic in Canada was launched in 1996, with an increasing number of new clinics in 2021. While all clinics served vulnerable populations, some targeted specific groups, such as children, people experiencing homelessness, immigrants, LGBTQ+ individuals and Indigenous peoples. We identified three pediatric mobile clinics, two of which targeted teenagers. Onboard the clinics, physicians often worked with nurses, outreach workers and social workers. These professionals provided primary care services, as well as healthcare navigation, sexual education, mental health care, harm reduction supplies, vaccination and emergency care. All mobile clinics partnered with their local government, charities or businesses to fund their initiative. Conclusion Mobile health clinics are a growing model of primary care in Canada. They are the result of a multidisciplinary collaboration between healthcare providers, social workers and outreach workers. To this date, Canadian pediatric mobile clinics remain a handful and represent an interesting avenue to address health inequities in children, during the pandemic and beyond.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,006 | 0,013 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».