Facilitating Access to Care for Children With Complex Health Needs Through Low-Barrier Place-Based Intake Processes: Lessons From the RICHER Social Pediatric Model
Notice bibliographique
Résumé
INTRODUCTION/OBJECTIVES: Exposure to adverse social determinants of health (SDoH) in childhood is associated with poorer long-term health outcomes. Within structurally marginalized populations, there are disproportionately high rates of developmentally vulnerable children. The RICHER (Responsive, Intersectoral, Child and Community Health, Education and Research) social pediatric model was designed to increase access to care in marginalized neighborhoods. The purpose of this study was to describe the children and youth engaged with the RICHER model of service and characterize the needs of the population. METHODS: A retrospective chart review was conducted on children and youth who accessed primary care services through the program between January 1, 2018 and April 30, 2021. Basic descriptive data analysis was done using Stata v15.1. RESULTS: A total of 210 charts were reviewed. The mean age in years at initial assessment was 6.32. Patients most commonly identified their race/ethnicity as Indigenous (33%) and 15% were recent newcomers to Canada. Evidence of at least 1 adverse SDoH was noted in 41% of charts; the most common included material poverty (34%), food insecurity (11%), and child welfare involvement (20%). The median number of diagnoses per patient was 4. The most frequently documented diagnoses were neurodevelopmental disorders (50%) including developmental delay (39%), ADHD (32%), and learning disability (26%). The program referred 72% of patients to general pediatricians and/or other subspecialists; 34% were referred for tertiary neuropsychological assessments and 35% for mental health services. CONCLUSIONS: Our data suggests that this low-barrier, place-based primary care RICHER model was able to reach a medically, developmentally, and socially complex population living in disenfranchised urban neighborhoods. Half of the patients identified in our review had neurodevelopmental concerns and a third had mental health concerns, in contrast to an estimated 17% prevalence for mental health, behavioral, or developmental disorders in North American general pediatric aged populations. This highlights the impact adverse SDoH can have on child health and the importance of working with community partners to identify developmentally vulnerable children and support place-based programs in connecting with children who may be missed, overlooked, or disadvantaged through traditional models of care.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».