106 Understanding the Impact of COVID-19 on Healthcare for Medically-Complex Children and Youth
Notice bibliographique
Résumé
Abstract Primary Subject area Complex Care Background COVID-19 and associated pandemic measures have disproportionately affected already vulnerable populations, including medically-complex children and youth. In Canada, about one percent of children and youth aged 0 to 18 years (inclusive) are medically complex, which is characterized by having complex, chronic conditions that require specialized care, high healthcare service usage, and functional dependence. In addition to being high users of formal healthcare services, it is estimated that parents spent an average of 52 hours per week providing unpaid care. Objectives As part of a larger study exploring the effect of the pandemic on these children and their families, the impact on healthcare usage by this population was investigated. Design/Methods In August 2020, a web-based cross-sectional survey was conducted with parents of medically-complex children and youth in British Columbia, Canada. A convenience sample was recruited through posting advertisements on social media platforms, word of mouth, and amplifying the study via the media. The survey, co-created with parent co-researchers, was comprised of 93 questions. It was divided into three sections that focused on pre- and post-pandemic questions about a) medically complex child(ren), b) family/household/community characteristics, and c) respondent demographics. Data were analyzed using descriptive statistics. Results Results illustrate the largely negative impact of the pandemic on this population’s healthcare usage. The survey was completed by 156 parents, mainly mothers (92.3%) who reported information for 188 medically complex children and youth. The children ranged in age from 0 to 18 years, with an average age of 9.5 years, and 58.0% were boys. Between February and August 2020, 30.3% of children had visited the emergency department and the same percentage had parents who avoided taking them in circumstances where they typically would have. 36.2% of the children had been admitted to hospital during that period. The children typically saw an average of four medical specialists and during the pandemic 63.8% had a specialist appointment cancelled or postponed by the clinic. During this time, there was also a steep decline or stoppage of all allied health therapies. Conclusion These results demonstrate a lack of pandemic preparedness to ensure continuity of services. Consequently, medically complex children and youth may be missing key interventions to address ongoing health issues and maintain functional abilities. More proactive planning and coordination are needed to ensure that future situations will not lead to lack of access or therapy for this vulnerable group.
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 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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».